arXiv Daily Digest - 2026-05-15

Scaling Scientific Machine Learning (SciML) toward universal foundation models is bottlenecked by negative transfer: the simultaneous co-training of disparate partial differential equation (PDE) regimes can induce gradient conflict, unstable optimization, and plasticity loss in dense neural operators. In particular, broadband open-channel fluid dynamics and boundary-dominated porous media flows impose incompatible spectral and geometric demands on a single dense parameter path. We introduce Shodh-MoE, a sparse-activated latent transformer architecture for multi-physics transport. Shodh-MoE operates on compressed 16^3 physical latents produced by a physics-informed autoencoder with an intra-tokenizer Helmholtz-style velocity parameterization, restricting decoded states to divergence-free velocity manifolds. The model guarantees exact mass conservation, achieving a physically verifiable velocity divergence of ~2.8 x 10^-10 (evaluated post-hoc in FP64) on 128^3 grids. A Top-1 soft-semantic router dynamically assigns localized latent patches to expert subnetworks, enabling specialized parameter paths for distinct physical mechanisms while preserving shared experts for universal symmetries. In a 20,000-step distributed pretraining run over mixed three-dimensional physical tensors, routing telemetry shows autonomous domain bifurcation: held-out validation tokens from the open-channel domain route exclusively to Expert 0, while porous-media tokens route exclusively to Expert 1. The model converges simultaneously across both regimes, achieving latent validation MSEs of 2.46 x 10^-5 and 9.76 x 10^-6, and decoded physical MSEs of 2.48 x 10^-6 and 1.76 x 10^-6. These results support sparse expert routing as a practical architectural mechanism for mitigating multi-physics interference in universal neural operators.

In epithelia, how do collective cell migration and tissue spatial organization feedback on each other? We address this question through large-scale numerical simulations of the cellular Potts model. By accounting for both cell morphology and cytoskeletal activity, we uncover a remarkably rich phase diagram featuring multiple types of orientational order, either as distinct phases or coexisting across length scales. We identify a specific pathway in parameter space along which a gradual increase in the actin polymerization rate drives a phase transition into a long-range flocking state. Simultaneously, quasi-long-range nematic order emerges at length scales much larger than the cell size due to the combined effects of directed motion and lateral cell-cell interactions. At length scales comparible to cell size, however, cells adopt an approximatively hexagonal morphology, resulting in hexanematic order, similar to that observed in reconstituted Madin-Darby Canine Kidney (MDCK) cell monolayers. With further increases in actin polymerization, nematic order becomes fully long-range, while hexatic order remains quasi-long-range and confined to short length scales, but independent of cytoskeletal activity. When noise is sufficiently low to allow crystallization at finite actin polymerization rate, cycling the cell-monolayer across the melting transition yields an example of phenotypical hysteresis, reminiscent of that observed across the epithelial-mesenchymal transition.

A silicon microring resonator with an anisotropic beryllium sulfide (BeS) cladding is proposed for polarization-selective detection of exhaled-breath volatile organic compound biomarkers. The anisotropic dielectric response of BeS enables the transverse-electric (TE) and transverse-magnetic (TM) modes to probe orthogonal components of the cladding permittivity tensor, generating two independent optical observables from a single device. Five clinically relevant biomarkers are investigated: acetone, isoprene, 4-hydroxyhexenal, 2-propenal, and benzene. First-principles optical constants are incorporated into three-dimensional finite-difference time-domain simulations to evaluate the sensing response. The TE mode exhibits a uniform resonance shift of 0.263 nm across all analytes and serves as a concentration reference channel, while the TM mode produces analyte-specific shifts ranging from 0.200 to 0.426 nm. A unique TM amplitude inversion is observed for benzene, enabling additional discrimination. The resulting dual-polarization response forms a two-dimensional optical fingerprint that distinguishes all five biomarkers without requiring a sensor array or multiple functionalized resonators. The device achieves quality factors of 4520 and 3151 for the TE and TM modes, respectively, with sensitivities up to 6.5 nm/RIU, figures of merit up to 14.9 RIU^-1, and detection limits as low as 1.5 mRIU. Cross-sensitivity analysis further shows that CO2 and H2O produce negative TM resonance shifts, separating interferents from target biomarkers in the fingerprint plane. The proposed platform demonstrates a compact route toward array-free photonic breath analysis using intrinsic cladding anisotropy.

Efficient and selective excitation of lattice vibrations is central to controlling energy flow at the nanoscale, yet remains challenging under conventional optical excitation. Here, we introduce a mid-infrared-assisted phonon amplification approach, termed MIRAPA, that enables efficient energy injection directly into vibrational bonds. Using surface-enhanced resonant Raman scattering in few-layer $\mathrm{MoS_2}$, we exploit strong exciton--phonon coupling to monitor phonon populations. When mid-infrared (MIR) light is introduced, it couples directly to out-of-plane lattice vibrations, leading to room-temperature phonon amplification exceeding $80\%$. Crucially, MIRAPA bypasses electronic excitation pathways, allowing the MIR power density to be nearly $300\times$ lower than that required for visible excitation to achieve comparable enhancement. The resulting phonon modulation is robust, persisting over more than $2800$ on/off cycles and exceeding $15$ hours of continuous-wave laser illumination without degradation. Quantitative analysis yields an effective noise-equivalent power of approximately $0.3\,\mathrm{nW}/\sqrt{\mathrm{Hz}}$ for MIR detection, highlighting the sensitivity of the approach. By combining vibrational selectivity, low-power operation, and long-term stability, MIRAPA provides a robust platform for probing and amplifying phonons in two-dimensional semiconductors. These results open new opportunities for nanoscale vibrational sensing, mid-infrared detection, and phonon-based coherent devices, including routes toward phonon lasing.

This paper presents the first systematic application of a material homotopy continuation framework for efficient, automated computation of dispersion curves in viscoelastic waveguides of arbitrary cross-section. A material homotopy continuously maps the original lossy problem to an auxiliary lossless one via an attenuation parameter s in [0,1], addressing the core challenges of the non-Hermitian eigenvalue problem. Grounded in analytic perturbation theory, the method guarantees branch identity continuity--a one-to-one correspondence between solutions at s=0 and s=1--provided the real-parameter path does not cross any exceptional points. Under a Type I exceptional point topology, physical mode labels established at the elastic stage remain valid at the viscoelastic stage without post-processing, yielding the characteristic real-part veering with imaginary-part crossing. The decoupling strategy performs reliable mode tracking in the Hermitian regime via adaptive wavenumber refinement, then propagates a sparse set of key solutions to the target viscoelastic state through predictor-corrector homotopy continuation. Numerical examples across symmetric and unsymmetric laminates validate the framework's robustness and efficiency, with the majority of cases verified at a loss factor of approximately 0.003 and a single symmetric laminate providing additional support at 0.02. For a challenging unsymmetric laminate at a loss factor of 0.05, the method still produces numerically accurate solutions; two complementary diagnostic signatures--an extremely sharp imaginary-part crossing and a discernible discrepancy between spectral group velocity and energy flux velocity--warn of potential label mismatch and guide further analysis.

We present an $\mathcal{O}(L^3)$ algorithm for evaluating contracted Clebsch--Gordan tensor products in $\mathrm{O}(3)$-equivariant machine learning potentials at fixed Canonical Polyadic (CP) rank. Mapping the angular integral to a structured Gauss--Legendre and Fourier tensor-product grid decouples the radial channel contractions from the angular transforms. The antisymmetric parity-odd Clebsch--Gordan channels, unreachable by the symmetric pointwise product on a scalar $S^2$ grid, are recovered through the surface-curl pairing $\hat r \cdot [\nabla_{S^2} A \times \nabla_{S^2} B]$, the spherical Poisson bracket, which supplies the $L=1$ angular momentum on the grid while preserving rotational equivariance. The construction extends to parity-aware equivariant message passing in atomic-cluster-expansion-style architectures and is verified by direct numerical quadrature. The full uncontracted Clebsch--Gordan tensor product remains subject to the $\mathcal{O}(L^4)$ output-size lower bound. A benchmark shows wall-clock scaling empirically as $L^2$ across the practical $l_{\max}$ range. For the on-site contraction this is pre-asymptotic, giving way to $L^3$ at large $l_{\max}$. For message passing it is structural and the runtime is memory-bandwidth bound on $L^2$-sized grid tensors.

Actively tunable nanophotonic platforms that control light-matter interactions enable reconfigurable optical systems and programmable photonic integrated circuits. Hydrostatic pressure provides a noninvasive and material-agnostic mechanism for modulating the refractive index and resonance conditions without introducing free carriers or structural damage. Here, we demonstrate multiple pressure-dependent functionalities in silicon nitride nanostructures, including resonance tuning, refractive index modulation, and polarization state conversion. Applying a pressure of up to 5 GPa, we observe a Fabry-Pérot resonance shift of up to 30 nm and a relative refractive index decrease of up to 4%. Based on the results, we design and examine, to the best of our knowledge, the first extreme-pressure-tunable, polarization-converting metasurface, which tunes the ellipticity and orientation angle of the output light. These findings establish pressure-controllable silicon nitride as a viable platform for reconfigurable photonics and extreme-environment nanophotonic systems, including deep-ocean exploration, planetary interiors, and space applications.

Scintillators convert ionizing radiation into visible photons, enabling applications from cosmic ray detection to medical imaging. Two independent strategies for improving scintillator performance via nanoscale patterning have recently been demonstrated: engineering material properties to enhance absorption of ionizing radiation and integrating nanophotonic structures to enhance the spontaneous emission rate ("nanophotonic scintillators"). Here, we propose a nanophotonic scintillator that simultaneously enhances both the initial energy conversion and the spontaneous emission rate, by periodically stacking a fast-emitting scintillator and a visible-light-transparent material with strong X-ray attenuation ("stopping layer") to form a one-dimensional (1D) photonic crystal (PhC) scintillator. Photoelectric absorption in the stopping layer increases the number of photoelectrons that deposit energy in neighboring scintillator layers and contribute to scintillation. At the same time, the spontaneous emission rate is enhanced by the nanophotonic structuring itself. We design a 1D PhC comprising an organic scintillator and indium tin oxide (ITO) as the stopping layer and numerically simulate the enhancement in scintillation yield and decay rate. The total detected light output is enhanced by up to a factor of 700 compared to a bulk organic scintillator of equal thickness. We further investigate a 1D PhC structure integrating inorganic and organic scintillators for time-of-flight positron emission tomography (TOF-PET): replacing the non-scintillating stopping layer with an inorganic scintillator further increases the light yield, and the coincidence time resolution (CTR) is enhanced up to 3.5 times compared to a bulk inorganic scintillator of equal thickness. Our work presents a unified approach to improve key scintillation parameters within a single nanophotonic structure.

Positronium-based imaging requires realistic modelling of positronium (Ps) decay in matter. We introduce a modular Ps decay model implemented in GATE 9.4 and GATE 10, enabling the definition of an arbitrary number of decay channels characterised by lifetime, branching fraction, annihilation multiplicity (2g/3g), and optional prompt photon emission. The model is validated through analytical and numerical benchmarks, including lifetime distributions, branching fraction consistency, photon kinematics, and prompt photon emission. Its practical applicability is demonstrated using simulations of mixed annihilation scenarios and the NEMA IEC phantom with a large field-of-view PET system. The proposed model accurately reproduces input lifetime distributions as weighted sums of exponential components and correctly samples decay channel fractions. Simulated two- and three-photon annihilation kinematics are consistent with theoretical expectations. Complex mixtures of decay channels, including varying 3g-to-2g ratios and multi-component ortho-positronium lifetimes, are correctly modelled, with observable signatures reflected in both temporal and energy distributions. Phantom simulations demonstrate the capability to generate realistic positronium-sensitive datasets. This work provides the first general-purpose, multi-channel positronium decay model integrated into GATE, enabling realistic simulations of positronium behaviour in complex media. The model supports the development and optimisation of positronium-based imaging techniques, including PLI and multi-photon PET, and applies to medical imaging, industrial tomography, and fundamental physics studies. Its public availability and compatibility with standard GATE workflows make it a valuable tool for the broader research community.

Physical Unclonable Functions (PUFs) are hardware security primitives whose inherent physical complexity can be exploited for secure authentication and cryptographic key generation. Silicon photonic devices, owing to their suitability for quantum and artificial intelligence applications alongside standard CMOS fabrication processes, constitute a highly promising substrate for integrated multifunctional PUFs. Despite the advanced security guarantees offered by quantum cryptographic protocols and the central role of silicon photonics in quantum technologies, quantum readout strategies based on single-photon states for photonic PUFs remain largely unexplored. In this work, we experimentally demonstrate a silicon nitride (SiN) programmable photonic Mach Zehnder interferometer mesh that implements a unitary transformation and operates as a PUF, whose secret physical signature arises from uncontrollable waveguide variations during fabrication. Using experimentally derived parameters from the SiN integrated mesh, we further introduce and numerically evaluate a quantum readout protocol that combines single-photon states with PUFs. Maximally mixed quantum states are employed to conceal the underlying unitary transformation from passive eavesdropping. Security against adversaries possessing devices fabricated under similar conditions is assessed, with authentication performance quantified through Monte Carlo analysis of the false acceptance and false rejection rates as a function of the number of detected events and corrected errors. The results indicate exceptional performance with equal error rates as low as 10 to the minus 14, highlighting the potential of quantum secure PUFs for high security authentication applications.

Plant sap-feeding insects must dispose of excess fluid, yet at millimeter scales droplet release is constrained by capillary adhesion and contact-line pinning. How phloem-feeding insects solve this puzzle, particularly as the excretory apparatus changes in size and form from nymph to adult, has remained unclear. Combining micro-CT, high-speed imaging, measurements of honeydew properties, and reduced-order modeling, we show that the spotted lanternfly (Lycorma delicatula) uses distinct release mechanics across ontogeny. Nymphs release honeydew with an anal stylus that acts as a capillary rectifier, imposing a curvature asymmetry that biases the attached droplet toward detachment through a Laplace-pressure difference. Adults use a longer stylus associated with an elastic basal region, maintain stylus-droplet contact through a finite compression phase, and release droplets with greater translational and rotational momentum. In both stages, stylus rotation is ultrafast, with peak angular accelerations of order $10^7$ rad/s$^{-2}$ and release unfolding on millisecond timescales, yet droplet ejection speed remains below stylus tip speed. Weber-Bond scaling based on measured honeydew properties places both stages at $We_d<1$ and $Bo_d<1$ at the outlet, but distinguishes their post-release states: nymphal droplets remain surface-tension dominated, whereas adult droplets enter deformation- and spin-influenced regimes. Development therefore maintains waste clearance across ontogeny under the same outlet-scale capillary constraint by changing how stylus motion is coupled to the droplet at release, linking life-stage biomechanics to honeydew placement in this invasive phloem feeder and suggesting bioinspired strategies for droplet ejection, antifouling, and self-cleaning surfaces.

Stratospheric aerosol injection (SAI) is a solar radiation modification technique, proposed as an interim measure to offset warming while greenhouse gas (GHG) emissions are reduced. This paper discusses a possible SAI implementation route - an alternative to sulfate aerosols formed in situ - based on engineered solid particles having dedicated properties such as size, composition, surface chemistry, and traceable origin, supporting safety, controllability, and functionality needed for SAI systems. These engineered properties also open up options for any future multi-state coordination of SAI through two technical building blocks: (1) the SAI-induced radiative forcing (SRF) - the magnitude of the cooling effect attributable specifically to the SAI layer - as an operator-independent quantity, derivable from direct aerosol-layer measurements; and (2) particle traceability through identifying signatures embedded at production. Both could feed into a shared, publicly accessible monitoring database open to independent interrogation, addressing several governance challenges by anchoring compliance assessments in measurable parameters. Drawing on precedents from the Montreal Protocol, IAEA safeguards, and other regimes, we show that shared technical metrics have historically enabled multi-state cooperation, and we argue the same could apply to SAI. We describe a phased pathway in which the technical capabilities and coordination practices that would use them are developed and tested together, at scales orders of magnitude below operational deployment. To be clear - we regard SAI deployment as premature; the conditions under which it might be considered have not been met. The paper does not propose a governance framework; rather, it identifies technical infrastructure that could support a wide range of such frameworks.

The use of mobile robotics in radioactive source seeking has become an important part of modern radiation-safety practices, supporting timely mitigation of contamination risks and helping protect public health. However, measuring radiation is often time-consuming, rendering traditional gradient-based source-seeking methods less effective due to lower sample efficiency. This paper proposes a sample-efficient Bayesian-Optimisation source-seeking strategy that utilises a heteroscedastic Gaussian process surrogate to balance exploration and exploitation. Excessive inter-sample travel is discouraged through a movement switching cost. The strategy is shown to generate sublinear regret in the source-seeking task, while simulations demonstrate its effectiveness in localising radioactive sources.

We study Lévy-like and truncated Lévy-like flights with step probability distribution of the form $r^{-1+ν}$ for negative, positive, and zero $ν$, focusing on the appearance of fractal geometry characteristics in the generated point sets. Forming ensembles of such point sets with fixed multiplicity, we develop simulation techniques leading to the desired value of correlation dimension in a vast continuous interval of scales. In particular, we demonstrate the possibility to produce ensembles of data sets with a low number of points with the needed properties. Furthermore, we show that the positive $ν$ distributions, apart from a region near the upper scale limit, show fractal behaviour that extends to infinitesimally low scales. As an example, we apply our findings to producing simulations relevant to the search for critical fluctuations, related to QCD critical endpoint, in heavy-ion collision experiments.

Single-photon detection possibility is a fundamental requirement for quantum technologies, including communication, computing and sensing. To achieve scalability and practical deployment, increasing attention is being directed toward integration of detectors with photonic integrated circuits, which offer compactness and compatibility with mass production. Superconducting nanowire single-photon detectors have emerged as the leading solution, combining near-unity efficiency, high temporal performance and the ability to be embedded across a wide range of photonic material platforms. In this review we trace the development of integrated superconducting nanowire single-photon detectors from early demonstrations to recent advances, outlining the progress in device architectures, material engineering and integration strategies. We also discuss performance benchmarks, emerging alternative designs, the future opportunities and challenges for this rapidly evolving field.

Statistical properties of light produced in spontaneous Raman scattering on an ensemble of molecules indicate the quantum nature of this phenomenon. The scattered light is non-classical and has high non-classical intensity correlations between Stokes and anti-Stokes components. The temporal coherence of this light is well investigated, while many questions related to spatial coherence remain open. Recent experiments reveal two peculiar features of the spatial coherence of the Stokes and anti-Stokes light. First, the intensity correlations between Stokes and anti-Stokes light remain non-classical even for macroscopic samples containing many molecules. Second, these correlations decrease when signal propagates through a multi-mode optical fiber: the more propagating fiber modes at Stokes and anti-Stokes frequencies the less the correlations. Moreover, the second-order autocorrelation function of Stokes and anti-Stokes light also decreases with the number of propagating modes in multi-mode fiber. In this paper, we build a model of spontaneous Raman scattering correlations of light produced by an ensemble of molecules and propagating through weakly guiding optical fiber that quantitatively explains all these observations. We show that spacial orthogonality of the fiber modes makes the light propagating through these modes uncorrelated in the standard detection scheme. This leads to suppression of non-classical intensity correlations of the total field in the multi-mode fiber. We find the degree of non-classical correlations on fiber parameters. The obtained results pave the way for engineering of non-classical Stokes -- anti-Stokes correlations.

One of the most common approaches for coupling optical single-photon sources and photonic integrated circuits is to use a cavity. The cavity acts as a spectral filter that distorts the light spectrum and changes its statistical properties. But in the general case one should take into account not only spectral filtering of light but also the spectral filter influence on the single-photon source dynamics. We build an effective analytical model for description of the cavity influence on the photon statistics of light emitted by the single-photon source as spectral filtering only. We show that this model correctly describes the photon statistics even in a strong-coupling regime between the single-photon source and the spectral filter. Our results can be useful for analytical modeling of photon statistics of quantum emitters strongly coupled to various electromagnetic interfaces.

Spectrally multiplexed telecom quantum networks require quantum memories that combine efficient storage with programmable frequency addressing. An ideal integrated implementation should therefore unite a native telecom transition, efficient storage and fast on-chip spectral control. Here we demonstrate a cavity-enhanced quantum memory in an isotopically purified $^{167}\mathrm{Er}^{3+}$-doped thin-film lithium niobate microring resonator. Long-lived hyperfine shelving states support persistent, high-contrast atomic frequency comb preparation, with a single-component comb lifetime of $277.6 \pm 52.6$s. Together with cavity impedance matching, this yields an on-chip storage efficiency of $23.3 \pm 0.5\%$ for 100-ns storage. The intrinsic electro-optic response of lithium niobate enables frequency-selective storage and routing of retrieved photons at rates up to 20~MHz with inter-channel crosstalk below $10^{-4}$. We further store and retrieve time-energy-entangled telecom photons, violating an entanglement-witness bound by more than 11 standard deviations and thus verifying the quantum nature of the storage process. Our results establish erbium-doped thin-film lithium niobate as a programmable light--matter interface for spectrally multiplexed quantum networks.

Exciton-polaritons provide a versatile platform for the study of a wide range of phenomena, including polariton lasers, topological polaritons, and bosonic condensation. Transition metal dichalcogenide monolayers host excitons with large oscillator strength and binding energies constituting a robust matter constituent that forms polaritons from cryogenic to room temperature when embedded in optical microcavities. Plasmonic nanoparticles arranged in lattice geometries offer strong field-confinement and high quality factors. However, the high sensitivity of monolayer excitons to strain and dielectric disorder necessitates encapsulation in atomically flat hBN to ensure a high optical quality, rendering plasmonics more challenging. Here, we employ our recently developed fabrication method for embedding gold nanodisk arrays into van der Waals heterostructures and compare two samples with opposite layer order. We observe that strain and etching-induced surface contamination can reduce the exciton quality and thus the light-matter interaction strength significantly. Our fabrication approach reduces interfacial irregularities and enables homogeneous large-area polariton lattices for a wide range of applications, such as polarization-control or topological polaritonics.

We introduce a systematic analysis of density functional approximation errors in solids by separating functional-driven from density-driven contributions using quantum Monte Carlo densities of silicon, sodium chloride, and copper as reference. Typically, functional errors dominate, but we identify important exceptions where density-driven errors exceed functional errors by factors of 2-3, notably for SOGGA11 and τ-HCTH in the semiconductor and the insulator. Material dependence is striking: 63% of functionals show error cancellation in silicon versus 18% in copper, and only five functionals surpass LDA accuracy for metallic copper even with exact densities. For silicon and sodium chloride, GILL or BECKE exchange combined with PBE, PW91, or P86 correlation achieves near-exact xc energies on QMC densities, while copper requires specialized functionals like PBEsol or PBELYP. High-quality densities consistently reduce density-driven errors across all systems. Historical analysis reveals that 1990s GGA functionals outperform many modern meta-GGAs, contradicting expectations of systematic improvement along Jacob's ladder. These results provide practical guidance for functional selection and highlight implications for machine learning potential development, where material-dependent error cancellation may compromise transferability.

The rapid growth of artificial intelligence, coupled with the slowing of Moore's law, is straining computing infrastructure, as CMOS electronics face inherent limits in bandwidth, energy efficiency, and parallelism. Integrated photonic computing encodes and processes information using the phase, amplitude, spatial modes, wavelength channels, and polarisation of guided optical fields, offering a scalable and energy-efficient route beyond charge-based signalling. Here, we review on-chip photonic computing, emphasising the progression from low-dimensional to high-dimensional architectures. At the foundational level, low-dimensional approaches manipulate the phase and amplitude of guided light through Mach-Zehnder interferometers, diffractive structures, microring resonators, and absorptive elements, forming a programmable basis for optical matrix-vector multiplication. Crucially, high-dimensional architectures exploit spatial modes and wavelength channels to carry multiple independent data streams through a single waveguide, achieving higher throughput with moderate hardware overhead. Practical deployment, however, demands more than device innovation. We examine how system-level techniques, from time-wavelength interleaving to hardware-aware training, address energy efficiency, precision, and algorithm-hardware co-design. Five challenges nevertheless remain: electro-optic conversion efficiency, computing parallelism, spatial integration, reconfigurability, and robustness. We highlight emerging topological structures, such as optical skyrmions, as a promising route to fault-tolerant, topologically protected encoding that exploits the largely untapped polarisation degree of freedom. We argue that, by embracing the higher dimensionality of light, photonic computing can offer not merely an incremental improvement but a new paradigm for high-performance, energy-efficient information processing.

Dielectric metasurfaces have introduced a new paradigm for substance detection by exploiting their resonant properties to enhance light-matter interaction. This enhancement can be used for sensing either through refractive index changes or through absorption-based mechanisms. Most works focus on high-quality factor resonators, aiming to increase field confinement in the vicinity of the resonant structure to improve sensitivity. In this work, we explore an alternative approach based on low-quality factor, fully dielectric metasurfaces, with engineered modes to enhance near-field concentration. We investigate different topologies that, despite their low-quality factors, achieve sensitivity and detection performance beyond what is typically reported for low-Q structures in the literature. This improvement is enabled by near-field engineering of the evanescent modes, allowing us to control the spatial distribution of the electromagnetic field and maximize its overlap with the analyte. Our results show that careful mode engineering provides a powerful strategy to boost sensing performance without relying on ultra-high-Q resonances.

Synchronization is a pervasive collective phenomenon underlying the firing of neurons, the beating of the heart, and the coherent emission of lasers. Across these systems, dissipation plays an organizing role, suppressing microscopic differences and steering coupled units toward a common macroscopic order. Here we harness engineered non-Hermitian dissipation to synchronize light directly in the optical domain. Implementing non Hermitian transition matrices on a silicon photonic processor, we drive arbitrary multimode optical fields toward a unique collective state with equal modal intensities and a globally locked phase, a process we call dissipation-induced phase synchronization. The synchronization rate and total optical power throughput are independently programmable, enabling control over the dissipative dynamics without compromising reconfigurability. These results recast dissipation as a functional resource and open a route to reconfigurable on-chip synchronization for classical and quantum photonic technologies.

Hydrogen (H2) is a promising carbon-neutral energy carrier. However, its deployment is limited by the lack of lightweight, reversible storage media that operate under practical conditions. Here, we establish nitrogen-doped graphdiyne (N-GDY) as a programmable two-dimensional platform for stabilizing dispersed light-metal dopants and enabling high-capacity physisorption of molecular H2. The computational package involves density functional theory (DFT) combined with ab initio molecular dynamics (AIMD) and Langmuir-based statistical thermodynamic modeling. The results revealed that N-sites of N-GDY bind up to five Li, Na, K, and Ca atoms per primitive cell with binding energies of -2.27, -1.57, -1.80, and -2.13 eV, respectively, exceeding their respective bulk cohesive energies. AIMD simulations at 400 K further confirm the structural robustness of the decorated frameworks and the absence of metal aggregation. The polarised metal centres activate reversible H2 adsorption through electrostatic and dispersion interactions, with average adsorption energies falling within the optimal window (-0.15 to -0.35 eV per H2). Sequential adsorption analysis reveals uptake of up to 25 H2 molecules per primitive cell, achieving intrinsic gravimetric capacities of 13.08, 10.82, 9.23, and 9.15 wt% for Li-, Na-, K-, and Ca-functionalized systems, respectively. Thermodynamic analysis indicates favorable adsorption-desorption behavior under near-ambient conditions, with Li- and Ca-functionalized systems exceeding the 6.5 wt% U.S. Department of Energy's ultimate system-level target when considering intrinsic material capacity. These results identify N-GDY as a chemically tunable scaffold for dispersing lightweight metals and provide a mechanistic design strategy for achieving high-capacity, reversible hydrogen storage in porous two-dimensional materials.

Fluctuations of nonequilibrium localized waves are shaped not only by direct stochastic forcing but also by deterministic transfer among coupled collective degrees of freedom. We develop a pathway-resolved stochastic collective-coordinate theory that makes this transfer explicit for stationary driven-dissipative solitons of the generalized Lugiato--Lefever equation with Raman response. The reduction yields a refined stationary phase-locking relation, providing a fixed point for the subsequent stochastic theory. Projecting field-level fluctuations onto four soliton coordinates: amplitude, frequency shift, temporal position, and global phase, yields a reduced Langevin model and, after linearization about a stable stationary state, an analytic power-spectral-density matrix. This framework separates direct stochastic injection from deterministic inter-coordinate conversion and thereby resolves how each observable spectrum is assembled from distinct internal fluctuation pathways. It shows that timing jitter is governed primarily by Gordon--Haus-type frequency-to-timing conversion, while phase noise is often dominated by amplitude-to-phase transfer rather than by direct phase diffusion. Raman response opens additional cascaded pathways, and the low-detuning hump in the intensity and phase spectra is traced to the driven response of an underdamped amplitude--phase subsystem preceding the breathing instability. Comparisons with stochastic simulations of both the reduced model and the full generalized Lugiato--Lefever equation show good agreement throughout most of the stable stationary single-soliton regime, with systematic deviations mainly near the Hopf boundary. The theory provides a general route for connecting internal fluctuation-transfer mechanisms of dissipative solitons to measurable noise observables.

Measurements of positional coordinates and dimensions - whether by human vision or optical instrumentation - are fundamental to safety, industrial productivity, manufacturing quality/accuracy, and scientific discovery. The ultimate precision of such measurements is governed by the Fisher information conveyed from an object to a detector through the optical field, and strategies for enhancing measurement performance often focus on reducing detector noise and/or refining estimation algorithms. Building on the emerging understanding of Fisher information as a physical quantity that propagates through space in a wave-like fashion, we demonstrate that substantial gains in precision can also be made by engineering the electromagnetic environment of a measurement target to optimise the generation and transmission of Fisher information. Using nanowire position metrology based on light scattering at a wavelength λ = 640 nm as an architype system, we achieve a multifold enhancement in localisation precision, reaching beyond λ/10,000. Our results establish target environment engineering as a powerful and broadly applicable strategy for advancing measurement and sensing performance across platforms ranging from optical characterisation of micro- and nano-objects to microwave radars and optical LiDAR navigation systems.

Nanoscale quantum light sources are essential building blocks for integrated quantum photonic systems. Here, we report a wavelength-scale entangled-photon source based on van der Waals-engineered NbOBr$_2$, and benchmark its performance for telecom-wavelength quantum light generation. By exploiting the material's second-order nonlinearity, we generate quantum-correlated photon pairs via spontaneous parametric down-conversion. We then use a 90$^{\circ}$ twisted stacking to induce quantum interference in photon-pair generation, yielding polarization-entangled photons. This approach enables tunability of the quantum optical state via control of the excitation laser polarization. We experimentally obtain entanglement fidelities exceeding 95% for Bell states, along with a high coincidence-to-accidental ratio of $\sim$335, and a brightness approximately one order of magnitude higher than recently reported telecom sources based on transition metal dichalcogenide (TMD) 2D materials. These results establish twisted van der Waals engineering as a powerful platform for highly tunable, high-brightness quantum light sources at telecom wavelengths.

We introduce a modular silicon-photonic Fabry-Perot resonator lattice based on cascaded tunable Sagnac loop reflectors. Each SLR is controlled by a single directional-coupler cross-coupling coefficient, enabling modular control of the effective lattice hoppings. As a representative example, alternating two SLR types maps the lattice onto the Su-Schrieffer-Heeger model in the weak-coupling limit. We derive the Bloch dispersion via a transfer-matrix formulation and obtain an effective tight-binding Hamiltonian in the weak-coupling limit. S-parameter simulations of a 20-site lattice show an isolated midgap resonance with edge-localized power profiles in the topological phase, and disorder tests show robustness against symmetry-preserving hopping perturbations. Our results establish SLR-based FP lattices as a complementary platform for on-chip topological photonics.

Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic simulations, machine learning, and workflow design, as well as iterative active learning procedures. Existing automated pipelines typically assume a fixed sequence of stages or depend on domain experts, which limits their adaptability to heterogeneous materials systems where the optimal curriculum is not known in advance. To lower the barrier to developing MLIPs for non-experts, we propose Lang2MLIP, a multi-agent framework that takes natural-language input and formulates end-to-end MLIP development as a sequential decision-making problem solved by large language models (LLMs). At each step, a decision-making agent observes the current dataset, model, evaluation results, and execution log, and then automatically selects an appropriate action to improve the model. This removes the need for a predefined pipeline and enables the agent to self-correct by revisiting earlier subsystems when new failures arise. We evaluate this approach on a solid electrolyte interphase (SEI) system with multiple components and interfaces. These results suggest that LLM-based multi-agent systems are a promising direction for automating MLIP development and making it more accessible to non-experts.

In living cells, proteins involved in specialized biochemical functions are often spatially organized within biomolecular condensates. Increasing evidence suggests that some of these condensates, including DNA repair condensates, emerge through liquid-liquid phase separation (LLPS). In the nucleus, however, condensates form within a highly heterogeneous environment composed of chromatin fibers, RNA, and additional protein scaffolds such as PAR chains, all of which may interact with phase-separating proteins. Moreover, condensate formation is frequently associated with specific chromatin conformations; for instance, loop extrusion has been proposed as a mechanism promoting DNA repair condensates. Here, we investigate how the surrounding fibrous environment controls the morphology and spatial organization of phase-separated condensates. Using Brownian dynamics simulations of minimal models combining Lennard-Jones particles with fixed fibrous substrates, we examine the respective roles of local fiber geometry and large-scale network organization, reflecting the multiscale architecture of chromatin. We show that protein-fiber interactions strongly influence droplet positioning relative to the substrate, in a manner analogous to wetting transitions in soft condensed matter systems. Both local geometric constraints and global network organization markedly affect droplet size, morphology, and multiplicity. In addition, large-scale asymmetries in fiber organization can induce robust spatial localization of the dense phase. Our results thus highlight how multiscale structural heterogeneity of the nuclear environment can regulate the emergence and organization of biomolecular condensates.

This study provides an analytical foundation for adversarial synchronization control in Kuramoto oscillator networks, where small gradient-based perturbations applied repeatedly to oscillator phases can dramatically enhance or suppress collective synchronization. Using the Ott--Antonsen reduction, we derive an exact closed-form expression for the effect of a single adversarial perturbation (kick) on the order parameter. A key finding is that each kick produces a finite, coupling-independent increment in the order parameter even when synchronization is arbitrarily weak, which combined with slow relaxation near the critical coupling and mean-field feedback explains the disproportionate amplification previously observed in numerical simulations. Fixed-point analysis further reveals a fundamental asymmetry between enhancement and suppression, with the latter governed by noise-induced escape in finite systems. Extending the framework to networks via the annealed network approximation, we show that the theory captures the synchronization behavior of representative model networks and identify a decoupling between kick sensitivity and mean-field dominance in scale-free networks. These results offer a tractable theoretical basis for understanding and designing kick-based synchronization control in oscillator networks.

Digital backpropagation (DBP) is one of the most effective techniques for compensating nonlinear distortions in coherent optical fiber communication systems. However, its practical application to wideband transmission remains limited by high computational complexity caused by large channel memory and the requirement for fine spatial discretization. In this work, we propose a subband-based learned digital backpropagation (SbL-DBP) framework for wideband optical transmission systems. The received signal is decomposed into multiple subbands, enabling independent frequency-domain compensation of the chromatic dispersion with reduced effective channel memory and lower computational complexity. Nonlinear intra- and inter-subband interactions are addressed in the time domain using a trainable multi-input multi-output filtering structure. The parameters of the proposed framework are jointly optimized using end-to-end gradient-based learning. In addition, sparsification techniques are employed to remove insignificant coefficients and further reduce computational complexity. Numerical simulations of an 11$\times$40~Gbaud WDM RRC-16QAM 20$\times$100 km transmission system demonstrate that the proposed method provides a superior performance--complexity trade-off compared to conventional DBP and enhanced DBP. In the low- and medium-complexity regimes, SbL-DBP provides higher signal-to-noise ratio gains while requiring fewer propagation steps.

High-pressure research is a productive route to new structures and emergent properties. However, crucial high-pressure structural information remains highly fragmented across individual publications and heterogeneous computational repositories. This fragmentation creates a major bottleneck for data-driven materials design. To bridge this gap, we introduce the High-Pressure Crystal Structure Database (HPCSD), a traceable, pressure-resolved repository that integrates experimental and theoretical high-pressure structures. HPCSD is constructed from two complementary data streams: elemental high-pressure phases and a searchable configuration space of stable and metastable phases generated via CALYPSO crystal structure prediction. To ensure rigorous comparability, all retained structures underwent re-optimization under a unified density functional theory (DFT) framework , with continuous enthalpy curves systematically generated specifically for the elemental phases across their stability fields. The initial release encompasses 77,346 consistently evaluated structural entries spanning 89 elements. An analysis reveals that pressure-induced polymorphism is ubiquitous and exhibits pronounced family-dependent trends. Structural diversity is strongly influenced by an element's electronic adaptability , with the greatest structural complexity emerging at intermediate rather than highest pressures. By providing standardized, reusable, and rigorously evaluated high-pressure structural data, HPCSD establishes a robust infrastructure to accelerate experimental phase identification, facilitate cross-study thermodynamic comparisons, and support the development of machine-learning interatomic potentials and generative models for high-pressure systems.

Solid-state Spatial Light Modulators (SLMs) are fundamentally limited in their ability to achieve high spatial complexity and high temporal bandwidth simultaneously. High-speed, low-energy modulation requires sub-wavelength active mode volumes, and sophisticated spatial wavefront engineering necessitates an ultra-fine pixel pitch. While small pixels can simultaneously solve both, in conventional architectures, the dense 2D electrical routing required for such pixels creates an insurmountable physical bottleneck. This results in a compromise between the SLM refresh rate, number of pixels and the field of view. Here, we demonstrate a hybrid architecture that overcomes this limit by spatially decoupling the electrical modulation plane from the optical output plane. By integrating a metasurface doublet with a photonic integrated circuit (PIC)-based optical phased array (OPA), we achieve independent 2D electrical control over each phase-element while simultaneously realizing a three-fold reduction in effective pixel pitch. This decoupling allows us to maintain the small active volume required for high-speed operation, while circumventing the routing constraints of dense spatial array of emitters. We utilize this platform to demonstrate tunable varifocal lensing, 2D beam steering, and 2D holography. Our work provides a scalable foundation for next-generation solid-state SLMs that simultaneously offer high speed, low power consumption, and large field of view.

This paper presents a novel method for measuring the Poynting vector characteristics of monochromatic electromagnetic waves. We outline a specific design for such a meter and provide experimental data to validate the approach. For testing purposes, we utilized vortex beams with both linear and circular polarization.

Optical Skyrmions have recently garnered much interest providing a potential avenue for high capacity, robust topological information transfer. Typically, Skyrmions are derived from the coupling of just two degrees of freedom (DoFs) limiting their versatility. In this work we realize spatio-spectral Skyrmions derived from the non-separability between three DoFs: wavelength, space and polarization. A compact and simple technique is used to generate the spatio-spectral vector beams (SSVB) carrying the desired Skyrmionic structure, offering simple pathways for complex Skyrmionic beam design. The topological structure, witnessed through a map between the spatio-spectral plane and the Poincaré sphere, exhibits an additional tunable $kπ$ parameter thereby enhancing the number of controllable DoFs. Our three DoF construction allows us to propose a novel topological multiplexing strategy that independently encodes different Skyrmion numbers at different radii of the field. We experimentally demonstrate the practicality of this approach by transmitting and receiving three distinct Skyrmion numbers encoded into a single topological field, for the first form of mode division multiplexing with Skyrmion topology. This work opens up new avenues for dense information encoding using multiple topological channels encoded in a single light field.

We propose a bilayer all-dielectric PhC for controlling Janus bound states in the continuum (BIC) and optical chirality through symmetry-selective perturbations. Starting from a symmetry-protected $Γ$-point BIC, we use interlayer displacement as one geometric control knob to generate different topological charges in the upward radiation and downward radiation channels. A subsequent diagonal in-plane displacement reconstructs the polarization topology around the BIC and generates a Janus-chiral BIC with strong handedness selectivity. In contrast, other in-plane perturbations generate chiral quasi-BICs with finite radiative coupling, for which the circular dichroism (CD) and resonance wavelength can be continuously tuned. We further show that material conductivity provides an additional dissipative degree of freedom for actively modulating the chiral response, with a switchable CD exceeding 0.89. Near-field optical-chirality distributions and multipole decompositions reveal that the chiral response originates from a symmetry-induced imbalance of local optical handedness and a spin-selective magnetic-dipole resonance. These results reveal the topological relationship between Janus radiation, polarization singularities and intrinsic chirality, thus paving a scalable route toward reconfigurable high-$Q$ chiral photonics.

First-principles density functional theory (DFT) is employed to evaluate the structural, electronic, optical, thermoelectric, and electrocatalytic properties of monolayer CrSi2N4. Its symmetric N-Si-N-Cr-N-Si-N septuple-layer structure exhibits dynamic, thermal (300 K), and mechanical stability, supported by a -8.76 eV/atom cohesive energy. PBE and HSE06 functionals reveal an indirect bandgap of 0.58 eV and 2.16 eV, respectively, driven by localized Cr-3d and N-2p states. The monolayer features 15.57 static dielectric constant and maximum absorption coefficients of 0.9 X 10^6 cm-1 (visible) and 1.4 X 10^6 cm-1 (deep-UV). Semiclassical Boltzmann calculations predict an outstanding room-temperature n-type thermoelectric power factor of 3.5 x mW/mK2. For hydrogen evolution (HER), the basal plane yields a baseline hydrogen adsorption free energy (ΔGH) of 1.05 eV at the N-site. Applying +5% expansive biaxial strain improves HER kinetics, reducing ΔGH to 0.46 eV. Thus, CrSi2N4 is a resilient, tuneable candidate for waste-heat recovery, photodetectors, and sustainable electrocatalysis.

We present an implicit, fully-coupled hydro-mechanical solver for the three dimensional simulation of fluid-driven rupture propagation along existing discontinuities. The solver handles simultaneously frictional slip (shear failure) and tensile opening (hydraulic fracture) along arbitrary intersecting fractures and faults in a linearly elastic and impermeable rock matrix. The spatial discretization combines a collocation displacement discontinuity boundary element method for quasi-static elasticity with a Galerkin finite element method for nonlinear pore-fluid diffusion along the discontinuities. Frictional and tensile failure are governed by a poro-elastoplastic cohesive zone like interface law with slip-weakening friction, dilatancy, and tensile strength degradation, integrated via an elastic predictor-plastic corrector scheme. The strong nonlinear coupling between mechanical deformation and fracture permeability is handled via adaptive implicit time-stepping. Efficient block preconditioning of the coupled tangent system, leveraging hierarchical matrix representations of the boundary element operator, is essential to achieve robustness across the full range of fracture behaviors. Accuracy and convergence are demonstrated against a comprehensive suite of analytical and semi-analytical solutions of increasing complexity: fluid-driven frictional ruptures under constant and slip-weakening friction, dilatant ruptures with permeability changes, and penny shaped hydraulic fractures spanning the viscosity-to-toughness transition. The solver is further assessed on two multi-fracture configurations: injection into three intersecting fractures, and a height-confined hydraulic fracture intersecting a strike-slip fault. The proposed framework simultaneously captures frictional slip, dilatancy, permeability evolution, and tensile opening.

Full-waveform inversion (FWI) estimates unknown parameters in the wave equation from limited boundary measurements. Recent advances in neural reparameterized FWI (NeurFWI) demonstrate that representing the parameters using a neural network can reduce the reliance on the high-quality initial model and wavefield data, at the cost of slow high-resolution convergence. However, its underlying theoretical mechanism remains unclear. In this study, we establish the neural sensitivity kernel (NSK) and the wave tangent kernel (WTK) to analyze their convergence behavior from both model and data domains. These theoretical frameworks show that the neural tangent kernel (NTK) induced by neural representation adaptively modulates the original sensitivity and wave tangent kernels. This modulation leads to several key outcomes, i.e., the spectral filtering effect, the gradient wavenumber modulation, and the wave frequency bias, connecting the convergence behavior of NeurFWI with the eigen-structures of NSK and WTK. Building on these insights, we propose several enhanced NeurFWI methods with tailored eigen-structures in NSK and WTK to improve inversion performances and efficiency. We numerically validate these theoretical claims and the proposed methods in seismic exploration, and firstly extend their application to medical imaging.

Recent theoretical and experimental advances in quantum ferroelectrics suggest that ferroelectricity can also emerge in non-polar space group, highlighting the limitations of conventional polar space group criteria in identifying ferroelectric materials. Here, we introduce a unified definition based on switchable polarization differences between energetically equivalent states, which naturally encompasses conventional and quantum ferroelectrics. Guided by this principle, we implement a high-throughput screening strategy that systematically identifies both conventional and quantum ferroelectrics among experimentally synthesized materials. In particular, we identify a new type of quantum ferroelectric in which the quantized polarization arises from arbitrary ionic displacements, in contrast to previous quantum ferroelectrics (including both fractional and integer quantum ferroelectrics) where quantized polarization results from fractional or integer ionic displacements. Notably, we find that materials such as Ba3I6 and Cs2PdC2 exhibit low switching barriers and robust insulating behavior, highlighting their experimental viability. Our results reconcile conventional and quantum ferroelectrics, expand the accessible materials landscape, and provide a practical roadmap for discovering next-generation ferroelectrics with advanced switchable functionalities.

Superconducting nanowire single-photon detectors (SNSPDs) have demonstrated timing jitter in the few-picosecond regime, yet their timing resolution deteriorates substantially under high-count-rate operation. Existing interpretations mainly attribute this degradation to deterministic waveform distortions, such as multiphoton responses and pulse pile-up, yet the experimentally observed jitter broadening at high count rates cannot be fully accounted for within this picture. Here, we show that stochastic baseline fluctuations arising from finite-memory readout dynamics constitute an intrinsic source of the count-rate-dependent timing jitter in SNSPD systems. For stochastically arriving photons, overlapping recovery responses accumulate in the readout chain and generate statistically fluctuating baselines, which are converted into timing uncertainty through threshold-based timing extraction. We develop a stochastic-process framework that quantitatively connects photon statistics, readout dynamics, and timing jitter. The framework predicts characteristic scaling behaviors, including a nonmonotonic dependence of baseline fluctuations under pulsed excitation with a maximum near half of the repetition frequency. These predictions are quantitatively verified through systematic variations of count rate, circuit time constant, and detector dynamical properties. Our results identify stochastic baseline dynamics as a fundamental mechanism limiting timing resolution in high-count-rate SNSPD operation and provide a general framework for optimizing finite-memory high-speed photon-counting systems.

Frequency modes of light are one of the most promising platforms that provide access to high-dimensional quantum states amongst different photonic degrees of freedom capable of high-dimensionality, enabling robust, error-tolerant, and scalable quantum optical information systems. We demonstrate engineering of precisely controlled two-photon high-dimensional states entangled in frequency through time-domain Fourier optical synthesis. We generate and convert a continuous broadband frequency-entangled state into a large range of discrete frequency bins suitable for ITU standards, with spacings ranging from 12.5 GHz to 750 GHz, and observe spectral anticorrelations over 38 frequency bins, including intra-bin pure states at a 100 GHz bin spacing. We characterize the full quantum state dimensionality via Schmidt decomposition and observe lower bounds on the frequency-binned Hilbert-space dimensionalities of at least 289, formed by two entangled qudits with dimension 17. Furthermore, we demonstrate quantum nonlocality via frequency correlations in a transmission experiment over a campus-scale two-node fiber network. This work represents a crucial step towards building a versatile and relatively simple way of generating precisely controlled high-dimensional spectral qudits, with the potential of harnessing in wavelength-multiplexed quantum networks, high-dimensional information processing, and communication of quantum states specifically, and fiber-optic quantum remote sensing.

Photonic time crystals are electromagnetic media with periodically time-varying parameters, enabling momentum band gaps, parametric amplification, and frequency conversion beyond what is possible in time-invariant systems. So far, they have been explored mainly in single-mode systems, which limits the range of accessible physical phenomena. Here, we introduce an impenetrable metasurface waveguide as a multimode time-varying platform supporting both guided surface modes and higher-order guided volume modes. We show that temporal modulation in this platform gives rise not only to conventional intramodal band gaps associated with same-branch coupling, but also to tilted intermodal band gaps originating from coupling between different guided-mode branches. Unlike intramodal band gaps, these intermodal band gaps are not restricted to half the modulation frequency and can enable directional wave amplification, where the amplified field carries energy along the waveguide even inside the band gap. We further show that the modulation phase difference provides an effective symmetry-control parameter: by exploiting temporal glide symmetry, one can selectively suppress or enhance gap opening for interactions between modes of the same or different symmetry. These results establish a versatile multimode platform for photonic time crystals, offering one of the simplest and most experimentally accessible routes to tilted band gaps compared with volumetric dispersive PTC implementations and, more broadly, opening new opportunities for time-varying electromagnetic systems.

The key problem facing ChatGPT-like AI's use across society is that its behavior can shift, unnoticed, from desirable to undesirable -- encouraging self-harm, extremist acts, financial losses, or costly medical and military mistakes -- and no one can yet predict when. Shifts persist in even the newest AI models despite remarkable progress in AI modeling, post-training alignment and safeguards. Here we show that a vector generalization of fusion-fission group dynamics observed in living and active-matter systems drives -- and can forecast -- future shifts in the AI's behavior. The shift condition, which is also derivable mathematically, results from group-level competition between the conversation-so-far (C) and the desirable (B) and undesirable (D) basin dynamics which can be estimated in advance for a given application. It is neither model-specific nor driven by stochastic sampling. We validate it across six independent tests, including: 90 percent correct across seven AI models spanning two orders of magnitude in parameter count (124M-12B); production-scale persistence across ten frontier chatbots; and a priori time-stamped prediction eleven months before the Stanford 'Delusional Spirals' corpus appeared, and independently confirmed by that corpus of 207,443 human-AI exchanges. Because it sits architecturally below the current safety stack, the same formula provides a real-time warning signal that current alignment does not supply, portable across current and future ChatGPT-like AI architectures and instantiable in application domains where competing response classes can be defined.

The robustness of XRD methods for the determination of the lattice parameters of crystals is well established. These methods have been extended to helical atomic structures using twisted x-rays \cite{friesecke_twisted_2016}. Building on an integral form used in \cite{friesecke_twisted_2016}, we construct integral representations of a broad class of time-harmonic solutions to Maxwell's equations in a vacuum or, more generally, in a homogeneous medium without source terms. The representation includes assignable generalized functions (distributions) that can be tailored to specific boundary or far-field conditions. When the assignable functions satisfy mild periodicity and smoothness conditions, the solutions can be approximated using multi-dimensional trapezoidal rules with exponentially fast convergence. This approximation can be physically interpreted as utilizing finite sources of plane waves to approximate the broad class of time-harmonic solutions to Maxwell's equations. Using these solutions, we show that radiation from suitably placed and oriented sources can serve as incoming radiation for structures with icosahedral symmetry to achieve constructive interference after interacting with the icosahedral structure. The finite source approximations are sufficiently general to satisfy the general Dirichlet conditions at an arbitrarily large number of assigned locations in a source-free domain. The integral representation also extends to a broad class of physical phenomena governed by Helmholtz-type equations. Examples include the scalar wave equation for acoustic waves and elastic wave propagation in linear isotropic solids, which involve both scalar and vector wave equations.

We investigate the suppression of matter-wave Talbot interference under environmentally induced decoherence. The system is modeled as an atomic beam diffracted by a periodic grating, whose transverse dynamics is described within the paraxial approximation. Environmental coupling is introduced through an effective open-system model that exponentially damps spatial coherences between diffracted components, allowing a continuous interpolation between the coherent Talbot regime and the incoherent far-field diffraction limit. Besides the usual intensity and transverse-momentum distributions, we analyze the local probability flow associated with the diffracted matter wave. The corresponding Bohmian, or hydrodynamic, representation is used here as a diagnostic tool fully equivalent to the standard quantum description, with no additional assumptions beyond the probability current of the paraxial wave field. In the present Talbot geometry, this analysis shows how decoherence progressively suppresses the carpet structure and smooths the transverse-momentum distribution, while the flow may remain organized into channels determined by the grating periodicity. The results illustrate, in a periodic matter-wave Talbot geometry, that the loss of visible interference and the loss of dynamical pathway separation need not occur simultaneously. In particular, flux-channel structures can persist in parameter regimes where multi-slit interference features have already been strongly reduced. This distinction provides a local characterization of decoherence in matter-wave Talbot interferometry and complements previous trajectory-based analyses of coherence loss in simpler interference and confined geometries.

Understanding the mutual influence between social behavior and physical health is crucial for designing effective epidemic mitigation strategies. Individual interactions drive the evolution of opinions, which in turn shape how infectious diseases are perceived and consequently how they spread within a population, for instance through the adoption or rejection of preventive measures. At the same time, the distribution and dynamics of physical contacts play a fundamental role in determining transmission patterns. To this end, we develop a mathematical framework to analyze the coupled dynamics of opinion formation, disease transmission, and physical contacts by employing graphon-based networks, which capture heterogeneous and large-scale connectivity patterns typical of realistic social structures. The epidemic compartmental model further incorporates a kinetic description of microscopic level physical contacts, allowing for a consistent multiscale representation of interaction patterns. Starting from a microscopic description governed by interpersonal compromise and intrinsic self-thinking processes, we derive a kinetic compartmental epidemic model on graphons via a mean-field limit. This formulation allows us to investigate the joint evolution of the disease state and the opinion distribution, with a particular focus on the role of social networks and physical contacts. Numerical experiments demonstrate that the graphon-kinetic approach provides a comprehensive representation of the coupled opinion-epidemic dynamics, revealing new possibilities for controlling disease spread by shaping population opinion patterns.

Graph construction is an essential step in the Graph Neural Network (GNN) based tracking pipelines. The goal of the graph construction is to construct a graph that contains only the defined true edge connections between nodes (detector hits). A promising approach for the graph construction is through the Metric Learning approach, where a node representation in an embedding space is learned, and nodes are connected according to their distance in the embedding space. The loss function for the metric learning in this case is a contrastive loss encouraging the true pairs of nodes to be close to each other, and pulling away the false pairs of nodes. This approach presents a conflict of the learning objective for the hopping connections when a true edge is defined as a chain connection in a particle track. To address the conflict for this case, we propose a ``Double Metric Learning'' approach, where two node representations are learned. A directed graph can then be constructed based on the distance between the two representations from two nodes respectively. We test this idea with the ATLAS ITk detector at the HL-LHC using the ATLAS ITk simulation and show better graph construction performance particularly for particles with high transverse momentum compared to the Simple Metric Learning approach. We also show that Double Metric Learning is able to accurately predict edge direction.

GaAs-based nanowires hosting active quantum heterostructures provide a promising route toward monolithic integration of single-photon sources on silicon, a key requirement for scalable quantum photonics. However, ultrathin axial quantum-emitter formation is often hindered by facet-dependent growth dynamics and rotational twins, which induce lateral overgrowth and compromise interface abruptness. Here, we develop InGaAs-based quantum emitters by tailoring facet evolution via dilute Sb incorporation, which efficiently suppresses twins and promotes confined axial insertion at the growth-front facet. This approach significantly enhances the probability of obtaining abrupt, few-nanometer-thin quantum dots at the nanowire tip. Single-nanowire optical spectroscopy reveals intense, spatially localized emission from the active region with lifetimes as short as (0.51 $\pm$ 0.02) ns, and second-order photon-correlation measurements consistently exhibit pronounced antibunching with $g^{(2)}(0)<0.4$, confirming single-photon emission. These results establish a strong correlation between twin density and axial heterostructure formation, identifying defect control as a key factor in realizing monolithically integrated nanowire single-photon sources.

Rare-earth gain media form the foundation of modern optical communications, emerging quantum hardware, and ultrafast optics. While chip-scale integration can enable fiber-like, and potentially beyond-fiber, functionality with unprecedented scalability, development in the visible and near-infrared remains in its early stages. Here, we demonstrate ytterbium-based optical gain integrated into an aluminum oxide photonic platform, achieving both single-mode lasing and optical amplification in the near-infrared regime. This platform delivers optical amplification with output powers exceeding 0.5 W, an optical-to-optical conversion efficiency above 70%, and a noise figure of 3.3 dB, approaching the quantum limit for phase-insensitive amplification. Furthermore, we achieve femtosecond pulse amplification to a record peak power of 14 kW, enabling supercontinuum generation with visible dispersive waves extending from 780 to 476 nm in conjunction with nonlinear photonic devices. This platform is compatible with heterogeneous integration into standard photonic circuits, laying the foundation for scalable visible-near-infrared photonic systems, including coherent laser arrays, mode-locked lasers, optical clocks, and microwave oscillators.

Soft, slender structures are ubiquitous in natural and engineered systems, with broad application potential from biomimetic materials to soft robotics. However, there is a notable lack of computational tools that simultaneously preserve high-fidelity continuum rod mechanics, scale to large interacting ensembles, and remain flexible across diverse biophysical settings. Here we introduce Elastica++, an open-source, high-performance implementation of the Cosserat-rod model for large-scale simulations of slender-body dynamics. Elastica++ combines performance-oriented kernels with shared-memory parallelism to sustain teraflop-scale throughput despite complex discretization domains and physical interactions. The framework further interoperates with external numerical solvers, supporting efficient multiphysics workflows. We demonstrate robustness and breadth through case studies spanning passive nest-like metamaterials, collective active-matter dynamics, cilia carpets, soft magnetic microrobots, and schooling swimmers. Elastica++ thus provides a missing foundation for high-throughput studies of emergent behavior in interacting assemblies of elastic slender structures.

Costly cooperation and costly signaling are both difficult to reconcile with simple fitness maximization, yet both are common in biological and social systems. We study a model in which agents emit costly signals and condition their actions on the signals they observe. Across the Prisoner's Dilemma (PD), Snowdrift (SD), and Stag Hunt (SH) games, we ask when this coevolutionary process can sustain cooperation and how it changes across well-mixed populations, spatial lattices, and fluctuating strategic environments. The simulations show that signals are selected less by their raw production costs than by the cooperative responses they currently elicit. In well-mixed populations, the mechanism sustains partial cooperation in PD and SD and drives near-complete cooperation in SH. On lattices, cooperation is strengthened further by local assortment. A reduced mean-field analysis explains why average population feedback is already sufficient in SD and SH, but not in the PD. To account for the PD dynamics, the reduced theory must include transient correlations associated with rare signals, inheritance, or spatial clustering. Our results therefore delineate a class of settings in which costly signals persist because they transiently organize cooperative responses and thereby reshape the effective strategic environment.

Multimode intracavity frequency-doubled lasers can reach states of amplitude noise suppression orders of magnitude beyond the predictions of independent-mode partition statistics. We show that the chi2 coupled-wave dynamics in the doubling crystal admit a Lyapunov functional whose monotone decrease under each crystal pass establishes a constant-intensity manifold as the per-pass descent target of the mode dynamics. We confirm the mechanism in an intracavity frequency-doubled Nd:YVO4-LBO laser, observing a 100 fold contrast between full and Fabry-Perot-filtered output noise at fixed detector bandwidth, well beyond the statistical-averaging baseline. The mechanism rests on the algebraic structure of the coupling, a coherent superposition of oscillators sharing a quadratic dissipative channel, and is therefore a candidate for analogous noise-suppression effects in other coupled oscillator systems with the same algebraic form.

Optical spin-orbit interactions (SOI) link photonic spin to momentum, offering a route toward on-chip polarization control and beam steering. Nevertheless, achieving sufficient optical SOI and nonlinearities on sub-micrometer scales - a prerequisite for dense photonic integration - remains an outstanding challenge. Here, we show that highly birefringent van der Waals (vdW) waveguides provide an ideal, chip-compatible platform to address this limitation. We focus on the ferroelectric semiconductor NbOI2, which exhibits record optical nonlinearities and dielectric anisotropy. Using femtosecond optical microscopy, we image light propagation and harmonic conversion beyond the total internal reflection barrier over tens of micrometers in NbOI2 slab waveguides. We report giant optical spin-splitting through the optical spin Hall effect, which facilitates spatial separation of optical spin currents on sub-micrometer scales, in quantitative agreement with a microscopic light-matter interaction model. We further leverage optical spin-momentum locking to realize polarization-controlled waveguide steering. We generalize these observations across various vdW waveguides and empirically confirm a scaling law linking dielectric anisotropy to geometric spin-splitting. Our results establish highly anisotropic vdW waveguides as an ideal platform for densely integrated opto-spintronic technologies.

Tweezer arrays of polarizable objects are a promising platform for assembling quantum matter and building next-generation quantum sensors. Light-induced dipolar interactions have emerged as a method to couple their motion, thereby establishing a new paradigm for controlling collective mechanical degrees of freedom. Here, we extend these into the regime of Floquet-driven interactions, combined with the intrinsic nonreciprocity of optical forces. We demonstrate beamsplitter, single-, and two-mode squeezing operations, as well as signatures of a negative-mass-like oscillator arising from the nonreciprocity. Moreover, we show that a programmable combination of these operations enables continuous tuning of complex eigenfrequencies. These results establish a toolbox of quantum operations of nonreciprocal interactions that are essential for investigating non-Hermitian many-body physics and collective quantum optomechanics.

The striking variety of macroscopic morphologies displayed by bacterial colonies depends on microscopic environmental and behavioural details in a manner that is currently not well understood. A surprising example is sibling inhibition, whereby isogenic bacterial colonies spreading in soft agar hydrogels tend to avoid each other and form sharp demarcation lines when growing nearby. Here we investigate this effect with the common pathogen \textit{Pseudomonas aeruginosa}, by combining quantitative density measurements with a minimal biophysical model. Our results show that the phenomenon does not depend on gel compression, lethal inhibition or quorum sensing-dependent cell communication. Instead, colony separation is driven by localised nutrient depletion through a dynamic feedback between growth and motility. The model, which is calibrated using experimental data, captures key observations including the dependence of inhibition strength on the initial nutrient concentration. This work establishes nutrient availability and non-lethal motility inhibition as central factors underlying sibling inhibition, providing a generalisable framework for microbial spatial dynamics with implications for understanding bacterial interactions in tissues, soils and engineered microbiomes.

Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is severely limited by unique sensor degradations beyond the capabilities of existing restoration methods, which are ignorant of underlying thermal physics. Here, we propose HAIR (HADAR-based Image Restoration) as a physics-driven framework for ground-based TIR-HSI restoration. HAIR utilizes the HADAR rendering equation (HRE) and combines it with the atmospheric downwelling radiative transfer equation (RTE) to model TIR-HSI using temperature, emissivity, and texture (TeX) physical triplets. This physical model leads to a TeX decompose-synthesize strategy that guarantees physical consistency and spatio-spectral noise resilience, in stark contrast to existing approaches. Moreover, our framework uses a forward-modeled atmospheric downwelling reference, along with spectral smoothness of emissivity and blackbody radiation, to enable spectral calibration and generation that would otherwise be elusive. Our extensive experiments on the outdoor DARPA Invisible Headlights dataset and in-lab FTIR measurements show that HAIR consistently outperforms state-of-the-art methods across denoising, inpainting, spectral calibration, and spectral super-resolution, establishing a benchmark in objective accuracy and visual quality.

High-pressure X-ray diffraction experiments were performed on Ti-Al-V alloys to investigate the effect of composition on structural stability, focusing on Ti-3Al-2.5V and comparing with pure Titanium and Ti-6Al-4V. Measurements using different pressure-transmitting media show a phase transition in Ti-3Al-2.5V at 17-19 GPa, intermediate between pure Ti (5-10 GPa) and Ti-6Al-4V (~30 GPa). Despite variations arising from the choice of pressure medium, the transition pressure shows a clear and systematic increase with higher Al and V content. Equation-of-state analysis indicates that the bulk modulus remains nearly unchanged across compositions. This suggests a decoupling between elastic properties and phase stability, with alloying primarily affecting the transition pressure rather than compressibility. These results highlight the role of composition in tuning high-pressure phase transformations in Ti-Al-V based alloys.

A macroscopic mesoscopic, deterministic stochastic coupling strategy is proposed to accelerate the direct simulation Monte Carlo (DSMC) method for chemical reaction. First, a macroscopic synthetic equation is formulated by integrating continuum constitutive relations for diffusion, stress, and heat flux, along with higher order constitutive relations that capture nonequilibrium transport effects. Second, higher order constitutive relations and chemical reaction source terms are sampled from DSMC and embedded into the macroscopic synthetic equation. Third, the macroscopic system is solved to the steady state, whose solution is then employed to correct particle distributions in DSMC intermittently. This coupling features asymptotic preserving, fast converging and noise reduction properties, supporting efficient, accurate simulations with coarse spatiotemporal grids and reduced evolution/sampling steps. Accordingly, it mitigates major computational bottlenecks of DSMC for near continuum flows by several orders of magnitude.

This study investigates the role of thermal boundary conditions on natural convection and entropy generation in non-Newtonian power-law fluids confined within a square cavity and a concentric cylindrical annulus. Steady, two-dimensional governing equations based on the incompressible power-law model and the Boussinesq approximation are solved using the Gridap.jl finite element framework. The numerical methodology is validated against benchmark solutions for both Newtonian and non-Newtonian convection, showing good agreement in terms of isotherm fields, streamlines, local Nusselt number distributions, and entropy generation. The effects of fluid rheology and heating mode are examined for shear-thinning, Newtonian, and shear-thickening fluids under uniform and non-uniform thermal boundary conditions. The results show that shear-thinning behavior enhances buoyancy-driven circulation, steepens thermal gradients, and increases heat transfer, whereas shear-thickening behavior suppresses convection and promotes conduction-dominated transport. Thermal boundary conditions are found to play an important role in controlling the intensity and spatial distribution of flow, heat transfer, and irreversibility. In both geometries, uniform heating produces stronger and more distributed convective structures, while non-uniform sinusoidal heating localizes thermal forcing and consistently reduces total entropy generation. An entropy analysis further reveals that viscous dissipation dominates irreversibility in shear-thinning fluids, whereas heat-transfer irreversibility becomes dominant as the power-law index increases. The study demonstrates that appropriate thermal boundary design, together with fluid rheology, provides an effective route for controlling heat transfer and minimizing thermodynamic losses in non-Newtonian convection systems. The source code and metadata are publicly available.

Traditionally, neutron-$γ$ discrimination in organic scintillators relies on techniques such as time-of-flight (ToF) selection and pulse-shape discrimination (PSD). However, particle identification through graphical cuts remains challenging in the low-charge regime due to poor signal-to-noise ratios (SNR). In this work, we propose SINAPSE, a lightweight deep learning framework for accurate and explainable neutron-$γ$ discrimination in the low-charge regime. The framework employs a dual-branch architecture that combines a 1-dimensional convolutional autoencoder for waveform denoising with a classifier for particle identification. Random augmentations are applied to high-SNR waveforms to simulate low-charge conditions, enabling robust extrapolation into regimes where conventional PSD labels are unreliable. We show that SINAPSE achieves superior denoising performance compared to conventional digital signal processing techniques, and outputs well-calibrated probabilities, consistent with traditional graphical cuts. Finally, we apply SHAP (SHapley Additive exPlanations) values to show that model decisions are driven by physically meaningful pulse-shape features, confirming consistency with established PSD principles.

Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to degradation in scattering tissue. We introduce DeepFilters, a scattering-aware deep optics framework that jointly optimizes a parameterized pupil filter and a digital-filter-based reconstruction network through a calibrated differentiable forward model to achieve broad generalization without retraining. Incorporating empirical scattering kernels, physics-guided regularization, and a hybrid genetic-gradient initialization strategy, DeepFilters extends the PSF from 16 micron to >400 micron in clear media and enables signal recovery beyond 120 micron deep in biological tissues, validated across fixed brain slices and sea urchin embryos.

We present a fast time-domain simulator for optical cavities capable of reproducing non-linear dynamical regimes arising from ring-down effect during resonance crossings at high mirror velocities. The model is based on a recursive formulation of the intracavity electric field as a sum over round trips, preserving the cavity memory while maintaining high computational efficiency. The simulator is designed to achieve three main goals. First, the boundary conditions of the cavity can be modified at each simulation step, allowing arbitrary time-dependent variations of both mirror positions and input electric field. Second, the sampling frequency can be flexibly chosen by the user, however, it is internally adjusted before effectively executing the simulation to remain consistent with the cavity round-trip structure. Finally, high computational efficiency was obtained by avoiding the repeated evaluation of the full electric field history. The framework is validated through comparison with experimental data from the Virgo interferometer during a mechanical excitation experiment, showing good agreement in non-adiabatic regimes. Due to its efficiency and flexibility, the simulator provides a versatile tool for time-domain studies of optical resonators and future applications in real-time control and reinforcement-learning-based lock acquisition.

We report the observation of a long-lived non-stationary state of light in a single-mode optical cavity. The observed state is a ghost of a saddle-node bifurcation which creates a bottleneck in phase space. While such ghosts are known to exist, accessing them is challenging because it requires a mechanism that steers the relaxation pathway away from the true attractor and into the bottleneck where the ghost emerges. Here we identify such a mechanism, namely a nonlinear response with memory. Our experimental system leverages this mechanism, enabling us to observe ghost states with lifetimes exceeding the cavity photon lifetime by more than ten orders of magnitude, even in the presence of strong fluctuations. The ghost manifests as a plateau in the relaxation dynamics of the cavity transmission, reminiscent of prethermalization. We show how the ghost lifetime depends on the memory time and the distance to the bifurcation, and we observe signatures of scaling in the distribution of ghost lifetimes at fixed driving conditions. Our work establishes minimal conditions for realizing parametrically long-lived non-stationary states.

Dopant distribution in two-dimensional semiconductors is typically assumed to be stochastic, limiting deterministic defect engineering. Here, we show that non-equilibrium growth kinetics can be harnessed to define dopant-driven strain architectures in vanadium-doped WS$_2$ monolayers. Using synchrotron X-ray fluorescence, we identify preferential vanadium incorporation, anti-correlated with tungsten content, along crystallographic bisectors. An adsorption-growth-diffusion model with a single kinetic parameter quantitatively captures the dopant segregation arising from preferential corner adsorption and limited diffusion during chemical vapor deposition growth. Hyperspectral Raman imaging demonstrates mechanically induced vibrational responses, revealing localized tensile strain ($\varepsilon \approx0.70\%$) channels associated with the anisotropic dopant distribution. This regime is marked by the depletion of W-site-sensitive in-plane modes and the emergence of a localized $J2$ mode (210~cm$^{-1}$), which our ab-initio calculations attribute to antiphase V$-$V oscillations. These findings establish kinetic segregation as a route to deterministic chemical and strain architectures in 2D semiconductors, enabling programmable defect landscapes and strain engineering during synthesis.

Integrated photonics has emerged as a promising platform for quantum communication and quantum computation. Thin-film lithium niobate (TFLN) has gained significant attention in this field due to its exceptional optical properties, enabling the realization of numerous integrated photonic devices. However, quantum memory, which serves as a universal building block for the quantum internet, has not yet been demonstrated in TFLN. In this study, we realized the first on-chip quantum memory using erbium ions doped TFLN. The developed quantum memory achieves a storage time of 400 ns with an efficiency of 1.95%, significantly outperforming conventional waveguide delay lines. The multimode capability is demonstrated by successfully storing four temporal modes. Furthermore, single-photon-level coherent pulses are encoded into time-bin qubits and stored with a fidelity of 96.8% , surpassing the classical limit achievable by measure-and-prepare strategy. Our results demonstrate the first on-chip quantum memory for telecom-band time-bin qubits in TFLN, providing a key building block toward integrated quantum registers and repeaters for scalable quantum information processing.

High-order edge-enhanced imaging enables precise feature localization and effective background suppression, offering a powerful tool for real-time recognition and high-contrast visualization. Extending this capability to the mid-infrared (MIR) regime is particularly valuable for applications such as biomedical diagnostics, material inspection, and remote sensing, yet remains limited by inadequate spatial-frequency modulation fidelity and low detection sensitivity. Here, we demonstrate a high-sensitivity MIR upconversion differentiator operating at 3 $μ$m, which achieves isotropic high-order edge enhancement by optically imprinting topological complex-amplitude patterns onto MIR Fourier components via nonlinear parametric interaction. Vortex transfer functions $t(k_r, φ) \propto k_r^\ell e^{i\ellφ}$ are precisely encoded on a phase-only spatial light modulator to enable tunable MIR differentiation from first- to fourth- order, with real-time switching at up to 60 Hz. Benefiting from a low-noise upconversion process and a single-photon-sensitive silicon camera, the system achieves high-contrast edge imaging under low-light conditions. Experimental results confirm accurate edge extraction and background suppression for both amplitude and phase objects, hence underscoring its potential for noninvasive diagnostics and label-free material analysis.

Vector beams, whose polarization varies across the transverse profile, are a central resource in structured-light optics and quantum photonics. Their characterization, however, becomes challenging when the field lies in a spectral region for which efficient spatially resolving detectors are unavailable. Here we demonstrate the spatially resolved reconstruction of an undetected vector beam by exploiting induced coherence in a nonlinear interferometer. In this effect, indistinguishability between two down-conversion pathways allows information encoded in an undetected field to be read out through interference of its detected partner. A telecom-wavelength idler field acquires a spatially varying polarization transformation but is never directly detected. Instead, its local polarization information is inferred from single-photon interference in the visible signal field, enabled by momentum correlations of the photon pair. Using phase-shifting and off-axis quantum holography with two polarization projections, we reconstruct the horizontal and vertical amplitudes and their relative phase across the beam profile, thereby recovering the full vectorial structure of the undetected field. We experimentally retrieve the polarization texture of an $m=2$ vector beam and compare multi-shot and single-shot reconstruction strategies. Our results extend imaging with undetected light from scalar objects to vectorial optical fields and open a route to polarization-sensitive sensing and state reconstruction in spectral regions that are difficult to access directly.

We present the results of an experimental study of the anomalous anisotropy of alignment signals in cesium vapors under strong spin exchange conditions in zero magnetic fields under linearly polarized optical pumping. We show that the anisotropy of the Hanle resonances in the plane perpendicular to the pump beam increases sharply with increasing concentration. In one direction, the resonance widths are determined by classical spin exchange, while in the other, by the SERF (Spin-Exchange Relaxation Free) effect. With further concentration increases, additional nonlinear effects arise, such as an increase of the normalized signal amplitude, effective magnetic field, bistability, hysteresis, and memory. To explain these observations, as well as the results presented in our previous studies, we construct a demonstration theoretical model incorporating spontaneous polarization effects arising under strong spin exchange. The model qualitatively shows that the experimentally observed ultra-narrow alignment resonances may originate predominantly from quadrupole anisotropy associated with spontaneous transverse orientation projected onto the detection axis.The unique properties of these resonances, such as their ultra-small width and magnetic field-controlled bistability with a long-term memory effect, make them promising for use in quantum sensing and information.

Speckle is an intrinsic pattern in optical coherence tomography (OCT) that obscures fine image features and degrades effective resolution. In this study, we propose a numerical speckle reduction method based on the dispersed scatterer model and the imaging formulation of OCT. Utilizing the shifted-complex-conjugate-product, the proposed method digitally modulates speckle patterns by shifting the complex en face OCT signal and averaging the resulting real-part images. This approach allows for effective speckle suppression using a single volumetric acquisition without additional hardware modifications. OCT point spread function phantom measurement demonstrated lateral resolution preservation of the proposed method. We validated the method using a custom-built full-field swept-source OCT system on human breast adenocarcinoma spheroids and a zebrafish eye. Quantitative evaluations using the contrast-to-noise ratio and equivalent number of looks demonstrated that the proposed method significantly outperforms conventional frame-averaging techniques. The speckle-reduced images revealed microstructures previously obscured by speckle, such as necrotic regions in spheroids, while preserving the original image sharpness and resolution.

Nanophotonic traps for cold atoms typically have trap volumes that are orders of magnitude smaller than, e.g., free-space optical tweezers. This makes efficient loading of these traps challenging, thereby limiting the total number of atoms coupled to the nanophotonic waveguide. Here, we demonstrate that $Λ$-enhanced gray-molasses ($Λ$GM) can substantially increase the number of trapped atoms in a nanofiber-based cold-atom setup. Specifically, we observe a six-fold increase in the number of loaded atoms compared to conventional red-detuned polarization gradient cooling. Despite the unusually small depth of our optical trap of only 24 $μ$K, we load about 4000 individual Cesium atoms, achieving optical depths exceeding 140 and reaching the collisional blockade regime over a length of approximately 1 mm. After loading, we perform efficient EIT-assisted cooling that is found to increase the trap storage time to 400(9) ms. This is a 5-fold improvement over the passive storage time. Remarkably, EIT-cooling also works with two co-propagating nanofiber-guided light fields and requiries only about a few hundred picowatt of optical power. Our results provide an efficient method to boost both the number of loaded atoms and the storage time of nanophotonic atom traps.

Jacobian-Free Newton-Krylov (JFNK) methods avoid forming the full Jacobian, but still require Jacobian-vector products, i.e., Gateaux derivatives of the nonlinear residual along Krylov directions. In standard Finite Differences (FD) formulations, these products are obtained by perturbing the Newton state and differencing residuals, making the linearization sensitive to round-off error and floating-point precision. This work evaluates the global impact of forward-mode Automatic Differentiation (AD) as a replacement for FD Jacobian-vector product in finite-precision JFNK solvers. The comparison keeps the discretization, Newton iteration, line search, Krylov methods, tolerances, and CPU/GPU backend fixed, only varying linearization strategy. Benchmarks include Burgers dynamics, Su-Olson radiation diffusion, reaction-diffusion, and nonlinear time-harmonic Maxwell equations, each evaluated in different nonlinear regimes. By preventing degradation of the Krylov operator, AD accelerates computation by 2-3 orders of magnitude across both CPU and GPU architectures. More importantly, it drastically improves global solver robustness, achieving a minimum completion rate of 95%, compared to just 42% for FD. Ultimately, accurate Gateaux derivatives unify performance and accuracy in JFNK methods, making AD the optimal choice for stiff nonlinear and reduced-precision environments.

The conventional formulation of power absorption, optical forces, and torques on dipolar particles involve lenghty and cumbersome expressions that obscure their shared physical origin. We apply a bispinor formalism that unifies these disparate phenomena in a very general case including chiral and nonreciprocal particles. This reveals that force, torque, absorbed power, and absorbed helicity rate can all be concisely expressed in terms of broken symmetries, and leads to the fundamental inequalities that dipolar particles' cross-sections must satisfy. This framework uncovers profound connections normally hidden behind complex algebra -- for instance, pressure forces depend exclusively on the difference in linear momenta of different light components and the corresponding breaking of symmetry by a particle, and optical recoil forces depend exclusively on helicity cross sections -- providing clarity, conciseness, and a powerful predictive tool for arbitrary dipole interactions.

Laser ablation in liquids enables the synthesis of surfactant-free nanoparticles but remains limited in productivity due to intrinsic constraints imposed by the liquid environment. These constraints include nonlinear optical losses, material redeposition, and cavitation bubble-induced shielding. Temporal intensity shaping of the incident laser pulse offers a potential route to mitigate these limitations. Here, ultrashort GHz-burst ablation is applied to laser ablation of gold in water. By distributing the pulse energy into a sequence of picosecond sub-pulses arriving within the nanosecond time window preceding cavitation bubble formation, GHz-burst irradiation enables energy delivery before the onset of bubble-induced shielding. This increases the threshold fluence for nonlinear losses and yields an ablation efficiency enhancement of up to a factor of three compared to single-pulse ablation. Importantly, this efficiency gain is not accompanied by an increase in cavitation bubble size or lifetime. In addition to enhanced efficiency, burst irradiation yields a twofold narrower nanoparticle size distribution. These results demonstrate that GHz-burst ablation is a promising approach to increase productivity while simultaneously improving nanoparticle quality.

Power grid frequency stability is fundamental to the secure operation of modern energy systems, yet the growing penetration of renewables and the associated reduction of system inertia have made frequency fluctuations increasingly non-Gaussian and difficult to model. Existing stochastic models based on standard Ornstein--Uhlenbeck-type restoring terms yield a unimodal frequency distribution and therefore fail to reproduce the bimodal structure, central suppression, and heavy tails widely observed in empirical data. Here, we propose a data-driven stochastic process that combines a Gaussian-core potential with superstatistical modeling, assuming slowly fluctuating coefficients for the grid dynamics. The Gaussian-core potential captures the potential barrier that gives rise to the characteristic double-peak structure of frequency distributions. Fitting the model to frequency data resolved at one-second intervals from the Great Britain grid, we find that the central barrier parameter increases substantially from 2020 to 2025 as the grid inertia progressively decreases. To simulate superstatistics, we use an Euler--Maruyama discretization and sample the drift amplitude from a lognormal distribution, thereby successfully reproducing empirical bimodality and heavy tails, as well as the autocorrelation decay. Our results establish a compact and interpretable model for characterizing the evolving complexity of low-inertia grid frequency dynamics.

To address the fundamental limitations imposed by chromatic dispersion and environmental susceptibility in standard single-mode fiber (SMF) for long-haul high-precision time transfer, we systematically explore the application potential of hollow-core fiber (HCF) through comparative experiments. We designed a bidirectional time transfer platform enabling direct comparison between HCF and SMF links across distances of 91 km, 68 km, and 54 km. We quantitatively characterize the impact of critical non-reciprocal error sources, specifically the optical Kerr effect and chromatic dispersion, under varying laser power, wavelength drift, and environmental perturbations. Our results show that HCF exhibits significantly suppressed dispersion, with a mean coefficient of 3.4 ps per nm per km, and reduced environmental sensitivity compared with SMF. Notably, over the 91 km link, the HCF yields a signal-to-noise ratio (SNR) enhancement of more than 24 dB and confines the time deviation to less than 80 ps, which is nearly an order-of-magnitude improvement over SMF, where the time deviation exceeds 600 ps, while remaining nearly immune to power and wavelength fluctuations. Under 24 hour diurnal monitoring, the 68 km HCF link demonstrates strong robustness, with environment-induced time delay fluctuations of 776 ps, corresponding to only 24.5% of those in SMF, which reach 3166 ps. Consequently, the time transfer stability, evaluated by time deviation (TDEV), reaches 0.2 ps at an integration time of 1000 s, representing a twofold improvement over SMF. These findings validate HCF as a superior transmission medium with low latency, low nonlinearity, and high thermal stability, paving the way for next-generation ultra-stable, long-haul time-frequency distribution networks.

Efficient, scalable, and magnetic-field-free superconducting diodes are essential for future superconducting electronics; yet, despite significant efforts, such practical devices remain unrealized. The main challenge lies in achieving broad-range in-situ tunability, both for optimization and for achieving transistor-like operation. Here, we study diodes based on four-terminal niobium planar Josephson junctions. We show that the multiterminal structure eliminates the need for an external magnetic field and enables essentially unrestricted in-situ tunability, along with reconfigurability of the diode polarity, leading to new functionality. For example, we demonstrate that such diodes can operate as Gauss neurons via reentrant superconductivity. By deliberately tuning the junction parameters, we obtain effectively infinite nonreciprocity (within experimental resolution) leading to threshold-free ac-current rectification. Such technologically simple, reconfigurable, and broadly tunable diodes could be instrumental for future digital and neuromorphic computing.

A recently developed approach, conditional probability density functional theory (CP-DFT), yields direct access to the exchange-correlation hole of a system, an important correlation function that is not available from any standard DFT calculation. We present the first results for extended materials with periodic boundary conditions. We demonstrate that CP-DFT works on weakly correlated materials (Na, Si). When applied to the prototypical Kagome material $CsV_3Sb_5$, we find $d$-orbital correlations that are not captured by standard DFT. Such distribution leads to a positive finding probability between two separated electrons and an enhanced charge density wave signal, suggesting a useful approach for strongly correlated systems.

We demonstrate an on-chip 0.96 TOPS hyperdimensional photonic tensor core by utilizing a time-spacewavelength multiplexed silicon photonic Crossbar (Xbar). The novel architecture relies on serializing the large matrix-vector or tensor-vector products by unfolding multiply and accumulation operations over time domain, while simultaneously distributing the computational workload over different spatial and wavelength channels. We experimentally demonstrate the operation of a 4-channel 2-input TSWDM Xbar that incorporates 56 GHz electroabsorption modulators (EAMs) and 4-channel integrated multiplexing stages. Its successful operation as a 4x2x1 tensorvector multiplication unit demonstrated an average error of 3.9%. Its performance as a photonic AI accelerator was also evaluated in the classification task of the Iris dataset, presenting experimental accuracies of 93.3% at data rates between 4x10 and 4x30 GBd, reaching 83.3% when the data rate increases to 4x60 GBd. Finally, we discuss the TSWDM Xbar scalability potential, revealing that the inclusion of a WDM scheme in the SDM architecture reduces the operating laser power, feasibly boosting the potential of constructing photonic accelerators with computational throughput in the POPS regime.

Achieving reliable joining between transparent materials and metals under non-optical-contact conditions remains challenging due to limited energy coupling and uncontrolled interfacial reaction across $μ$m-scale gaps. Burst-mode ultrafast lasers provide a potential solution for large-gap welding through temporally distributed energy deposition. However, the underlying interaction mechanisms and achievable joining limits remain unclear. In this study, burst-mode ultrafast laser welding of sapphire to Invar alloy was investigated under controlled interfacial gaps from 3 to 10 $μ$m. Cross-sectional microscopy, elemental mapping, white-light interferometry, and shear testing were employed to analyze joint morphology, elemental distribution, fracture behavior, and mechanical performance.After optimization of the processing parameters for burst-mode ultrafast laser welding, the interfacial morphological evolution and joint strength under different gap conditions were systematically investigated. At a 3 $μ$m gap, cyclic thermal stresses induced by burst pulses generate transverse micro-crack networks in sapphire, accompanied by a reduction in joint strength with increasing sub-pulse numbers. Notably, at a 10 $μ$m gap, where single-pulse welding fails, burst-mode ultrafast laser welding enables interfacial bridging with a maximum shear strength of 6.3 MPa, representing the highest level among published studies.These results indicate a gap-dependent evolution in burst-mode welding behavior governed by crack formation and energy accumulation. This study provides an important theoretical basis and practical guidance for achieving high-performance joining of dissimilar materials under large gap conditions.

Optical neural networks offer a route to low-latency and energy-efficient inference by encoding computation in light propagation. However, most existing implementations rely on planar photonic circuits or discretely spaced diffractive layers, restricting volumetric integration and imposing stringent alignment requirements. Here we demonstrate a volumetric optical scattering neural network (OSNN) in which densely packed weak scatterers form a three-dimensional, locally connected optical computing medium. In contrast to fully connected diffractive architectures, the OSNN uses near-field scattering interactions, described under the first-Born approximation, to compress optical interconnections into a monolithic volume. We implement this concept using resilient inverse design and two-photon nanolithography, yielding OSNN devices with a volume of ~$3.8*10^{-4}mm^{3}$ and a record-breaking neuron density of $1.0*10^{9}/mm^{3}$. Experimentally, the fabricated classifier achieves $94.8\%$ blind-test accuracy on MNIST, while the imager performs optical compressed imaging with a $1-μm$ effective resolution and average FSIM values of $0.93$ on Fashion-MNIST and $0.91$ on VesselMNIST3D. OSNN paves the way for ultra-dense, ultra-compact, and efficient optical computing, creating a universal platform for embedded optical intelligence and promising widespread application in AI fields ranging from autonomous driving to medical diagnosis.

The orientation of cell division is a major determinant of three-dimensional plant morphogenesis. Whether and how a simple division orientation rule explains the establishment of symmetric body plans is a fundamental question. Testing such hypotheses is facilitated by a modeling framework that combines realistic three-dimensional cell mechanics, irreversible cell-wall growth, and a deformable tissue geometry. We recently introduced such a framework, a 3D mechano-geometric multicellular model of apical stem cell-driven morphogenesis. Here we document how the model is built from physiological and computational perspectives. We describe the triangulated thin-shell representation of cells, the treatment of turgor pressure, cell-wall elasticity and strain-driven wall growth, the cell-division algorithm together with its two pluggable division-rule implementations, and the remeshing operations that keep the triangulation well-conditioned as cells grow, divide, and deform. The aim of this paper is to make the present model accessible and customizable to experimental plant biologists.

Ultrasound for microstructure characterisation is increasingly studied and is often assessed through inversion performance. However, the framework is fundamentally constrained by the information content available in the measured response. Hence, this work examines identifiability directly by analysing the geometry of the forward operator in both a canonical pulse-echo model and a stochastic surrogate microstructure. For the canonical model, a closed-form sensitivity analysis reveals information limits arising from parameter coupling, dimensional restriction, and interface-driven saturation. For the surrogate microstructures represented by Gaussian random fields, the forward map from correlation length $D$ and texture-coherence parameter $T$ to the attenuation and velocity observables remains structurally full rank. However, the sensitivity geometry is strongly anisotropic, with uneven parameter influence across the observable space. When intrinsic microstructural variability is incorporated, practical identifiability is further reduced. A variance-weighted Fisher framework shows that recoverability is governed by the balance between sensitivity magnitude and stochastic variability, rather than by structural rank alone. Inversion results confirm this behaviour: single observables produce elongated and weakly constrained objective landscapes, whereas combined observables improve conditioning through complementary sensitivities. These results show that, within the feature-level framework considered here, identifiability limits are governed primarily by forward-map structure and intrinsic variability, with direct implications for observable selection and measurement design.

Biological systems perform complex multi-step processes in a reproducible way despite underlying stochasticity. The standard explanation is micromanagement by molecular machinery that recognizes and corrects specific errors. Here we study conditioning, a qualitatively different strategy in which attempts failing a coarse criterion are destroyed and do not leave a physical record. The surviving, i.e., conditioned, ensemble is narrower and therefore more ordered. We model conditioning through stochastic resets in a ''socks-before-shoes'' model of a growing population, where $n$ actions must be completed in any order to replicate and any replication attempt not finished by a threshold time is discarded. We find that resets impose hierarchical temporal ordering of the $n$ actions without microscopic control over which action happens when. When disorder carries a sufficient time penalty, this ordering is free: the fastest-growing population is automatically the most ordered, with no direct selection for order required. Save points, at which verified progress is preserved across resets, allow conditioning to scale to complex multi-step processes. Conditioning provides a minimal route to reliable behavior, requiring only a clock rather than molecular machinery that recognizes specific errors. For the right class of processes, it pays for itself.

Ultrafast optical imaging has enabled direct observation of femtosecond-nanosecond dynamics, yet three-dimensional (3D) dynamic measurements at high numerical aperture (NA) remain hindered by the intrinsically shallow depth of field (DoF) of conventional microscopes. Here, we propose an ultrafast, wide-field pump-probe interferometric microscope on a telecentric platform that significantly extends the effective DoF to ~18 micrometer at a high NA of 0.9 while maintaining high spatial resolution (down to 235 nm) and temporal resolution (~170 fs). The system enables single-frame 3D topography reconstruction without axial scanning or multi-view acquisition. We demonstrate these capabilities by capturing axial material flow during laser-induced microsphere melting that remain unobservable with conventional narrow-DoF systems, and by tracking the azimuthal rotation of ablation lobes during axial propagation of temporal focused spatiotemporal optical vortex (TF-STOV) pulses, directly revealing the spatiotemporal evolution of STOV-matter interactions

Reconfigurable radio-frequency front ends in modern radar and wireless systems require delay elements that simultaneously offer low-loss, low noise, compact form factor, and wideband frequency agility. However, electromagnetic, acoustic, photonic, and active-circuit delay technologies each fail to deliver this combination. Here we report a microwave delay platform based on magnetostatic surface waves (MSSWs) in microfabricated 18 $μ$m yttrium iron garnet (YIG) waveguides, in which co-engineering the spin wave dispersion with the radiation impedance of meander-line transducers grants pitch-controlled access to distinct dispersive or near-constant group-delay regimes. Tuned continuously from 6 to 19.6 GHz under magnetic bias, the delay lines deliver group delays of 3.3 to 42.8 ns at insertion losses of 2.5 to 10.1 dB and nonreciprocal isolation of 24 to 39 dB, all measured directly into 50 $Ω$ without external impedance matching. Length-resolved characterization yields unit-time propagation losses of 56 to 109 dB/$μ$s and propagation Q-factors that rise monotonically from 3002 to 4893 across the operating range, exceeding state-of-the-art fixed frequency acoustic delay lines at every benchmarked frequency. These results establish microfabricated YIG as a versatile, low-loss microwave platform for next-generation reconfigurable RF signal processing.

Complex frequency excitations, oscillating signals whose amplitude decreases exponentially in time, have recently been demonstrated to significantly increase the effective quality factor of mechanical resonators. In this work, we investigate the accuracy of natural frequency estimation in mechanical systems under noise using such excitations. The analysis is performed on an underdamped linear time-invariant single-degree-of-freedom spring-mass-damper system. We employ tools from information theory, namely Fisher information, to systematically quantify the sensitivity of complex-frequency excitation to measurement noise. Explicit closed-form expressions are derived relating Fisher information to excitation and system parameters under both Gaussian white and colored noise. The theoretical predictions are verified through Monte Carlo numerical simulations. The results indicate that appropriate selection of excitation parameters can significantly enhance the Fisher information, leading to improved estimation accuracy under complex-frequency excitations compared with conventional harmonic excitations. Experimental results demonstrate the advantages of complex-frequency excitation in terms of both accuracy and robustness of natural-frequency estimation. These findings establish a foundation for the development of high-performance sensors and novel nondestructive evaluation methods.

Quantized tensor trains (QTTs) are a multiscale computational framework that can potentially reduce the computational cost of solving partial differential equations and initial value problems by making low-rank approximations. However, its use is somewhat limited in practice, in part due to the challenges that arise when making low-rank approximations of the quantized data. For example, when performing long-time dynamical numerical simulations, it has been observed that the accumulation of numerical errors arising from both the discretization of the partial differential equation itself and the low-rank approximation can lead to increased rank and noise-dominated results. Focusing on a set of advection-dominated test problems relevant to electromagnetic plasmas and electromagnetic fields, this work investigates how the choice in time integrator, the addition of numerical dissipation, and the choice in problem representation can affect the efficiency and success of the QTT calculations.

In this work we evaluate the excitation and measurement patterns (EMP) for networks with tree topology. We investigate guidelines for the selection of the minimal EMPs, i.e. those with the least number of excited and measured nodes combined, for which the accuracy obtained, in terms of the trace of the asymptotic covariance matrix, is optimal. We introduce the concept of partial information matrix as a means to systematically obtain the information matrix for any dynamic network. For a specific tree class, called cross, we show that the accuracy of a particular module depends on the magnitude of the parameters to be estimated. Furthermore, when all factors are equal, it is best to excite. %we show that for small magnitudes of this parameter, it is best to excite. We extend a topological condition for branches under which the accuracy of a particular module of the network is independent of the other parameters from the tree. We provide a numerical analysis showing that our guidelines could be used as a selection tool for minimal EMPs for tree networks.

A time-Floquet reconfigurable intelligent surface (TF-RIS) periodically modulates its elements within a signaling interval, enabling frequency conversion and additional degrees of freedom compared with a conventional RIS. Time-Floquet multiport-network theory (TF-MNT) provides a physics-consistent model for TF-RISs that accounts for inter-element coupling, but its practical use requires estimating the underlying parameters when the TF-RIS design and radio environment are (partially) unknown. In this Letter, we propose a segmented estimation approach for constructing an accurate proxy TF-MNT model from end-to-end measurements. First, with the TF-RIS operated as a conventional RIS, we estimate conventional proxy MNT parameters independently at each considered time-Floquet harmonic. Second, under periodic time modulation, we align the inherent ambiguities among the per-harmonic conventional proxy MNT parameters, considering three measurement setups with different access to phase and harmonic information. Based on full-wave numerical simulations, we quantify the impact of the number of measurements and the noise level on the proxy-model accuracy. Finally, we demonstrate the performance loss incurred without the proposed ambiguity alignment in a canonical harmonic backscatter communications scenario.

Individual contributions to the spread of an epidemic vary widely due to an individual's location in a social network and their intrinsic ability to spread or contract diseases. While the effect of heterogeneous population structure and infection rates is well-understood, less studied is the impact of population-level covariance between susceptibility and transmissibility, despite empirical evidence showing that both susceptibility and transmission vary across individuals. We introduce a mathematical modeling framework incorporating population subgroups, each with its own joint distribution of susceptibility and transmissibility. We apply this framework to the susceptible-infected-recovered (SIR) model to examine the effect of community structure and degree heterogeneity. We derive analytical expressions for the basic reproduction number, which, when reduced, corroborates prior results and validate these results with numerical simulations. We pair these estimates with simulations exploring first, the temporal dynamics of this model with the homogeneous SIR model, and second, implications for effective social intervention. This analysis provides a foundation for future studies exploring the interplay between structural and dynamical heterogeneity in infectious disease transmission.

Permeability of hydrogen isotopes in molten salts is commonly inferred from permeation experiments using simplified one-dimensional interpretations, which may not capture the coupled transport pathways present in realistic systems. In this work, a multi-dimensional, multi-material hydrogen isotope transport modeling framework implemented in FESTIM is benchmarked against permeation measurements from the HYPERION experiment conducted at the MIT Plasma Science and Fusion Center.The model explicitly resolves transport across molten salt and nickel structures, as well as external boundary conditions, enabling system-level interpretation of the measured permeation fluxes over the temperature range 773-973K. Rather than relying on idealized one-dimensional formulations for permeability estimation, this study employs a validation-informed inverse framework to assess how multidomain transport and external boundary assumptions influence the permeability inferred from experimental fluxes.Two limiting external boundary conditions, representing ideal coating and uncoated vessel behavior, are used to define a physically motivated envelope for hydrogen isotope exchange with the environment.The model captures the observed magnitude and temperature dependence of permeation fluxes under both conditions, while revealing significant lateral transport and sidewall leakage pathways that are not represented in one-dimensional interpretations.The inferred FLiBe permeability exhibits consistent Arrhenius behavior but spans a range that depends strongly on the assumed boundary conditions, demonstrating that using one-dimensional formulations to describe a permeation experiment may not be adequate to extract accurate permeability.These results provide a physically grounded framework for interpreting permeation measurements in coupled liquid-metal systems and highlight the importance of multidomain transport modeli

Second-order Moller-Plesset perturbation theory (MP2) provides accurate correlation energies for periodic systems but suffers from finite-size errors (FSEs) that have inverse volume scaling due to the Coulomb kernel singularity in reciprocal space. This error scaling limits the routine applicability of MP2 to real materials, requiring prohibitively dense k-point meshes for convergence toward the thermodynamic limit (TDL). We introduce MP2 singularity subtraction (MP2SS), a systematic approach that applies the singularity subtraction strategy to reduce MP2 FSEs. The method employs auxiliary functions and fitting procedures that consider both the singularities present at the origin in reciprocal space and also the discontinuities in the MP2 structure factor that arise from finite k-point sampling. We present three possible MP2SS configurations (Gaussian, exponential, and tuned) which use different combinations of decay functions and demonstrate their performance for gapped systems. All MP2SS configurations consistently achieve millihartree accuracy for correlation energies at coarser k-point meshes than with no correction. Our results establish singularity subtraction as a powerful and flexible approach for mitigating finite-size errors in periodic correlation methods and provide a foundation for extending the technique to higher-order perturbation theories and other post-SCF methods.

Control of light polarization and propagation in sub-wavelength architectures is foundational to nanophotonic technologies. A frontier direction is to leverage strong optical spin-orbit interactions to realize polarization-selective light steering, known as the photonic spin Hall effect. In this context, hyperbolic plasmon polaritons (HPPs) are of particular interest as they offer large optical spin-orbit coupling from strong confinement and dielectric anisotropy, as well as ray-like propagation. Despite theoretical predictions, however, the hyperbolic spin Hall effect in natural materials has remained elusive. Here, we demonstrate the hyperbolic spin Hall effect in the visible and near-infrared range in the natural hyperbolic van der Waals metal MoOCl2. Enabling this discovery is a novel far-field pump-probe microscope that facilitates the launching and imaging of HPPs with exceptional sensitivity through interference with a high-momentum reference field. This approach preserves excellent control over light polarization, overcoming a key barrier to polarization-selective interrogation of hyperbolic materials. We show that both hyperbolic and surface plasmons in MoOCl2 display chiral fields, and that their propagation direction can be completely switched upon light helicity reversal. Our results demonstrate on-demand steering of chiral plasmons, firmly establishing natural hyperbolic materials as ideal components for reconfigurable nanophotonics and chiral light-matter coupling.

Quantum emitters in hexagonal boron nitride (hBN) have emerged as a promising solid-state platform for quantum technology applications. However, a persistent challenge in the field is the unclear origin of many observed emission lines, particularly in the visible range, which can be difficult to distinguish from signals arising from organic or process-induced contamination during sample preparations and handling. This ambiguity limits both the reproducibility of emitter generation and the reliable identification of truly intrinsic quantum defects. This work provides a step-by-step framework to assess whether quantum emitters in electron-irradiated hBN are associated with organic contaminants introduced during sample preparation. We employ hyperspectral imaging, thermal annealing, and oxygen plasma etching to investigate the origin of the green-yellow emitters in electron-irradiated hBN. The combined results not only rule out organic contamination as the source of emission but also provide insight into the spectral variability, thermal stability, and vertical localization of the emitters generated in electron-irradiated hBN that was created without any pre- or post-processing. In addition, our experiments demonstrate the feasibility of creating stable emitters in hBN with thicknesses below 10 nm. These findings provide practical guidance for the identification and controlled implementation of hBN-based single-photon emitters in quantum photonic devices.

Natural hyperbolic materials offer a powerful platform for light-matter interactions by supporting highly anisotropic electromagnetic modes without the need for artificial patterning. In this work, we experimentally demonstrate that the nodal-line semimetal PbTaSe$_2$ exhibits robust hyperbolic optical behavior in the visible to near-infrared spectral range, which arises intrinsically from its anisotropic electronic structure and layered crystal symmetry. By combining first-principles calculations, ellipsometry, Drude-Lorentz modeling, and reflectance measurements, we establish a consistent experimental and theoretical picture of bulk hyperbolicity in this material. This hyperbolicity is of plasmonic origin and is characterized by a competitive quality factor ($Q_\mathrm{max} \approx 2.8$) and a very large anisotropy parameter ($|R| \approx 231$) at 0.78 eV.

High throughput screening was used to study of the biokinetics of F. venenatum A3/5 cultivation on alternative carbon substrates, including monosaccharides, disaccharides and mixtures relevant to food & beverage, dairy and agricultural waste streams. Expired functional drink from the beverage sector was also assessed as the primary carbon source for mycoprotein production. Growth data was analysed using modified single and multiphase Gompertz models for comparison of maximum specific growth rate and progression milestones across diverse growth regimes. Time-series substrate and byproduct data was analysed using comparative metrics, providing an explanatory basis for the different growth phenotypes observed. Substrate type strongly influenced the apparent carbon allocation strategies, with rapidly consumed sugars such as glucose and sucrose supporting high growth rates, low biomass yield and a high degree of fermentative byproduct formation. Fructose and xylose cultivations led to slower overall growth but higher biomass yield and lower byproduct formation. Galactose and lactose showed distinct dynamics that suggested co-existence of transport and metabolic induction limitations. In all dual-substrate systems, sequential utilisation was observed. However, metabolic inheritance and environmental shift effects were highlighted as potential kinetic limitations. These conditions exhibited stunted diauxic growth and low yield from secondary sugars, with glucose-dominated primary growth significantly reshaping secondary substrate efficiencies relative to their study in silo. The expired functional drink supported highly rapid growth and achieved the highest maximum specific growth rate and biomass titre of all conditions examined, alongside reduced fermentative overflow and enhanced ethanol reassimilation relative to a compositionally matched synthetic control.

A Wiener-Hopf-type integral equation for the stationary PDF of a reflected random walk is derived rigorously based on modern probability theory, and an application to battery energy storage systems (BESS), specifically the sizing of the inverter, is discussed in depth. The methodological steps include the construction of a Markov kernel, the derivation of a Fredholm integral equation of the second kind for the PDF of the BESS power, and an analytical solution of the equation based on a Neumann series. The analytical results were compared against numerical solutions obtained with the Nystrom method, as well as against the results of an algorithmic simulation using simulated input time series. The use of truncated versions of the analytic solution allows for the construction of simplified design rules for the power systems practitioner. General insights into inverter sizing criteria of storage systems for ramp-rate control of variable renewable energy (VRE) sources such as wind and solar are provided.

Magnetic interatomic potentials need to account for coupled lattice and spin degrees of freedom, yet constructing reliable training sets remains costly because noncollinear first-principles labels are expensive. Active learning can mitigate this cost, provided that the uncertainty estimate is physically meaningful for the magnetic-response targets that drive spin reorientation. Here we extend the $\mathrm{e}^2\mathrm{IP}$ evidential framework to magnetic machine-learning interatomic potentials by formulating the projected spin-force likelihood and the corresponding epistemic uncertainty in the tangent plane orthogonal to the local spin direction. This construction prevents the uncertainty model from allocating probability mass to a radial spin component that is absent from the constrained-moment supervision. Using bulk BiFeO$_3$ and monolayer CrTe$_2$ as benchmark systems, we show that the resulting tangent-plane epistemic uncertainty indicator $U_{\mathrm{epi}}^{\mathrm{sf}}$ correlates strongly with prediction error and selects more informative configurations than random sampling, simultaneously improving energy, force, and projected spin-force accuracy. These results demonstrate a physically interpretable and data-efficient route for constructing uncertainty-aware magnetic machine-learning interatomic potentials.

To address the increasing demand for ultra-high-capacity wireless communication, terahertz (THz) frequencies near 300 GHz are attracting attention as a new spectral frontier. This work presents the first experimental demonstration of error-free (BER $< 1\times10^{-9}$) 10 Gbps transmission in the 300 GHz band using a soliton microcomb generated in an integrated silicon nitride (SiN) microring resonator. While many previous microcomb-based THz demonstrations have focused on coherent modulation formats and operation near the forward-error-correction (FEC) limit, this work investigates a simple intensity-modulation/direct-detection (IM-DD) on-off keying (OOK) architecture suitable for low-complexity THz links and fiber-wireless integrated systems. Although the experiment was conducted in a short back-to-back waveguide configuration, the generated THz wave enabled stable low-BER transmission without FEC or advanced offline signal processing. Analysis of the error-free threshold power indicates the feasibility of free-space transmission over several tens of meters with high-gain antennas and THz-band amplifiers. These results demonstrate the feasibility of robust low-complexity THz photonic links based on soliton microcombs for short-range fiber-wireless integrated systems.

Dyadic Green's function is an important tool of computational photonics, giving deeper insights into light-matter interaction. We present an operator approach to the derivation of the dyadic Green's function of a generic anisotropic planarly-layered medium for both electric and magnetic fields. The resulting Green's function is expressed through the evolution operators (a kind of transfer matrices) of the comprising layers and the surface impedance tensors, the singular term being naturally separated from other terms. The operator approach to the Green's function simplifies both the conceptual understanding of the problem and the subsequent practical applications, some of which are demonstrated here. The proposed approach can be easily generalized to the case of spherical and cylindrical layers. The obtained results can be applied in nanophotonics engineering problems.

We present an analytical emission model that accurately predicts the properties of effusive sources formed by long collimation tubes. By construction, it captures the full range of molecular flow, from the transparent flux regime, which occurs in highly rarefied gases, to the opaque regime, which arises as the flux increases and interparticle collisions become non-negligible. The model is based on a previously developed secondary-emission-surface approach, improved here to overcome its internal limitations and recover the well-established axial flux intensity. It provides accurate analytical predictions of the angular intensity distribution in the molecular flow regime, offering valuable guidance for the design of efficient primary sources across a broad range of experiments in atomic and molecular physics

Empirical confirmation of the environmental-dominance inequality Var(ln rho_eff) >> Var(ln k) from arXiv:2605.02985, computed directly from three public datasets (Opportunity Atlas, World Bank GDP per capita PPP, World Inequality Database) at four levels of aggregation: U.S. census tracts, between countries, within-country deciles, and the global pooled-individual distribution. The headline global value Var(ln rho_eff) = 4.33 yields a dominance ratio R in [27, 134] across plausible sigma_ln k in [0.18, 0.40]. The inequality holds with one-to-two orders of magnitude margin at the global and within-country-decile levels, with a single-digit but still dominant margin between countries, and collapses to R in [0.33, 1.61] within already-homogenized U.S. census tracts for income. A 1990-2022 time series shows the global aggregate stable while composition shifts from between-country dispersion (-34%) to within-country dispersion (+26%), consistent with international convergence plus Piketty r > g. Multi-outcome validation shows the inequality is robust for income, infant mortality and incarceration but shrinks toward parity for outcomes targeted by sustained global convergence (life expectancy). Partial-identification and selection-bias bounds (Chetty-style 40-50% selection share) leave R in [14, 80]. All inputs and outputs are SHA-256 hashed in an append-only manifest and fully reproducible from the accompanying notebooks.

Preserving scalar boundedness is important for numerical schemes used in turbulent compressible multi-component flow simulations to prevent unphysical results and unstable simulations. However, ensuring scalar boundedness for high-order, low-dissipation numerical schemes poses challenges in highly under-resolved conditions due to inherent dispersion errors that generate spurious oscillations. Numerical dissipation is needed to mitigate these oscillations, but excessive dissipation negatively affects resolution. In this work, we propose formulations for high-order finite-difference schemes to preserve scalar boundedness without predefined bounds, while maintaining high accuracy and low numerical dissipation. The proposed formulations augment a non-dissipative numerical flux of a high-order central-difference scheme with an explicit dissipative numerical flux that adaptively switches between high-order and low-order formulations. Building on a deliberate choice of the non-dissipative flux, we construct two schemes using Jameson's artificial viscosity method and a monotonicity-preserving limiter as the dissipative flux. We examine the schemes in one-dimensional scalar advection problems and a three-dimensional temporal turbulent mixing-layer case involving sharp scalar gradients and under-resolved conditions, evaluating their accuracy, boundedness of species mass fractions, and numerical diffusivity. The scheme with the monotonicity-preserving limiter demonstrates superior performance.

Forward propagation of input uncertainties in physics-based wildfire models is computationally prohibitive, limiting the use of high-fidelity simulators in risk assessment workflows. This work introduces a geometry-aligned bi-fidelity surrogate framework that addresses the convection-dominated nature of wildfire spread by mapping low- and high-fidelity solution snapshots onto a common reference domain prior to basis selection and reconstruction. Unlike conventional bi-fidelity schemes, which combine spatially shifted snapshots and thus suffer from oscillations and excess basis requirements near sharp fronts, the proposed mapping aligns the dominant front geometry through per-variable shift/stretch transforms in 1D and an activity indicator-based affine alignment in 2D, so that reduced bases compare physically corresponding structures rather than displaced ones. Building on the ADfiRe physics-based simulator, we demonstrate the method on 1D and 2D test cases in which low- and high-fidelity models differ in mesh resolution and physical completeness. Across both settings, the geometry-aligned surrogate reproduces full-field temperature and fuel composition with substantially lower error than its unmapped counterpart, eliminates Gibbs-type oscillations near steep gradients, and recovers high-fidelity probability density functions for key quantities of interest (e.g., maximum temperature, evaporated moisture, and burned area). After offline training, online predictions are roughly three orders of magnitude cheaper than direct high-fidelity evaluation, making the framework a practical building block for many-query uncertainty quantification once the offline cost is amortized over enough queries. We discuss the conditions under which the geometric alignment is most effective, its limitations for non-convex or topologically complex fronts, and the path toward validation against real data.

We introduce two-quantum (2Q) fluorescence-detected pump-probe (F-PP) spectroscopy as a tool to probe ultrafast multiparticle interactions in many-body systems. We describe a pulse-shaper-based fully collinear setup utilizing phase cycling to capture the 2Q F-PP signal simultaneously with the one-quantum (1Q) F-PP signal. Thus, we investigate the dynamics of energy transfer and diffusion-limited annihilation. We apply a data post-processing strategy to isolate excited-state dynamics from spurious background. The technique is applied to a squaraine heterodimer and a squaraine copolymer to demonstrate the removal of so-called incoherent mixing that generally plagues action-detected nonlinear spectroscopy on multichromophoric systems. Specifically, we show that this approach is not only applicable to 1Q but also to 2Q F-PP signals, eliminating incoherent mixing contributions as well as other "parasitic" signals that result from pulse-overlap ambiguities. As a result, we retrieve background-free spectral and dynamical information of doubly excited electronic states.

Alnico magnets have gained renewed interest in the search for rare-earth free permanent magnets due to their high thermal stability and magnetisation. However, the limited coercivity of these shape-anisotropy-based alloys constrains their performance. Starting from a reference Alnico sample, we realised a finite elements micromagnetic study of exchange-decoupled rods by varying their dimensions and interrod spacing across those observed experimentally. We computed the hysteresis properties by progressing from micromagnetic simulations of a small number of rods within the magnetostatic field of their neighbours to large systems treated statistically based on the distribution of orientations of the grains. We compared the coercivity of an isolated rod with that of the exchange-decoupled system to highlight the effect of magnetostatic interactions. We computed analytically the stray field acting on a single rod as a consequence of its surrounding rods in order to confirm the scaling of the coercivity with the packing fraction p. We explored how intrinsic material properties influence magnetic behaviour by examining materials with different magnetocrystalline anisotropy constants and saturation polarisation values. Results from several hundred simulations were used to train a multi-layer perceptron regressor and predict the magnetic properties as function of the dimensions of the rods, interrod spacing and orientation of the grains. With this approach, we highlight the underlying trends by which nanoscale structuring, intrinsic material properties and grain alignment can be tailored to improve the magnetic properties of Alnico alloys.

Today's cutting-edge optical spectroscopic exploratory tools, such as Raman or infrared spectroscopy, rely on methods of signal enhancement as a route for their development. These methods are indispensable for substance identification and characterization in almost any scientific, regulatory, or industrial laboratory, therefore new and better methods of enhancement are always sought after. In this paper, the design of a new optical device for enhancement is presented, called nano-engineered microsphere (NMS). This device innovatively combines plasmons, a present flagship enhancement method, with a photonic nanojet, a new and emerging enhancement tool, to provide unprecedented properties in terms of affordability, stability, and performance. By using numerical simulations, a detailed design of the device is presented, and the optimization of device parameters for the strongest enhancement is investigated. The simulations show different influences of the parameters on the enhancement, from low to critical. The most influential parameter was found to be the radius of the nanoelement tip, which, at low values, showed a tremendous increase in the enhancement. The optimized device shows exceptionally promising abilities regarding the enhancement, while the estimated cost of production and use is low. Such properties paired with low price and ease of usage could enable the NMS to become one of the leading methods of enhancement in Raman and infrared spectroscopy with the spatial resolution towards nanometers.

The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting conventionally relies on real-world physical samples (e.g., white paint), inhomogeneous mixtures with embedded scatterers, or biological tissue-mimicking phantoms. Such methods, while effective in certain contexts, are not without complexity and limitations: the exact medium properties are challenging to control and often require laborious preparation, external characterisation techniques, are not easily reproducible between studies and cannot be matched precisely by numerical simulations. Here, we propose a simple all-digital implementation of random scattering which can be readily implemented on any setup capable of producing digital holograms. Our approach employs binary random phase masks encoded onto a spatial light modulator which perturbs the input beam's phase and amplitude. We highlight two methods to precisely tune distortion strengths which show excellent agreement between simulated and measured results. We demonstrate distortion strengths comparable to real-world scattering samples and illustrate two example applications to emulate scattering of scalar and vectorial structured light. Finally we showcase the versatility of this toolkit for emulating various amplitude and phase profiles and suggest several easy to implement alternative modalities accessible with this method. This digital phantom circumvents many of the practical challenges of physical samples, making it ideally suited for applications at the intersection of structured light, biological imaging and optical communications.

Reconfiguring the spectral output of nonlinear metasurfaces after fabrication remains challenging. We address this by exploiting the nonlinear Pancharatnam--Berry phase of $C_{3v}$-symmetric plasmonic metasurfaces. By integrating two metasurfaces inside a multipass cell, we experimentally demonstrate continuous spectral tuning of second-harmonic generation (SHG) phase-matching peaks across a 900--970 nm pump range by rotating one metasurface relative to the other. The extracted geometric phase follows the $3σθ$ dependence, and a full $2π$ tuning cycle is completed with $120^{\circ}$ of physical rotation. This establishes geometric-phase metasurfaces as a reconfigurable nonlinear platform, where mechanical rotation enables post-fabrication and broadband tuning of nonlinear optical responses.

Qualification of components operating in future fusion power plants will be heavily reliant on simulations of component behaviour. The lack of representative test environments for many aspects of the expected operating environment will necessitate full or partial virtual qualification of components. The cornerstone of virtual qualification is credible validation of the simulation models on which it relies. In this work, we present a probabilistic model validation framework that forms the basis for implementation of virtual qualification in fusion. We demonstrate our framework on a representative component; a high heat flux heat sink subject to a tightly coupled multi-physics loading. We perform data-rich, optimised experiments, in which we implement high fidelity diagnostics and rigorously quantify aleatoric and epistemic uncertainty on all measurements. Our simulation approach efficiently samples input uncertainty distributions to predict probability boxes describing component response, using a statistical surrogate to replicate behaviour of the finite element model we wish to validate. We then used a novel implementation of the modified area validation metric to quantify the model form error of the finite element model, isolating it from the aleatoric and epistemic experimental uncertainty. We discuss the contribution of our validation approach towards virtual qualification, and the benefits of the risk-based decision-making it facilitates. The experimental, simulation, and validation datasets are published as a benchmark of a probabilistic validation approach for fusion, and for use in development of new model validation methodologies.

Large eddy simulation has been widely used to simulate turbulence at balanced computational cost and accuracy. Many Subgrid-Scale (SGS) models have been proposed over the years, where data-driven and machine learning-aided approaches set the recent trend. To address the problem of extrapolation in these models, we propose a new data-driven SGS model based on an information-theoretic picture of turbulence. To this end, we estimate the model parameters by maximizing mutual information, which correspond to the scale-by-scale local equilibrium hypothesis in developed turbulence or "information preservation." An a priori test confirmed that the estimated parameters are in good agreement with the previously reported empirical values. Furthermore, a posteriori tests on periodic box turbulence and channel turbulence exhibited accuracy comparable to the existing models. These results suggest the utility of the information-theoretic picture of turbulence for constructing more generic SGS models without the need for empirically prescribed model parameters, while enhancing physical interpretability beyond black-box approaches.

Raman spectroscopy enables broadband, multi-species gas analysis by providing access to an entire vibrational spectrum in a single measurement. However, the sensitivity of gas-phase Raman sensing is often limited by weak signals and fluorescence background from various optical elements that constrain the achievable signal-to-noise ratio (SNR) through signal-dependent noise contributions (e.g. shot noise). Here, we present a cavity-enhanced Raman spectroscopy (CERS) gas sensor employing a 500 mW, 532 nm continuous wave (CW) laser and a simple, non-resonant two-mirror multi-pass cavity (MPC) operated at ambient pressure and near the concentric condition, providing up to 45 internal reflections. To quantitatively capture the impact of fluorescence on performance, a CCD-specific noise model was developed that links fluorescenceinduced baseline levels to measurement noise. Complementary optical simulations were employed to assess the signal collection efficiency in the MPC. Through a systematic analysis of fluorescence sources, the background was reduced substantially by step-wise elimination of fluorescent optics. The fluorescence-minimized setup resolves weak Raman signatures in ambient-air spectra, including CO2 peaks, O2 and N2 overtones, and ambient CH4 (2 ppm). Calibration measurements for O2 (diluted in N2), N2 (in O2) and H2 (in N2) demonstrate detection limits of 11 ppm, 5 ppm and 3 ppm, respectively, with a 180 s measurement time. The results highlight fluorescence mitigation as a key design lever for robust, field-oriented CERS instrumentation for trace gas sensing.

Exact diagonalization (ED) is a workhorse technique in computational quantum many-body physics, but published ED results are rarely accompanied by machine-checkable evidence of their numerical correctness. The community typically relies on the implicit trust chain LAPACK $\to$ user code $\to$ result, with at most informal agreement against another package treated as confirmation. We argue that this practice is inadequate for a method whose output frequently underpins theoretical claims, and we present \textsc{certify-ed}, a verification framework designed to be used \emph{alongside} existing ED packages (QuSpin, XDiag, ALPS) rather than as a replacement for them. The framework consists of (i) a multi-oracle eigensolver that runs three independent LAPACK paths and reports their pairwise disagreement, (ii) thirteen logically independent validation layers covering algebraic invariants, analytic limits, alternative algorithms, arbitrary-precision reference computation, conservation laws, dynamical consistency, and finite-size scaling, and (iii) tamper-evident SHA-256 hashed certificates that downstream consumers can verify. The framework also ships an error-injection layer that confirms the entire pipeline detects six injected error classes. Running on sixteen physics models from one-dimensional spin chains to two-dimensional Kitaev honeycomb clusters, our reference implementation passes 53 of 53 unit tests and 81 of 81 individual validation tests in under thirty seconds, with maximum disagreement against QuSpin of $1.6\times 10^{-14}$ across 320 eigenvalue comparisons, and agreement with 50-digit \texttt{mpmath} reference values to $1.6\times 10^{-15}$. The package is released under the MIT license on Zenodo and Github

Bound states in the continuum (BICs) arise from destructive interference suppressing radiation despite spectral overlap with the continuum. Here we show that Friedrich--Wintgen interference naturally emerges from a bright--dark supermode decomposition of resonances coupled through a shared radiation channel. In this basis, any finite leakage of a quasi-BIC induces a causality-driven reactive coupling enabling non-Hermitian pumping of the dark sector. We derive the optimal condition for this process and show that it corresponds to the supercritical coupling regime previously identified in [Nature 626, 765 (2024)], while naturally recovering universal quasi-BIC asymmetry scaling. Extending the theory to Dirac-like dispersions in photonic crystal slabs, we identify an open-Dirac singularity where the Dirac gap matches the supercritical regime. A four-wave Hamiltonian quantitatively reproduces rigorous coupled-wave analysis, revealing the breakdown of conventional critical coupling. Near this regime, absorptive cross-coupling induces coherent absorption interference and enables suppression of effective dissipative losses beyond conventional material limits. These results motivate the concept of a generalized bound state in the continuum (gBIC) as a limiting non-Hermitian state where radiative and effective gain compensate, producing a true divergence of the total quality factor. Overall, this work establishes a unified framework connecting BIC interference, Dirac topology, and non-Hermitian physics for ultra-high-Q enhancement and loss engineering in open photonic systems.

We study a triplet majority-rule opinion-dynamics model with collective reversal on quenched networks. Interactions occur on local triplets composed of one agent and two of its neighbors, while collective reversal acts only on unanimous triplets. This rule separates local conformity from external perturbations that disrupt local agreement. We show that quenched network topology shifts the order--disorder critical point away from the well-mixed value. For Barabási--Albert, Erdős--Rényi, and random regular networks, the critical point is shifted while the critical exponents remain close to the mean-field values. By contrast, Watts--Strogatz networks exhibit a much lower critical point and stronger deviations in the effective critical exponents, highlighting the role of clustering and local correlations. A rewiring analysis of Watts--Strogatz networks further shows that the ordered phase becomes more stable as the network becomes more random. These results indicate that quenched topology not only sets the transition point, but also leads to topology-dependent effective critical behavior in networks with strong clustering and local correlations.

Silicon nanospheres are high-quality optical resonators and promising building blocks for Mie-tronic devices. While the Mie resonances of an isolated sphere are well understood, practical implementations require substrates that inevitably modify the measured optical response. Here, we investigate how substrates alter the observable spectrum of individual nanospheres, focusing on three fundamentally different cases: a thin silicon nitride membrane, that emulates a free-standing particle, bulk silicon, which is common in experiments, and gold, where mirror charges lead to hybrid optical modes. Cathodoluminescence and dark-field spectroscopy, combined with electrodynamic simulations, show that the measured resonances are not intrinsic to the particle but depend strongly on the environment and the excitation mechanism. We find that substrate-induced effects and probe-specific selection rules can suppress, enhance, or even invert the spectral signatures of electric and magnetic modes. These results provide practical guidelines for interpreting and designing substrate-supported dielectric resonators for Mie-tronic applications.

The appearance of generative models has opened vast chemical spaces in the design of functional materials. Although machine learning interatomic potentials (MLIPs) have substantially accelerated phonon calculations, high-fidelity prediction of lattice thermal conductivity \k{appa}lat still requires accurate treatment of anharmonic interactions, which remains a key challenge for existing potentials across novel chemical spaces. To address this challenge, we present a comprehensive benchmark of 15 surrogate models for predicting \k{appa}lat using the Phonix database, which contains 6,966 entries with anharmonic phonon properties derived from first-principles calculations. Firstly, We categorize these surrogate models into three distinct groups: Physical-informed feature descriptors combined with ML models, end-to-end deep neural networks, and pre-trained MLIP-embeddings combined with ML models. By evaluating model performance across random, space-group disjoint (testing generalization to unseen crystal symmetries), and Out-Of-Distribution splits (OOD dataset that testing extrapolation to property regimes beyond the training range) based on \k{appa}lat, we probe both interpolation and exploration capabilities. Our results reveal that MLIP-embedded models excel in interpolation within well-sampled regions, deep neural network models especially ALiEGNN demonstrate superior robustness in OOD regimes critical for discovering novel low-\k{appa}lat. Additionally, we find a systematic degradation in performance when the structural representation is reduced. Although surrogate models exhibit lower accuracy than direct simulations using first-principles calculation, they reduce computational costs by orders of magnitude, enabling efficient high-throughput screening of thermoelectric materials with minimal loss in generative design workflows.

Cementitious materials are widely used for hazardous-waste encapsulation, yet the molecular mechanisms governing heavy-metal ion retention across different gel chemistries remain insufficiently resolved. Here, classical molecular dynamics simulations were employed to investigate the adsorption-controlled mobility of representative heavy-metal ions (Pb2+, Ba2+, and Cs+) within nanopores of C-S-H, C-(N)-A-S-H, and N-A-S-H gels. By combining pore-averaged diffusivity, spatially resolved diffusivity and residence-time analysis, ion-density profiles, two-dimensional adsorption maps, radial distribution functions, coordination analysis, and interfacial binding-strength descriptors, this study establishes a comparative atomistic framework linking gel surface chemistry to ion mobility suppression under nanoconfinement. Ion mobility is substantially reduced in all gel nanopores relative to bulk solutions, but the extent and mechanism of suppression vary strongly with gel chemistry. C-(N)-A-S-H with higher Al/Si ratios exhibits the strongest retention, driven by ion accumulation around Al-linked oxygen species via an ion-exchange-like mechanism with charge-balancing Na+. C-S-H immobilizes ions primarily through surface hydroxyl oxygens and Ca-mediated linkages, whereas N-A-S-H exhibits more distributed binding environments. Pb2+ and Ba2+ exhibit broadly similar immobilization mechanisms, whereas Cs+ shows more distinct, gel-dependent interactions with silicate and aluminosilicate oxygen sites. A relative total binding strength (rTBS) descriptor is introduced, showing a strong positive correlation with the extent of ion immobilization across gel types, ion species, and pore sizes examined. These results clarify gel-specific and ion-specific mechanisms controlling heavy-metal retention in idealized cementitious nanopores.

Developing reliable methods for certifying the dimension of a given quantum system or process is essential to ensure the validity of claimed realization of high-dimensional (HD) quantum advantages. The existing criteria for certifying genuine HD quantum teleportation (HDQT) mainly focus on demonstrating the successful transmission of genuine HD quantum states. However, a complete certification of HDQT must also identify the entanglement dimension of resource, which is critical for verifying whether the transmission capacity and noise resilience meet the necessary thresholds. Here we propose two universal criteria (based on fidelity and robustness, respectively) for certifying genuine HDQT behaviors that can close this gap by fully identifying the dimension of the entanglement. Both criteria require only the input and output teleportation data and remain feasible under partial Bell-state measurements. Furthermore, the robustness-based criterion has stronger noise resistance and it requires no prior assumptions about local operations, making it robust even in black-box scenario. Our results establish a universal and reliable theoretical framework for validating the core quantum advantage in HDQT, pivotal for ensuring the reliable links in HD quantum networks.

The Ince-Gaussian modes form a complete set of solutions to the paraxial wave equation parametrized by an ellipticity parameter ε, enabling a continuous transition between Laguerre-Gaussian and Hermite-Gaussian modes While each fixed ε defines an orthogonal basis, modes associated with different ellipticities are not mutually orthogonal, and no explicit transformation between such bases has been reported. Here, we derive the first explicit finite analytical expression to transformation between Ince-Gaussian bases of arbitrary ellipticity, enabling direct and experimentally accessible mapping between non-orthogonal structured-light representations. We further demonstrate an experimental implementation using spatial light modulators to perform ellipticity-resolved modal decomposition. This framework introduces ellipticity as a controllable degree of freedom for structured light engineering, enabling new strategiesfor mode conversion, encoding, and high-dimensional optical information processing.

The evaluation of thermoelectric conversion efficiency remains challenging owing to the lack of internationally standardized measurement protocols. Commonly used techniques -- including the heat flow, guarded heater, and AC Harman methods -- differ fundamentally in their operating principles and sensitivity to heat losses. In this study, we benchmark three module-level efficiency measurement techniques -- the heat-flow, guarded heater, and AC Harman methods -- using commercial Bi$_2$Te$_3$-based modules with different substrates materials. The conversion efficiencies obtained using the heat flow and guarded heater methods showed good agreement within experimental uncertainty for temperature differences up to 70 K. In contrast, the AC Harman method underestimated the conversion efficiency by approximately 30 %. Through systematic measurements on modules with different substrates and detailed finite element simulations, this underestimation was attributed to boundary-condition effects and radiative heat dissipation, which significantly reduce the effective temperature difference developed across the module in the Harman configuration. These results highlight the limitations of the AC Harman method for quantitative conversion-efficiency evaluation under non-ideal thermal environments and emphasize the necessity of accounting for radiative and substrate-related heat losses. Nevertheless, with appropriate modeling and correction, strategies, the AC Harman method remains a viable tool for rapid performance screening. Our results provide a quantitative benchmark of major measurement techniques and contribute to clarify best practices for module-level thermoelectric metrology and guide method selection, fully supporting future efforts toward methodological standardization.

Controlling optical chirality at the subwavelength scales is essential for many applications of nanophotonic structures in polarization optics, sensing, and nonlinear photonics. Achieving a strong chiroptical response in planar dielectric metasurfaces without intrinsically chiral building blocks (or "meta-atoms") remains challenging. The recent theoretical study [ACS Photonics 12, 6717 (2025)] predicted that bilayer metasurfaces with rotated C$_4$-symmetric apertures can exhibit pronounced chiral response originating from resonant chiral photonic modes realizing maximum chirality under the mode strong coupling. That observation uncovers a novel mechanism of metasurface chirality. Here, we confirm experimentally this novel concept and demonstrate resonantly enhanced circular dichroism in the near-infrared frequency range. We fabricate a free-standing silicon membrane metasurface that is nominally achiral. When out-of-plane symmetry is broken by a thin PMMA layer, it unlocks and activates a strong chiral response. The observed circular dichroism is explained by the properties of chiral photonic modes, and it is governed by interlayer coupling and symmetry breaking, in agreement with theoretical predictions. These results establish bilayer metasurfaces as a simple and versatile platform for engineering strong mode-induced chirality in compact planar photonic metadevices.

We have designed optical metasurfaces hosting high-quality factor quasi-bound state in the continuum (q-BIC) resonances for optical biosensing in flow. The unit cell of the metasurface contains two rectangular bars. An asymmetry factor is introduced by varying the gap width between the bars, to enable optical coupling to a q-BIC resonance confined to the air gap between neighboring nanoresonators. The location of the resonances makes them highly sensitive to changes in the local refractive index, leading to experimental bulk refractive index sensitivities exceeding 315 +/- 22 nm/RIU and a figure-of-merit of 66 +/- 5 RIU-1. Successful streptavidin-biotin binding was observed by measuring the metasurface transmission in real-time by exposing the metasurface to various concentrations of analytes via a commercial microfluidic flow cell apparatus. The experimental limit of detection, defined as 3σ above noise, was found to be 1.8x10-8 M. This platform represents a compact optical approach for point-of-care diagnostics with fast read-out.

The proposition that band geometry alone can protect optical states against disorder has proven not merely theoretically elegant but experimentally incontrovertible. A key attribute of photonic topological systems is their capacity to simultaneously possess high-intensity excitations at multiple distinct frequencies that are confined to the same topological interface. However, exploiting this freedom to protect the interaction between at least two topological states has remained an open experimental challenge. Here, we report an interaction between two topological states, with one being precisely frequency-doubled to the other, supported in a hybrid plasmonic and photonic topological insulator via nonlinear phase matching. We find that the phase matching inherits a unique spin-momentum locking unseen in conventional nonlinear systems. This ability to bring two topological states into phase-matched nonlinear interaction at a single interface sets the stage for a new class of doubly protected nonlinear photonic devices, potentially finding implications in generating entangled photon pairs with enhanced resilience and robustness for secure quantum information technology.

Conductivity models for warm dense matter inform simulations of planetary structure and fusion experiments. State-of-the-art conductivity calculations based on density functional theory approximate many-body physics and neglect electron-electron scattering lifetimes. We introduce a many-body framework for electrical conductivity using the GW approximation of the electronic self-energy. For beryllium, improved transition energies yield a surprisingly large reduction in low-temperature DC conductivity, while electron-electron scattering primarily reduces high-temperature DC conductivity.

This article analyzes the feasibility of having a second synchrotron in Latin America, to be located, in principle, in a city within the Greater Caribbean region but open to all the continent. It is shown that an initiative of this sort is compatible with the economies of the region and would require a marginal increase of the current regional investment in science, which is broadly below that of other regions of the world, with peaks of low financing precisely in the Greater Caribbean. The project is not only feasible, but, beyond its purely scientific interest. it would have an impact for the development of cities in the region. The article is mainly focused to analyze this impact from the social, economic, and political point of view. It is shown that the return of the investment would have its break-even point long before the end of the expected lifetime of the infrastructure, and that through a system of smaller accelerators, that would be part of the same project, the benefit would not concentrate on the country hosting the facility. These smaller facilities could contribute to the national development as possible nuclei of cities of knowledge, project which belongs to the priority of some countries/cities of the region.

Two-body reduced density matrices (2RDMs) encode the essential two-electron physics of electronic states, but their quartic storage cost poses a major limitation in practical workflows. We investigate a simple protocol to compress both transition and non-transition 2RDMs into a lower-rank representation that preserves their wedge-product structure and physical symmetries under truncation. The resulting decomposition couples Coulomb and exchange channels through a common set of low-rank factors, yielding a more compact rank-sparse representation than single-channel factorizations. For correlated states, the effective rank scales linearly with system size, achieving a $\sim99$\% compression for the coupled-cluster 2RDM of octane while retaining chemical accuracy. We apply this to the recently introduced {\em ab initio} eigenvector continuation workflows, where many-body wave functions are interpolated across nuclear geometries with mean-field cost. Here, 2RDMs between training states act as projectors into a subspace but their memory scaling limits applications to larger systems. The compression scheme reduces the memory cost from quartic to quadratic for a fixed error per electron. Metrics to systematically control the decomposition are investigated, enabling statistically resolved structural, dynamical and spectroscopic observables from nonadiabatic molecular dynamics simulations of photoexcited H$_{28}$ chains, interpolating from compressed near-exact DMRG training data. This establishes these structure-preserving compressed intermediates for practical correlated electronic structure workflows.

Systems close to a phase transition turn weak perturbations into large responses. At equilibrium, this amplification is closely linked to criticality: fluctuations grow, dynamics slow, and a common soft mode controls the response. Whether this correspondence survives in driven-dissipative quantum systems, sustained by continuous pumping and loss away from thermal equilibrium, remains an open question. Here we show experimentally that it does. In a room-temperature semiconductor photon Bose-Einstein condensate, the critical slowing of spontaneous intensity fluctuations and the amplification of weak pump perturbations are measured independently. Both peak at the same condensate population, $\bar{n}_c = 1250$, where the dimensionless slowing factor and susceptibility reach the same value, $\bar{n}_c/2 = 625$. A single weakly damped collective photon-reservoir mode governs both effects. This fluctuation-response correspondence in a finite open quantum gas establishes critical susceptibility as a measurable dynamical signature of condensation, with peak gain set by system size.

Regression to the Mean and Regression Dilution are often viewed as unrelated issues in the clinical and ecological literatures. In reality, they are different names for the same problem: measurement error in an independent variable that biases the perceived relationship between two factors. This study unifies these traditions by comparing specialized clinical tools, like the Berry correction, with standard structural estimators such as Major Axis and Reduced Major Axis regression. Using an analytical framework, we evaluate how these methods perform across various noise levels and sample sizes. Our results show that the Berry method is a specialized tool designed for clinical scenarios where a 1:1 relationship is expected. However, applying it to ecological trade-offs with negative slopes can lead to severe errors. We provide maps of optimality to identify which estimator most accurately recovers the true biological signal under different conditions. By reconciling these disparate methods, we offer a principled guide for researchers to choose the correct tool based on their data's noise profile rather than their disciplinary tradition.

We present the Quantum Hamiltonian Analysis Toolkit (QHAT), a newly developed application that provides a user-friendly interface for studying Hamiltonians and performing Hamiltonian simulation on fault-tolerant quantum computers. QHAT enables the generation and analysis of Hamiltonians through a powerful and feature-rich application, driven by simple inputs designed to reflect user needs rather than algorithmic details, so that productive research on your application of interest can be done without needing a deep understanding of quantum computing algorithms. QHAT enables a streamlined workflow to analyze Hamiltonians and Hamiltonian simulation, supporting multiple choices of algorithms and analyses. It supports Hamiltonians from multiple sources but can also generate Hamiltonians based on a simple description of the system, saving intermediate data files for re-use when generating related Hamiltonians. Deriving the parameters for quantum computing algorithms can be a challenge, so QHAT is built around user-facing concepts such as maximum allowable error, rather than being built around algorithmic details such as steps counts or order parameters. An emphasis on user-friendly interfaces and efficient analysis means that the barrier to entry is low while rapidly providing results useful for a broad scope of studies.

In discrete-variable black-box optimization, the number of candidate solutions grows combinatorially, while each evaluation is often expensive. Therefore, it is important to identify promising solutions efficiently within a limited number of trials. Bayesian Optimization of Combinatorial Structures (BOCS), an existing parametric method, works effectively when only a small amount of data is available. However, as the number of observations increases, BOCS tends to repeatedly propose points that have already been evaluated, which leads to search stagnation. A random-point addition strategy has been proposed to address this issue when an evaluated point is proposed, but it cannot sufficiently exploit information from promising data obtained so far. In this study, we propose a hybrid method that uses BOCS as the main search framework and generates alternative unevaluated points using a Gaussian process only when search stagnation is detected. In the Gaussian-process-based component, multiple Lower Confidence Bound (LCB) acquisition functions are adaptively selected to dynamically control the balance between exploitation and exploration. Numerical experiments using fully connected Quadratic Unconstrained Binary Optimization (QUBO) and Higher-order Unconstrained Binary Optimization (HUBO) as black-box functions show that the proposed method finds solutions with better objective values than the conventional random-point addition method in both settings. Additional analyses show that its effectiveness comes from selecting points that promote search progress within Hamming-distance neighborhoods, rather than simply adding low-energy points near promising solutions. Experiments with sparse surrogate models for quantum annealer applications further suggest the importance of retaining near-fully connected representational capacity.

We present results from the Big Mysteries Survey, a large-scale survey conducted through the American Physical Society's Physics Magazine on foundational and controversial topics in contemporary physics. The survey provides a snapshot of physicists' views on issues in cosmology, black-hole physics, quantum mechanics, quantum gravity, and anthropic coincidences. A central finding is that several positions often described publicly as field-wide ``consensus'' views are, in practice, supported by much narrower majorities or by pluralities rather than majorities.

We report on a gate-based variational quantum classifier implemented with single photons and probabilistic gates, to emulate the standard quantum circuit model framework. We evaluate the expressive power of two deployable quantum neural networks (QNNs) by computing their effective dimension, a capacity measure grounded in a proven generalization-error bound, and compare them with classical artificial neural networks (ANNs) of equivalent trainable-parameter count. Supervised binary classification tasks are used to benchmark performance across photonic and superconducting QNNs, both of which exhibit superior converged (lower) cross-entropy loss and (higher) prediction accuracy relative to matched-parameter ANNs. For a nonlinearly separable task, our photonic QNN with a single pair of trainable parameters successfully converged (loss 0.04 and accuracy 100%), whereas the equivalent ANN failed to learn the decision boundary, saturating at random-guessing performance. We simulate photonic quantum circuits, training them on the XOR problem and a two-class Iris subset using gradient-free optimization, and assess their robustness to sampling errors under realistic noise processes including photon loss and phase-shifter imperfections. Circuits with comparatively high effective dimension were deployed remotely on a six-qubit photonic quantum processor, achieving classification accuracies of up to 100% in both online and offline learning settings. Notably, even the simplest QNN deployed, with just two trainable parameters, successfully solved tasks that classically require ANNs with at least quadruple the number of parameters, suggesting an emergent algorithmic advantage. Overall, these results demonstrate a clear proof-of-principle that gate-based QNNs can be realized and trained effectively on current photonic hardware, providing proof of algorithmic advantage on a gate-based photonic QNN.

We explore Krylov complexity in the BMN matrix model following a systematic reduction of it, known as the pulsating fuzzy sphere model. We present an analytical setup that allows us to calculate Lanczos coefficients in both large and small deformation limits of the matrix model.

For more than a century, the diffraction limit has defined the resolution achievable by passive optical imaging systems. Although some resolution improvement can be gained through classical data processing of the image, it is limited by the noise arising from quantum nature of light. Minimizing the effect of this noise requires quantum treatment of optical imaging. By reformulating imaging as a problem of quantum measurement and estimation, it becomes possible to identify optimal detection strategies that recover spatial information previously thought inaccessible. This review summarizes the theoretical framework that underpins this development, from the formulation of quantum Cramér-Rao bounds and Chernoff bounds to the construction of receivers that attain them, such as those based on spatial-mode demultiplexing. We show how these methods can beat conventional imaging in the classification, localization, and imaging of sub-Rayleigh incoherent sources. We then discuss extensions to multiparameter and partially coherent scenarios, and highlight the unifying connections between estimation and discrimination tasks. Finally, we survey recent experimental demonstrations that approach quantum-limited resolution and outline emerging applications in microscopy, astronomy, and optical sensing.

This paper proposes a new integrated magnetics (IM) design for an isolated zero-voltage-switching (ZVS) Cuk converter (IZCC). In this design, six magnets are wound onto a single magnetic core, and to minimize magnetic core size and losses, both direct current (DC) and alternating current (AC) flux cancellations are considered. The DC flux is fully cancelled, and the AC flux must be cancelled until a limited value such that the input and output inductor currents have enough ripple to provide the conditions for achieving ZVS on all switches. Therefore, the value of the coupling coefficients (CC) between the windings should be considered such that the minimum ripple to achieve ZVS for all the switches is available. The design is implemented on a simple magnetic U-core, and the CC values are specified based on the winding locations and arrangement. To validate the idea experimentally, a hardware prototype is proposed with a power of 0.5 kW, a switching frequency of 150 kHz, and a peak efficiency of 97.25%.

We develop a non-perturbative description of squeezed light generation in an arbitrary lossy structure consisting of multiple coupled microring resonators. This is applied to two ring photonic molecules where the interference of the fields in the coupled rings leads to a modification in the resonance spectrum near a shared resonance. Considering a dual-pump degenerate squeezing scheme under a five resonance approximation, we investigate two methods to suppress parasitic four-wave mixing contributions and compensate for group velocity dispersion within a primary resonator through hybridization effects with a second auxiliary resonator. In the former case, this comes from an effective splitting of the unwanted resonances supporting parasitic four-wave mixing interactions that add thermal noise to the desired degenerate squeezed state. For sufficiently strong coupling between the resonators, we demonstrate near complete suppression of such parasitic processes, resulting in near unit fidelities with the corresponding output state that would arise were the parasitic interactions neglected. In the latter case, the hybridization effectively shifts a pump resonance, realigning the desired dual-pump four-wave mixing process and leading to a significant enhancement of the signal generation and output squeezing.

Most mathematical models of opinion dynamics treat attitudes as scalar quantities or positions on a low-dimensional ideological axis. Empirical attitudes, however, are bundles of positions across many policy issues, and the geometry of the resulting high-dimensional belief space is non-trivial. This paper develops a network-theoretic framework for analysing how individuals move through such a space between two measurement waves. Continuous attitude profiles in $[0,1]^n$ are discretised onto regular grids of resolution $k$, occupied positions form a network whose adjacency is defined by single-issue unit moves, and densely populated regions are interpreted as network-normative: empirically common configurations of attitudes in the population. We introduce a hierarchy of null models against which observed movement can be benchmarked: a closed-form coverage baseline requiring no behavioural parameters; a local random-walk that retains each respondent's baseline position and asks whether destinations are over-represented in occupied regions relative to a uniform 1- or 2-step move; and a marginal permutation null model that preserves per-issue change distributions while disrupting within-respondent cross-issue coupling. Applying the framework to a two-wave panel of $N=1194$ respondents on $n=10$ issues, we find that the observed inside rate exceeds the coverage baseline by a factor of 36 at the focal resolution $k=3$, exceeds the two-hop random-walk null model by $\sim 0.30$, and exceeds the perturbation null model by $\sim 0.04$; only the one-hop random walk is competitive. The perturbation gap grows from near zero at $k=2$ to $\sim 0.14$ at $k=5$, indicating that coupled cross-issue updating is detectable only at fine resolutions. Network-normative attraction is therefore real but representation-contingent: which null model is exceeded, and by how much, changes systematically with $k$.

Time-independent scattering methods are widely used to analyze transport in periodic $\mathcal{PT}$-symmetric systems. However, their predictions become unphysical when the system supports time-growing bound states (TGBSs), which manifest as $S$-matrix poles in the first quadrant of the complex wave-number plane. Here, we analytically delineate the region of physical relevance for a $\mathcal{PT}$-symmetric chain of $N$ unit cells with gain/loss strength $γ$. We derive the TGBS onset threshold $γ_c = 2\sin[π/(4N)]$, which scales as $π/(2N)$ for large $N$ and vanishes in the thermodynamic limit. Enlarging the structure thus enriches stationary scattering phenomenology but inevitably triggers TGBSs at weaker gain/loss. Time-dependent wave-packet simulations confirm this analytical boundary quantitatively. Applying this criterion, we show that many previously reported predictions of gain-loss-induced localization, reflectionless transport, and coherent perfect absorbers and lasers in large periodic structures fall outside the physically relevant regime. $S$-matrix pole analysis is therefore an indispensable prerequisite for interpreting time-independent scattering predictions in periodic non-Hermitian systems.

We develop a unified spectral-semigroup framework that connects real-time and imaginary-time quantum dynamics through analytic continuation. Within this formulation, evolution is expressed as an exponential reweighting of spectral components generated by a single operator $\mathcal{G}$, placing unitary and dissipative dynamics on equal footing within a common spectral structure. The mapping naturally induces a nonlocal fractional operator in time, giving rise to a contractive semigroup governed by a square-root spectral deformation and identifying imaginary-time evolution as an effective fractional low-pass filter. While exponential attenuation suppresses high-frequency components, the inverse transformation remains systematically controllable within a well-defined spectral window. In this regime, stable reconstruction of low-energy and coarse-grained dynamical features is achieved, establishing a predictive relation between imaginary-time evolution and recoverable information. This leads to a quantitative description of a bandwidth-resolved asymmetry between forward propagation and inverse recovery. Across systems with continuous and discrete spectra, few-level coherence, and non-Hermitian generators, we demonstrate that spectral structure governs reconstruction fidelity in a unified manner. In particular, non-Hermitian and open-system settings reveal that irreversibility emerges as a geometry- and scale-dependent feature of the spectrum, tied to both damping and eigenstate non-orthogonality. These results recast analytic continuation as a structured, scale-dependent filtering process with quantifiable and systematically accessible reconstruction limits, providing a unified perspective on the interplay between dynamics, spectral geometry, and information recovery.

The concept of metasurfaces was recently applied to the extreme ultraviolet (EUV) spectral regime, providing a new opportunity for transmissive focusing elements in a regime where materials are highly lossy. The realization of metalenses in the EUV, however, is challenging due to the optical losses and low refractive index contrast of available materials, as well as the larger-than-wavelength periodicity of metaatom arrays imposed by fabrication limits. In this paper, we propose alternative EUV metalens design strategies, including layout schemes and metaatom mapping rules. We demonstrate that the focusing efficiency can be roughly doubled compared with the simple square-lattice design of an EUV metalens purely by using an alternative semi-analytical design approach without reducing the metasurface's minimum feature size. The proposed strategies are generally applicable to metaoptics design for efficiency improvement when metaatoms are lossy or induce diffraction orders.

Reliable modeling and control of core density is essential for reactor-relevant magnetic confinement fusion operation, motivating cryogenic pellet injection as a primary fueling actuator and the need for predictive pellet source models in integrated modeling. Here we present an upgrade of the physics-based pellet code HPI2 in which the plasmoid release spatial step is determined self-consistently from ablation physics, $dx_{var}=v_{\mathrm{pel}}\,t_{\mathrm{exit}}$ (optionally rescaled to trade accuracy for computational cost), removing an ad-hoc discretization parameter and improving numerical robustness across injection conditions. The upgraded model is first validated in stand-alone against a high-field-side pellet-fueled, ohmic, WEST discharge (#58656) by comparing synthetic and measured interferometry line-integrated density increments, obtaining a mean error of $\sim 10\%$. We then perform full-radius, time-dependent integrated modeling validation by coupling the new HPI2 within the High Fidelity Pulse Simulator (HFPS) workflow (JINTRAC/IMAS), combining JETTO with SANCO for the impurity/radiation evolution and TGLF-SAT2 for the turbulent transport. The coupled simulations reproduce the main density rise and relaxation after pellet injection and the associated electron-temperature transient, while taking into account the strong influence of tungsten radiation in WEST, supporting the consistency of HPI2 as a predictive pellet particle source in integrated modeling frameworks. Ultimately, this validation study supports the use of pellet modeling tools in integrated modeling studies for larger devices such as ITER.

Understanding the molecular mechanism by which denaturants modulate protein structure remains a central challenge in protein biophysics. In this work, molecular dynamics simulations were employed to investigate the effects of urea on the structural stability of bovine serum albumin, its F isoform at pH 3.7, over a broad range of urea concentrations (0 M to a fully urea/solvated system). The results reveal that urea induces a concentration/dependent dehydration/rehydration mechanism within the protein hydration shell. At low urea concentrations, a marked reduction in protein/water hydrogen bonds is observed, accompanied by a corresponding increase in protein/urea interactions, consistent with a competitive solvation process. At higher concentrations, urea/urea self-association becomes significant, limiting direct protein/urea interactions and promoting partial rehydration of the protein surface. Despite these solvent rearrangements, the secondary structure of BSA remains largely preserved, whereas local and tertiary structural features, particularly in Domain III, exhibit increased solvent exposure and conformational flexibility. These findings support a dynamic compensation mechanism in which urea partially replaces water in the solvation shell without fully disrupting the hydrogen-bonding network. Overall, this study provides molecular-level insight into the interplay between preferential interactions, solvation dynamics, and protein stability under denaturing conditions.

Complex microbial habitats see the spatial competition of different clonal bacterial populations that switch between different phenotypes. Here, we determine the effect of this subpopulation structure on the invasion of one species by another in a minimal model of two competing species: one species switches, both stochastically and in response to its competitor, to a persister phenotype resilient to competition. Surprisingly, our combined analytical and numerical results show that this phenotypic switching has no effect on the speed of the travelling wave by which the competitors invade the first population. Conversely, we discover that phenotypic switching can speed up the wave by which this population invades their competitors. Our results thus suggest, counterintuitively, that bacterial persistence can be an offensive, rather than defensive ecological strategy.

Here we present different approaches to ultrafast pulse and polarization shaping, based on a ``quantum fluid'' platform of polaritons. Indeed we exploit the normal modes of two dimensional polariton fluids made of strong coupled quantum well excitons and microcavity photons, by rooting different polarization and topological states into their sub-picosecond Rabi oscillations. Coherent control of two resonant excitation pulses allows us to prepare the desired state of the polariton, taking benefit from its four-component features given by the combination of the two normal modes with the two degrees of polarization. An ultrafast imaging based on the digital off-axis holography technique is implemented to study the polariton complex wavefunction with time and space resolution. We show in order coherent control of the polariton state on the Bloch sphere, an ultrafast polarization sweeping of the Poincaré sphere, and the dynamical twist of full Poincaré states such as the skyrmion on the sphere itself. Finally, we realize a new kind of ultrafast swirling vortices by adding the angular momentum degree of freedom to the two-pulse scheme. These oscillating topology states are characterized by one or more inner phase singularities tubes which spirals around the axis of propagation. The mechanism is devised in the splitting of the vortex into the upper and lower polaritons, resulting in an oscillatory exchange of energy and angular momentum and in the emitted time and space structured photonic packets.

A common task in physics and astronomy is studying which of the competing hypotheses the data prefer. This is usually done by computing the Bayes factor between the two hypotheses, and either interpreting it in terms of the posterior odds or as a ranking statistic for a frequentist p-value test. Here we describe a relationship between the Bayes factor and its distributions under the two competing hypotheses, called the Bayes factor-Bayes factor (BB) relationship, expressed as a diagnostic plot. Using examples from gravitational wave (GW) astronomy, we demonstrate how the BB plot can validate the accuracy of Bayes factor calculations. The BB relationship may also be useful for estimating background distributions of the Bayes factor at low computational cost, even analytically in some cases. We apply this technique in the context of wave-optics lensing of GWs, extrapolating the background distribution from GWTC4 to put a rough bound of $\lesssim 4.1 σ$ on the statistical significance of GW231123.

We study a simple but useful test for neural exchange-correlation (XC) functionals: can a neural model reproduce an established XC functional when it is used self-consistently? We call this test functional cloning. The model is trained at the GGA level to reproduce a known semilocal functional, using either a constrained or an unconstrained architecture. The motivation is that an XC functional is not used on a fixed input. In a Kohn-Sham self-consistent-field calculation it contributes to the potential, and the resulting density is part of the outcome of the same calculation. A good pointwise fit to sampled density descriptors is therefore not by itself enough. Because the target functional is known, the error can be measured directly. We compare the clones on sampled descriptors, molecular total energies, energy differences, transfer between PySCF and SIESTA, and equations of state for crystalline solids. The constrained models reproduce the reference functional more accurately in molecular self-consistent calculations. They also give better initial parameters for later optimization against correlated molecular energies. An additional observation is that the constrained architecture already gives a reasonable solid-state baseline before cloning, as seen from randomly initialized constrained models. Clones trained only on molecular densities transfer well to solids, reproducing reference lattice constants and bulk moduli across metallic, covalent, ionic, oxide, and layered systems. Cross-code tests show that energy differences are relatively robust, while total energies depend strongly on whether the cloning descriptors come from all-electron or pseudopotential densities. These results make functional cloning a useful diagnostic before full self-consistent training of neural XC functionals.

A fundamental symmetry of the non-Hermitian operators describing wave-propagation in time-varying media imbue such systems with non-trivial topology. This topology may be measured directly in a wide range of experimental settings as a quantised real part of the Berry phase, contrasting unconstrained geometric gain or loss. This topological index is provided explicitly for practical examples, including a non-Hermitian analogue of the Su-Schrieffer-Heeger model.

Dynamic atom gravimeters enable absolute gravity measurements on moving platforms. However, their performance is severely degraded due to the complex dynamic environment. This paper finds that the amplitude modulation noise (AMN) is a key factor contributing to the degradation of gravity measurement performance. We find that the AMN is induced by the cold atomic cloud trajectory and velocity variation. We build a model to illustrate the principles and magnitude of AMN arising from various experiment processes. Then we propose a method to fit the normalized AMN respect to the kinematic parameters of the cold atomic cloud, and successfully suppress this noise from 0.11 to 0.038 using the fitting result. With this method, we improve the fringe phase resolution from 0.244 rad to 0.092 rad, and reduce the dynamic gravity measurement noise from 2.69 mGal to 1.68 mGal. This study finds and suppresses a key noise source for the dynamic atom gravimeters, which is important for further improving its precision. The proposed method can be also applied for precision enhancement for other dynamic atom interferometer-based sensors, such as the atom gradiometers and gyroscopes.

Optical skyrmions offer a robust vectorial information degree of freedom for free-space communication, but practical deployment requires a compact platform capable of active topological reconfiguration. Here, we propose a silicon microring-resonator optical phased array that integrates spin-selective emission and programmable phase control on a single chip. Optimized inner- and outer-grating microring emitters provide decoupled LCP and RCP radiation bases with polarization fractions of 90.27% and 91.40%, enabling active switching between Néel-type and Bloch-type skyrmions, while dynamically tuning the skyrmion number across Nsk =-1.914 to 1.918. Using these programmable topological states, a 4-symbol free-space communication link is constructed and compared with ideal LG-OAM encoding under Kolmogorov turbulence. The skyrmion-encoded link maintains a lower symbol error rate over a broader turbulence range, demonstrating that topological observables are more robust than scalar OAM modes. These results establish actively reconfigurable optical skyrmions as compact, programmable, and turbulence-tolerant information carriers for next-generation free-space optical communication.

A thermally tunable extraordinary terahertz transmission in a hybrid metal-vanadium dioxide (VO2) metasurface is numerically demonstrated. The metasurface consists of a metal sheet perforated by square loops while the loops are connected with strips of VO2. The frequency and amplitude of the transmission resonance are modulated by controlling the conductivity of the VO2. For y-polarized incident field, the resonance transmission peak redshifts from 0.88 to 0.81 THz upon insulator-to-metallic phase transition of VO2. For x-polarized incident field, the transmission resonance at 0.81 THz is observed in the insulator phase. However, in the metallic phase of VO2, the electromagnetic field is effectively reflected in the 0.5-1.1 THz range with a transmission level lower than 0.14. The proposed metasurface can be utilized as a terahertz modulator, reconfigurable filter, or switch.

Test-mass thermal noise is a limiting noise source for current and next-generation ground-based gravitational-wave observatories. Uniform-intensity higher-order laser beams, including Laguerre-Gaussian (LG) and Hermite-Gaussian (HG) modes, have been proposed as alternatives to the fundamental Gaussian beam due to their thermal-noise advantages. As interferometer power increases toward the megawatt regime, thermal aberrations from absorption in the test-mass coatings become increasingly significant. In this work, we quantify the robustness of higher-order modes against absorption-induced thermal deformation. We show that, under identical operating conditions, higher-order modes produce substantially more uniform thermal distortions than the fundamental mode, requiring significantly less thermal compensation power. The optimal curvature correction is reduced to 33% for the LG$_{2,2}$ mode and 24% for the HG$_{3,3}$ mode relative to the fundamental mode. We further show that the residual thermal deformation of higher-order modes results in lower optical loss, larger cavity power buildup, and improved modal purity in an aLIGO-like cavity. In addition, astigmatism compensation further enhances the intracavity purity of HG modes under self-heating-induced deformation. These results demonstrate that higher-order modes not only mitigate thermal noise but also intrinsically reduce beam self-heating effects, making them promising candidates for future high-power gravitational-wave interferometers.

Manifold-based combustion models decrease the cost of turbulent combustion simulations by projecting the thermochemical state onto a lower-dimensional manifold, allowing the thermochemical state to be computed separately from the flow solver. The solutions to the manifold equations have traditionally been precomputed and pretabulated, but this results in large memory requirements and significant precomputation cost even for simple models. One approach to alleviate the memory requirements is to use In-Situ Adaptive Manifolds (ISAM), which only stores solutions that are encountered during a simulation in a database built with In-Situ Adaptive Tabulation (ISAT). Even with ISAM, as the manifold complexity increases, the memory requirements can still grow too large. Another approach to reduce memory of these databases are machine learning methods, for they represent functions in a highly memory-compact manner. However, current implementations of these methods require the pregeneration of training datasets with little knowledge of the states present in a simulation. This work develops the Neural In-Situ Adaptive Manifolds (Neural-ISAM) method, which is designed to address the drawbacks of both adaptive tabulation and machine learning methods, and leverage their benefits by coupling neural networks to manifold databases on-the-fly. ISAM databases are built via ISAT, which stores the manifold solutions in a binary tree, and Neural-ISAM periodically searches this tree to identify regions that can be pruned. Neural networks are trained on the candidate regions, and these portions of the binary tree are then replaced by the trained neural network, reducing the memory requirements of the database. Neural-ISAM memory usage, computational performance, and accuracy is evaluated in LES of two turbulent flames with increasing manifold model complexity: Sandia Flame D and the Sandia Sooting flame.

The Cold-Neutron Inelastic Spectrometer (CNIS) is a direct-geometry, time-of-flight instrument designed for China Spallation Neutron Source (CSNS) and optimized to probe low-energy lattice and magnetic excitations. The instrument integrates a long flight path with bent supermirror guides and an elliptical-focusing geometry to suppress high-energy background while improving cold-neutron delivery to the sample. A flexible multi-disk chopper suite provides pulse shaping, band selection and monochromatization, enabling multi-$E_\textrm{i}$ operation. Modular features, including an interchangeable high-focusing guide insert, radial collimation and a vacuum ``airbox'' for simplified sample-environment integration, enhance signal-to-noise and operational versatility. Through combined flight-path and chopper optimization, CNIS achieves excellent routine-mode energy resolution and can reach approximately $\sim 1\%$ in a dedicated high-resolution configuration. CNIS is planned to commence user operation in 2029, offering a highly flexible platform for cold-neutron inelastic scattering studies.

We introduce an $O(M)$ algorithm for evaluating the azimuthal Fourier modes $G_{k,m}$, $m = 0, 1, ..., M$, of the three-dimensional Helmholtz Green's function with real wavenumber $k$, together with all their first- and second-order derivatives with respect to the cylindrical source and target coordinates. The cost is independent of both the wavenumber and the source-target separation, and high relative accuracy is retained even for modes whose magnitude is exponentially small. The method combines contour deformation at a few boundary modes with a boundary-value formulation of the five-term recurrence in the mode index. Derivative quantities are obtained from stable recurrences, adding only a small constant factor to the cost of $G_{k,m}$ alone. Numerical experiments demonstrate high relative accuracy, linear scaling in $M$, and applications to modal boundary integral equation solvers for axisymmetric acoustic scattering, where the $k$-independent kernel evaluator makes dense per-mode linear algebra the dominant cost.

The rapid advancement of Large Language Models has transformed scientific research workflows, including enabling the automated extraction of data directly from published literature. Most existing efforts, however, focus on extracting simple labeled key-value entities, whereas many scientific applications require more complex, hierarchically structured data. A representative example is Quantum Cascade Lasers, whose device architectures are defined by tens of interdependent parameters organized in nested layer sequences. In this work we propose a \emph{JSON-Schema Guided Information Extraction Pipeline} (JSG-IE) that enables reliable extraction of deeply structured device data without model fine-tuning. By transforming extraction into a schema-constrained generation task, our approach significantly improves structural consistency and accuracy. Across 12 state-of-the-art LLMs, a properly designed JSON Schema improves performance by 5.7\% over conventional prompting, with the highest $F_1$ score up to 83.4\%, achieved by the reasoning-enabled Kimi-k2-thinking model. Importantly, this performance enhancement is most significant for mid-tier and open-source models, where $F_1$ gains reach as high as 24.1\%, effectively enabling these widely accessible models to achieve extraction fidelity previously restricted to much larger architectures. This framework provides a scalable path toward automated construction of high-fidelity device databases, accelerating data-driven optoelectronic design.

Sensing weak forces through observing a mechanical motion near or below its quantum zero-point fluctuation has been desired in diverse areas. While mechanical oscillators have played a crucial role in such studies, their application to free-fall-type sensing has been elusive, in particular in the quantum regime. Here, we demonstrate sensing a static force of the order of 10 zeptonewtons with a levitated nanomechanical oscillator below the zero-point fluctuation through the rapid modulation of its confining potential. We prepare a squeezed state with a reduced velocity uncertainty by abruptly decreasing the potential. Subsequently, we detect the exerted static force through time-of-flight measurements, where we release the nanoparticle from the potential and measure the displacement during a free fall. Furthermore, time-of-flight measurements allow us to perform quantum state tomography of the squeezed state, from which we reconstruct its Wigner quasiprobability distribution and evaluate the Fisher information for the position measurement to quantify the achievable force sensitivity of our protocol. Our results demonstrate that modulating the trap stiffness serves as a crucial technique for quantum-limited force sensing and paves the way to utilize a levitated nanoparticle as a promising sensing platform beyond the quantum limit with a capability of quantum state tomography.

We present a non-destructive, spatially resolved thickness characterization method for rhombohedral (3R) molybdenum disulfide (MoS$_2$) on polydimethylsiloxane (PDMS) substrates. Unlike broadband spectroscopic approaches, the proposed method reduces the measurement to a small number of discrete intensity images, enabling direct thickness mapping with a conventional microscope architecture and commercially available bandpass filters. Our approach combines a systematic framework for selecting optimal discrete wavelength samples of the material's reflectance with a robust thickness retrieval algorithm based on a multivariate Gaussian probability model. By sampling the reflectance with just five strategically chosen near-infrared bandpass filters, we demonstrate thickness characterization up to 691 nm with a mean 95% confidence-interval width of 8.3 nm. The method is adaptable to other van der Waals materials and conventional optical thin-film systems. It therefore provides a foundation for scalable, real-time thickness characterization in, e.g., dry-transfer fabrication workflows, where thickness screening remains a critical bottleneck for the production of van der Waals heterostructure devices.

Decision-making by imitating the highest earners has been observed in experimental studies. In two-strategy decision-making problems, this behavior may result in perpetual fluctuations in the population proportions of the two strategies. How these fluctuations evolve for large population sizes remains unclear. This paper addresses this question for a heterogeneous population of players imitating the highest earners. We show that the family of Markov chains describing the discrete population dynamics forms a generalized stochastic approximation process for a good upper semicontinuous differential inclusion--the mean dynamics. Furthermore, we prove that the mean dynamics always equilibrate. Then, by using results from stochastic approximation theory, we show that the amplitudes of fluctuations in the population proportions of the two strategies diminish to zero with probability one, as the population size approaches infinity. Our results suggest that in a well-mixed, large population, imitating the highest earners is unlikely to generate large-scale, perpetual fluctuations.

High brightness and low coherence laser sources with wideband tunability are essential for many full-field imaging applications aiming for high contrast and speckle free performance. However, this combination of parameters is challenging to achieve. The current solutions focus on decreasing spatial coherence or generation of time-varying speckle patterns, while suppression of temporal coherence typically compromises brightness. Here we demonstrate a wideband pulsed laser source with low temporal coherence and the absence of phase correlation between pulses as an alternative approach with simultaneous time and frequency diversity. The full gain spectrum of a Tm doped fiber laser (1650 nm 2000 nm) is operated in a tunable noise like pulse regime, which by nature is composed of countless structured elementary events with uncorrelated phases randomly varying from bunch to bunch. The measured spectral widths range from 13.8 nm to 18.8 nm, while the average output power varies between 63.3 mW and 213 mW. Numerical simulations reveal that temporal coherence decreases significantly with increasing optical gain, dropping from near unity at low gain to approximately 0.2 at high gain. The startup dynamics of the noise like pulse laser are experimentally studied using the dispersive Fourier transformation (DFT) method. Based on single shot spectra and frequency resolved optical gating traces, the coherence properties of the laser are further analyzed by calculating the mutual coherence function and cross-spectral density. The noise like pulse laser exhibits a coherence time of approximately 100 fs and an average pulse burst duration of about 40 ps in the high-gain regime.

Optical fiber multi parameter sensing is fundamentally constrained by cross-sensitivity and the complexity of multi sensor integration. Here, we present a dual-dip heterogeneous long-period fiber grating (LPFG) sensing platform enabled by bending assisted annealing, which introduces anisotropic refractive index redistribution and mode dependent coupling enhancement. This process yields enhanced sensitivity, improved dip contrast, and opposite spectral responses between dual resonance dips, providing intrinsic spectral heterogeneity. To overcome temperature cross sensitivity, a polymer-encapsulated cascaded LPFG-FBG architecture is developed, where the LPFG serves as the microbending sensitive element and the FBG acts as a reference channel. PDMS encapsulation enhances stress transfer and suppresses interfacial slippage, improving linearity and repeatability. As a result, the bending sensitivity increases from -3.44 to -8.97 nm per cm, and the detection limit improves from 0.017 to 0.006 cm. Building on this, a multi parameter sensing paradigm is established by integrating dual dip heterogeneity with LPFGFBG spectral orthogonality. With PAAm functionalization, the platform enables simultaneous and decoupled sensing of temperature, bending, and humidity, demonstrating scalable and versatile multi parameter capability. Overall, this work establishes a minimalistic yet robust paradigm for multi-parameter fiber-optic sensing, offering a scalable strategy for high-performance sensing in structural health monitoring and harsh environments.

Symmetry strongly impacts wave transport in complex media. In this Letter, we demonstrate that the phenomenon of symmetry-induced through-barrier transmission enhancement enables quantitative sensing across barriers in complex media. We consider two mirror-symmetric chaotic cavities coupled through a narrow slit and containing point scatterers at mirror-symmetric positions. The characteristics of the scatterers in one cavity are unknown, whereas those of the scatterers in the other cavity are programmable. By tuning the programmable scatterers to maximize broadband total transmission, we recover the unknown scatterers' characteristics across the barrier. We show that reliable sensing requires a sufficiently large bandwidth, because otherwise a narrowband asymmetric resonant enhancement can dominate over the desired symmetry-induced enhancement. We further examine how absorption and barrier opacity influence the minimum required bandwidth. Our results establish a symmetry-empowered principle for through-barrier sensing in complex media, suggesting a route toward through-wall imaging in complex environments.

This paper expands on the TRANSP description given in Computer Physics Communications 312 (2025) 109611 by describing recent progress in TRANSP's predictive functionality and emphasizing the development of the PT_SOLVER module and integration of the high-fidelity T3D/GX framework for plasma profile prediction using a high-fidelity gyrokinetic model for turbulent transport. PT_SOLVER is a modular, multi-region, parallel solver for coupled transport equations of particle density, electron and ion energy, and toroidal angular momentum that uses an implicit Newton method to advance the solution of these equations. The numerical formulation includes source coupling, moving-geometry terms, and nonlinear stabilization based on modified Peclet numbers, thereby enabling the PT_SOLVER to handle the stiffness associated with gradient-dependent transport models. Stabilization occurs via a nonlinear function controlling discretization in zones of steep gradients or rapidly changing transport coefficients. Source terms that account for heating, current drive, alpha-particle effects, and collisional energy exchange are handled thoroughly, and both residual norms and profile-change measures are used to assess convergence. Verification is carried out using analytical benchmark solutions, manufactured solution benchmarks, convergence studies of stiff gradient-dependent diffusivities, and code-to-code comparisons of TGYRO using the TGLF/NEO models for anomalous and neoclassical transport. This paper also describes the TRANSP Interface to the modular T3D/GX workflow and presents verification examples related to the interface for coupled prediction simulations. The results in this paper confirm that the predictive TRANSP framework has a robust numerical implementation for time-dependent predictive transport simulations, and it provides a basis for future hybrid reduced and high-fidelity workflows.

Multi-nucleated cells exist in all domains of life, ranging from animals, plants and fungi to single-celled organisms such as the slime mold Physarum polycephalum. The large cell size, in the case of Physarum reaching centimeters and more, challenges the coordination of nuclei activity as signals need to cross large distances. In search for a mechanism for fast long-ranged communication among nuclei, we quantify nuclei dynamics and cytoplasmic flows in Physarum's tubular network. We observe nuclei in two interchangeable, dynamic states: mobile, flowing within the cytoplasmic shuttle flow, or trapped in the tube's porous cell cortex. As we find nuclei to accumulate at the tube's inner fluid-porous interface we theoretically explore and confirm, with physiological parameters, that slowing down of mobile nuclei during flow is sufficient for diffusible signal exchange between mobile and trapped nuclei. We analytically derive that communication akin to pigeon-post with mobile nuclei serving as pigeons shuttling between trapped nuclei acting as waypoints, gives rise to signaling velocities that account for the rapid intracellular reorganization observed in Physarum. Since signal transfer by flow-transported nuclei outcompetes the mere diffusion of signals encoded in cytosolic proteins, pigeon-post communication surpasses alternative signaling mechanisms, even diffusive relay signaling up to twenty-fold in velocity. The key ingredients of pigeon-post communication, namely alternating flows and waypoints, exist in other multi-nucleated cells and may also be generalized beyond intracellular signaling.

Intracardiac flow patterns are shaped by the coupled motion of the cardiac chambers and heart valves and provide important information about cardiac function. However, clinical flow imaging remains limited by exam times, noise, resolution, and incomplete details of the three-dimensional flow. Computational fluid dynamics (CFD) can potentially provide detailed flow quantification and predictive insight into treatment outcomes, but clinical translation requires frameworks that reproduce patient-specific measurements while balancing physiological realism, computational cost, and modeling effort. Herein, we present an image-based, patient-specific computational framework for simulating whole-heart intracardiac hemodynamics that balances physiological fidelity with computational efficiency. The framework first employs machine learning-based segmentation and mesh propagation to reconstruct moving cardiac anatomies from time-resolved images. CFD simulations are then performed to resolve blood flow in deforming domains, while resistive immersed surfaces (RIS) are used to model all four cardiac valves with physiologically realistic opening and closing dynamics. The framework was applied to model hemodynamics in a healthy adult and a pediatric patient with complex congenital heart disease (CHD). In the healthy case, the simulations reproduced physiologic pressure-volume behavior, valve timing, and ventricular vortex formation. In the CHD case, simulated chamber and vessel pressures showed agreement with cardiac catheterization measurements. Simulated flow fields were qualitatively consistent with 4D-Flow MRI, while providing higher-resolution visualization of flow structures that were partially obscured by imaging artifacts. Comparison between the healthy and CHD cases further revealed altered diastolic flow organization and elevated normalized viscous dissipation in the CHD heart.

Artificial intelligence (AI) is reshaping education, scientific training, and materials discovery. In materials science, AI models increasingly support property prediction, experiment prioritization, and hypothesis generation; however, the limiting factor is no longer only algorithmic capability but also whether students and educators can use AI with domain-specific scientific judgment. This workshop-informed white paper and curriculum-oriented position article argues that AI education for AI-powered materials discovery must move beyond tool access and surface-level interaction with generative AI systems toward a workflow-aligned model of AI literacy. We connect AI literacy to materials-informatics competencies: data provenance, domain-specific featurization, model validation, uncertainty quantification, physics informed reasoning, reproducibility, and experimental feedback. We also emphasize outcome-oriented equity: institutions should evaluate not only access, participation, and engagement, but also whether AI-enabled instruction produces comparable learning gains, transfer of learning, confidence calibration, defined as the alignment with students confidence and the quality or correctness of their work, persistence, and research readiness across student subgroups. The paper synthesizes relevant evidence, identifies risks for learners such as cognitive off-loading and cognitive surrender, and provides a dual-track curriculum model and implementation recommendations such as curriculum guides and an assessment plan for courses, bootcamps, workshops, and program-level reform. The central goal is to prepare students to become better scientists, not merely more efficient users of AI tools.

The manuscript considers Scanning Transmission Electron Microscopy (STEM) images and derives transformations needed to correct various distortions occurring during scanning. These transformations form the basis for the correction algorithms implemented in the CEOS Panta Rhei and TEMDM software. The manuscript is intended as a technical reference and is meant to be published only on arXiv rather than in peer-reviewed journals.

Strong atom-photon interactions on scalable photonic platforms hold significant potential for both atomic and photonic quantum information platforms. In particular, trapping of a single atom on a planar photonic integrated resonator at the subwavelength distances required for strong coupling to the guided modes has remained an outstanding challenge. Here we demonstrate efficient trapping of a single ultracold rubidium atom within the evanescent field of an integrated silicon-nitride microring resonator, at distances of 150-200 nm from the chip surface. Efficient, single-stroke loading process is achieved using an evanescent-field mechanism related to Sisyphus cooling, in which a single scattering event dissipates the atom's kinetic energy and transfers it into a near-surface trap. We observe logarithmic scaling of trapping durations spanning from sub-millisecond timescales up to 1 second, without continuous cooling. The trapped atom couples efficiently to the resonator, enabling on-chip photon collection, photon antibunching, and Purcell-enhanced spontaneous emission with single-atom cooperativity exceeding unity. Our results establish the potential of CMOS-compatible chip-based atom-photon interfaces for scalable quantum photonic circuits.

We propose a time-domain boundary integral method to model linear wave propagation with refractive, focusing, and Doppler effects arising from medium heterogeneities and moving obstacles. In contrast to existing techniques, our method avoids volumetric discretization and yields a formulation posed only on the boundary of the obstacle. We combine two classical ingredients: a geometric--optics parametrix to capture leading-order behavior at propagating wavefronts, and a ray-based characterization of the distorted causal geometry. The former provides a framework for defining layer potentials and deriving the associated boundary integral equations, while the latter enables a pure boundary-only formulation. Taken together, these ingredients extend existing numerical techniques for the homogeneous, fixed-boundary case to the heterogeneous, moving-boundary setting, with appropriate modifications to capture the discrete causal structure arising from the intersection of distorted light cones with the worldsheet of the moving boundary. Numerical experiments demonstrate the ability of the method to resolve Doppler effects from moving obstacles, including a rotating turbine configuration, with stable performance up to Mach 0.9. In heterogeneous media, the method captures strong refractive effects from spherical inclusions: wave propagation wrapping around a gas bubble in water, and defocusing from a hot fireball rising through a stratified atmosphere.

We present a systematic accuracy assessment of the thin-element approximation (TEA), the beam propagation method (BPM), and the wave propagation method (WPM) for binary diffractive gratings, using the rigorous Fourier modal method (FMM) as a reference. Random binary gratings are generated over a range of spatial frequency cutoffs and thicknesses, and the transmitted field overlap between each scalar method and the reference is measured. The results are summarized as accuracy maps in the spatial frequency-thickness parameter space, revealing the domain of validity of each method and providing practical guidelines for the choice of forward model in diffractive optics inverse design pipelines.

Discovering governing equations from data is crucial for understanding complex systems in many diverse fields from science to engineering. Yet, there still is a lack of versatile computational toolbox to deal with this long standing challenge due to the inherent non-autonomicity and unknowability of the underlying dynamics. Here, we introduce a data-driven approach for inferring non-autonomous dynamical equations by identifying an optimal set of basis functions within the model space, enabling the reconstruction of complex systems behavior under simplified prior specifications. Our method demonstrates effectiveness in equation discovery on canonical synthetic systems such as cusp bifurcation and coupled Kuramoto oscillators. Furthermore, we extend the application of this approach to leaf cellular energy, unmanned aerial vehicle navigation, chick-heart aggregates, and marine fish community under simple basis function libraries. Leveraging the inferred equations, we accurately predict the evolution of these empirical systems and further uncover their governing laws. Our approach offers a novel paradigm to reveal the underlying dynamics of a wide range of real-world systems.

Tunable bound states in the continuum (BICs) in metasurfaces offer powerful opportunities to control light-matter interactions, yet the role of out-of-plane symmetry breaking remains poorly understood. Here, we reveal a mechanism that enables tunable high-Q BICs and directional radiation through out-of-plane symmetry breaking in all-dielectric metasurfaces. A substrate-free metasurface composed of periodically arranged multilayer cylinders that support overlapping magnetic dipole and electric quadrupole resonances, yielding electric mirror and symmetry-protected BIC responses at 1550 nm. Introducing multilayer substrates breaks out-of-plane symmetry and excites guided modes. When the guided-mode wavelength matches that of the BIC and coupling to the substrate is suppressed, the BIC wavelength remains nearly invariant, while the Q factor increases with layer number. In contrast, spectral detuning and enhanced coupling lead to pronounced blueshifts and rapid Q degradation. The interplay between guided-mode matching and coupling strength thus governs whether a BIC remains robust or becomes tunable. These findings establish a general framework for BIC engineering via out-of-plane symmetry breaking and provide a versatile platform for tunable metasurfaces with potential applications in integrated optics.

The calibration of discrete element method (DEM) models is commonly performed by tuning model parameters to match an experimental measurements, most commonly the angle of repose (AOR). Although widely used, AOR-based calibration metrics do not adequately characterize the full heap morphology, particularly when dealing with cohesive granular materials. As a result, AOR-based calibrations often leads to non-unique parameter sets. In this work, we propose a DEM calibration procedure based on full-field image analysis of static powder heaps rather than scalar AOR measurements. The method compares an average experimental heap profile (AEHP), obtained from repeated GranuHeap experiments, with an average numerical heap profile (ANHP) generated from DEM simulations. This comparison is performed using pixel-wise grayscale intensity values of both average heap profiles. Two metal powders commonly used in additive manufacturing, Ti6Al4V and Al6061, are used to evaluate the proposed methodology. This work highlights the limitations of traditional AOR-based approaches and demonstrates that full-field heap morphology offers a more reliable framework for DEM calibration.

Noise is a significant challenge in imaging. Conventional intensity-based techniques mitigate noise through various filtering methods, but they often require prior knowledge of noise characteristics and struggle, especially under low-light conditions and with spatially structured noise. Quantum distillation provides enhanced noise rejection; however, its applicability is limited as it requires specialised illumination and substantial modifications to existing imaging setups. In this article, we introduce a coherence-based image distillation approach that separates object from noise by leveraging the difference in their temporal coherence properties. We implement this through our interferometric protocol, which enables imaging based on spatial coherence while simultaneously filtering out noise via temporal coherence. This overcomes the limitations of both intensity-based and quantum distillation methods. We experimentally demonstrate noise resilience by successfully recovering feature-rich objects, such as QR codes and grayscale wheels, obscured by spatially uniform and structured noise 20 times as intense as the object. We further show that our method remains effective for fields with substantial spectral overlap, outperforming spectral filtering in regimes where the latter provides little noise suppression. This approach provides a robust framework for noise-resilient imaging with applications in optical communication, fluorescence microscopy, and biological imaging at both high and low light levels.

This work introduces an end-to-end framework for inverse design of elastic networks directly in the space of constitutive behaviors. A constitutive prior is constructed from noisy stress-strain data using a latent representation that defines a manifold of admissible material laws while enforcing thermodynamic consistency. The inverse problem is formulated as a PDE-constrained optimization problem over latent constitutive variables that parameterize spatially varying material behavior. To improve robustness in the resulting nonconvex optimization, a homotopy-based continuation strategy is introduced using intermediate target point clouds generated through affine registration. Geometry matching is performed using the Chamfer distance, enabling optimization without requiring mesh correspondence between the target and reference configurations. To account for manufacturing constraints limiting abrupt spatial variation in material properties, the framework additionally incorporates a neural-network-based smoothness prior together with a graph-based smoothness metric. The proposed approach is demonstrated on several inverse design problems for elastic networks and compared against alternative optimization strategies.

This paper presents a method for estimating the resolution of a digital holographic microscope using neural network analysis of reconstructed images. The spectral bandwidth of the source ($Δλ$) is used as a controlled image degradation parameter. Numerical simulations were performed within inline Gabor holography. A dataset of reconstructed images was generated for several test objects over a $Δλ$ range from 0.05 to 20 nm. The model predicts $Δλ$ from reconstructed images with high precision. The predictions are consistent with standard resolution metrics, including FWHM, MTF, and the USAF resolution criterion. The generalization analysis shows that the model is sensitive to the type of degradation. It captures interferometric distortions and responds selectively to the underlying physical mechanism. The proposed approach enables resolution estimation without explicit modeling of all degradation factors and can be applied to compact holographic systems.

From subcellular structures to entire organisms, many natural systems generate complex organisation through self-organisation: local interactions that collectively give rise to global structure without any blueprint of the outcome. Yet a significant portion of the information driving such processes is not produced by self-organisation itself, instead, it is often offloaded to initial conditions of the system. Biological development is a prime example, where maternal pre-patterns encode positional and symmetry-breaking information that scaffolds the self-organising process. From maternal morphogen gradients in early embryogenesis to tissue-level morphogenetic pre-patterns guiding organ formation, this transfer of information to initial conditions, analogous to a memory-compute trade-off in computational systems, is a fundamental part of developmental processes. In this work, we study this offloading phenomenon by introducing a model that jointly learns both the self-organisation rules and the pre-patterns, allowing their interplay to be varied and measured under controlled conditions: a Neural Cellular Automaton (NCA) paired with a learned coordinate-based pattern generator (SIREN), both trained simultaneously to generate a set of patterns. We provide information-theoretic analyses of how information is distributed between pre-patterns and the self-organising process, and show that jointly learning both components yields improvements in robustness, encoding capacity, and symmetry breaking over purely self-organising alternatives. Our analysis further suggests that effective pre-patterns do not simply approximate their targets; rather, they bias the developmental dynamics in ways that facilitate convergence, pointing to a non-trivial relationship between the structure of initial conditions and the dynamics of self-organisation.

Spike activity has been the dominant neural signal for behavior decoding due to its high spatial and temporal resolution. However, as brain-computer interfaces (BCIs) move toward high channel counts and wireless operation, the high sampling frequency of spike signals becomes a bottleneck due to high power and bandwidth requirements. Local field potentials (LFPs) represent a different spatial-temporal scale of brain activity compared to spikes, offering key advantages including improved long-term stability, reduced energy consumption, and lower bandwidth requirement. Despite these benefits, LFP-based decoding models typically show reduced accuracy and often rely on non-causal architectures that are unsuitable for real-time deployment. To address these challenges, we propose REALM: a retrospective distillation framework that enables causal LFP decoding. Inspired by offline-to-online distillation strategies in speech recognition, REALM transfers representational knowledge from a pretrained multi-session bidirectional LFP model to a causal version for real-time deployment. We first pretrain a bidirectional Mamba-2 teacher model using a masked autoencoding objective. We then distill this teacher model into a compact student model via a combined objective of representation alignment and task supervision. REALM consistently outperforms both causal and non-causal LFP-based SOTA methods for behavior decoding. Notably, our REALM improves decoding performance while achieving a $2\times$ reduction in parameter count and a $10\times$ reduction in training time. These results demonstrate that retrospective distillation effectively bridges the gap between offline and real-time neural decoding. REALM shows that LFP-only models can achieve competitive decoding performance without reliance on spike signals, offering a practical and scalable alternative for next-generation wireless implantable BCIs.

Genome-scale metabolic models (GEMs) are essential tools for systems biology and rational chassis design, but conventional top-down reconstruction depends heavily on sequence homology and often leaves unknown enzymes and metabolic dark matter unresolved. Direct reconstruction from metabolomics is also difficult because mapping observed metabolites to reactions is an ill-posed inverse problem with combinatorial ambiguity and possible spurious networks. Here we present MetaGEM, a bottom-up framework that uses enzymes as physical anchors to convert system-level network inference into enzyme-metabolite interaction prediction. MetaGEM uses a multimodal dual-tower architecture that combines protein evolutionary semantics from a protein language model with three-dimensional metabolite representations. It further introduces contrastive learning with hard negative mining to separate structurally similar metabolites and reduce false positive interactions. On a de-homologized benchmark, MetaGEM achieves state-of-the-art enzyme-metabolite prediction performance, with AUROC of 0.9701 and MCC of 0.8033, and remains robust under low sequence identity splits. In downstream reconstruction, MetaGEM generates functional genome-scale metabolic models for Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. The reconstructed models improve network connectivity, capture promiscuous enzymes, and show strong agreement with experimental phenotype microarray and gene essentiality data. These results indicate that MetaGEM provides a practical route from metabolomic evidence to computable metabolic networks and offers a foundation for automated AI-driven virtual cell reconstruction.

A sufficiently large information flux in recurrent neural networks, quantified by the mutual information between successive network states, is considered a prerequisite for rich information processing capabilities. This raises the question of whether biological neural networks, such as cortical microcolumns, may be structurally organized to enhance information flux. To investigate this possibility, we study a simplified model of the cortical layer 5 architecture, in which a densely and strongly interconnected core population is embedded within a larger supporting network. Surprisingly, we find that the embedding network exerts a pronounced flux-enhancing effect on the core dynamics. Systematic reverse-engineering analyses reveal that the embedding network provides two key contributions: first, it generates effective biases that shift core neurons into a higher-entropy operating regime; second, it supplies stochastic fluctuations that prevent the network from becoming trapped in simple fixed-point or oscillatory attractors through the mechanism of Recurrence Resonance. We further show that the information flux can be increased even beyond the biologically embedded case by applying individually optimized biases to the core neurons, and that these biases can emerge from a simple self-organization principle. Our findings are relevant both for the functional interpretation of biological neural circuits and for the design of artificial recurrent systems such as reservoir computers.

DNA methylation is usually treated as an epigenetic memory mark: transcriptional history is written into regulatory DNA and later stabilizes a chosen cell identity. This picture explains persistence, but it makes memory passive. Here we show that the same promoter-level coupling required for methylation memory can instead turn methylation into an internal control variable for regulatory dynamics. Transcription-factor occupancy protects regulatory DNA from methylation, while methylation shifts later transcription-factor binding thresholds. Under time-scale separation, this reciprocal loop separates into fast expression dynamics conditioned on methylation and a slow methylation flow written by expression. Minimal promoter, self-activation, and fate-toggle models show that this feedback does more than preserve a past state: it autonomously reshapes the expression landscape. In a methylation-coupled toggle, the preferred expression state can move continuously through single-well drift, allowing commitment without first entering a multiwell regime. Stochastic simulations further show that evolving methylation reduces fate reversals relative to a frozen landscape, making weak early expression bias more predictive of later fate. These results recast DNA methylation from a downstream stabilizer of cell identity into a slow dynamical coordinate that can help determine how regulatory states are chosen.

Although recurrent neural networks (RNNs) trained on cognitive tasks have become a widely used framework for studying neural computation, the internal mechanisms by which RNNs switch between rhythms across multiple frequency bands, and how these mechanisms relate to neuronal time constants, have not been systematically analyzed. We trained leaky integrator RNNs with neuron-specific learnable time constants on a four-band (theta, alpha, beta, gamma) rhythm-switching task and analyzed 20 independently trained networks. Whereas low-frequency rhythms were produced by distributed participation of many neurons, high-frequency rhythms were dominated by a small subpopulation of short-time-constant neurons, and the negative correlation between time constant and matched-mode amplitude strengthened monotonically with frequency. Rhythm switching was supported by multiple coexisting mechanisms: turnover of the active subpopulation, network-wide baseline shifts that reposition the operating point near distinct unstable fixed points, and inter-neuronal phase reorganization that selectively cancels or supports band components in the population output. The mechanism deployed for each mode pair varied across training runs, exposing a degeneracy of learned solutions. These findings parallel the coexistence of rhythm-specific and multi-rhythm interneurons reported in biological circuits and provide a candidate framework for interpreting frequency-band-specific functional differentiation in neural systems.

Firing rate fluctuations in neural populations are observed experimentally over multiple time scales, in single neurons, across trials when elicited by stimuli, and across populations. In this work, we examine how firing rate fluctuations emerge in networks of coupled integrate-and-fire neurons as a function of the initial distribution of voltages in networks with time-varying inputs. We analytically derive an approximation for the evolution of the instantaneous population rate or flux as a function of the initial voltage distribution through a Fokker-Planck system. Unlike earlier mean field approaches based on asynchronous or constant flux steady state solutions to the Fokker-Planck system, the approach considered here is based on the transport solution to the advection equation and assumes that the time-varying inputs are slow, and the neurons are in the excitation-driven regime. The transport mean field system predicts how firing rate fluctuations emerge from a dynamic interaction between time-varying inputs, initial densities, and coupling in populations of neurons.

Genetic circuit design remains a laborious, expert-driven process despite decades of progress in synthetic biology. We study this problem through code generation: models produce Python code in pysbol3 to construct genetic circuits in the Synthetic Biology Open Language (SBOL), a formal representation that supports automated verification. We introduce GenCircuit-RL, a reinforcement learning framework built around hierarchical verification rewards that decompose correctness into five levels, from code execution to task-specific topological checks, and a four-stage curriculum that shifts optimization pressure from code generation to functional reasoning. We also introduce SynBio-Reason, a benchmark of 4,753 circuits spanning six canonical circuit types and nine tasks from code repair to de novo design, with held-out biological parts for out-of-distribution evaluation. Hierarchical verification improves task success on functional reasoning tasks by 14 to 16 percentage points over binary rewards, and curriculum learning is required for strong design performance. The resulting models generate topologically correct circuits, generalize to novel biological parts, and rediscover canonical designs from the synthetic biology literature.

Brain-language model comparisons often interpret neural prediction scores as evidence that model representations capture brain-relevant language computation. We asked whether language models align with brains, and whether prediction scores are enough to support that claim, using L-PACT, a source-audited framework that evaluates predictive, relational, mechanism-stripping, and reliability-bounded evidence. Across primary naturalistic language neural datasets and derived language-model representations, L-PACT compared real model features with nuisance baselines and severe controls, tested whether model-to-brain profiles reproduced brain-to-brain patterns, recomputed held-out scores after mechanism stripping, and normalized evidence against brain-brain ceilings. The locked analysis set contains 414 predictive-control rows, 2304 relational profile rows, 4320 mechanism-stripping rows, 420 brain-brain ceiling rows, and 146 integrated decision rows. Assay-sensitivity checks showed that brain-brain reliability, brain-as-model run-to-run relational profiles, independent low-level neural and WAV-derived acoustic-envelope gates, and a deterministic implanted-signal simulation can produce positive evidence when expected. Nevertheless, no real model row passed the predictive, relational, mechanism-stripping, or operational Turing-bounded reliability gates; all 146 integrated rows were control-explained. Less stringent single-criterion rules would have counted raw positive predictive, relational, stripping-delta, and ceiling-normalized effects, but L-PACT downgraded them because controls explained the apparent evidence. In the analyzed derived artifact set, the tested language-model representations do not satisfy L-PACT alignment gates; apparent positives are converted into an auditable control-explained taxonomy rather than treated as structural alignment.

Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. However, what remains unknown is which visual properties models actually converge on and which factors may underlie this convergence. To address this, we decompose the object similarity structure of 162 diverse vision models into a small set of non-negative dimensions. To determine universal versus model-specific dimensions, we then estimate how often each dimension reappears across models. In contrast to model-specific dimensions, universal dimensions are more interpretable and more strongly driven by conceptual image properties, indicating the relevance of interpretability and semantic content as implicit factors driving universality across models. Differences in architecture, objective function, training data, model size, and model performance do not explain the emergence of universal dimensions. However, models with more universal dimensions also better predict macaque IT activity and human similarity judgments, suggesting that universality reflects representations relevant to biological vision. These findings have important implications for understanding the emergent representations underlying deep neural network models and their alignment with biological vision.

RNA viruses form genetically diverse populations structured as mutant spectra, or quasispecies, whose internal organization influences their evolutionary and adaptive dynamics. While genetic diversity has been extensively characterized, the structural organization of viral populations in sequence space remains less explored. Here, we compare genotype network architectures in two RNA viruses with markedly different evolutionary contexts: bacteriophage $Qβ$ evolving in controlled laboratory conditions and SARS-CoV-2 evolving within infected human hosts. Using deep sequencing data, we reconstruct the genotype network of mutationally coupled variants within viral populations and analyze their topological properties. Despite large differences in genome size, mutation rate, and ecological setting, both viruses exhibit a common organization: a highly abundant central haplotype surrounded by layers of variants of diminishing abundance as Hamming distance to the central haplotype increases. All reconstructed networks share qualitative and quantitative topological features, displaying a hierarchical structure. The robust organization of both populations under multiple conditions suggests that RNA viruses may share a common genotype network architecture governed by fundamental properties of sequence space and the generic mechanisms of replication and mutation. Genotype networks provide a unifying framework to describe viral population structure beyond conventional diversity measures and, by revealing how local constraints shape mutational search, offers insights into the predictability of viral evolution.

The increasing availability of experimental data has intensified interest in calibrating stochastic models, raising fundamental questions about parameter identifiability. Structural identifiability determines whether parameters can be uniquely recovered from idealised, noise-free data, a prerequisite to allow for parameter estimation. However, existing methods to assess structural identifiability are not generally applicable to stochastic processes. We develop a methodology to analyse structural identifiability for a class of spatio-temporal stochastic processes. We investigate how identifiability depends on the type of available data, distinguishing between single-particle trajectories and total particle density measurements. For trajectory data, we use the individual-based model description that explicitly represents single-particle dynamics. For population-level data, we derive a partial differential equation model representation, that describes the evolution of total particle density, and apply a differential algebra approach, common to ordinary differential equations analysis. We further introduce a novel method to study the initial condition, based on characteristic equations to construct a Taylor expansion of the density evolution, enabling identification of additional identifiable parameter combinations. We apply our methodology to a model, and show it is identifiable with trajectory data but only locally identifiable with density data, and demonstrate the critical role of initial conditions in the identifiability analysis.

Brain encoder models predict cortical fMRI responses from the internal activations of pretrained vision and language networks, and are typically evaluated by held-out prediction accuracy. This is a useful signal for training but a poor one for interpretation: it tells us an encoder fits the data without telling us whether it has internalized the functional organization of the brain. We propose feature visualization -- gradient ascent on the encoder's predicted activation for a target region of interest (ROI) -- as a complementary interpretability technique, and apply it to TRIBE v2 composed with V-JEPA 2 (ViT-G, 40 layers), holding both frozen and synthesizing still images for seven regions spanning the ventral and dorsal visual hierarchies. Under identical hyperparameters, the probe recovers a visible progression of increasing spatial scale and feature complexity across V1 to V4, matching the ventral-stream hierarchy. It also produces three distinctive downstream regimes: radial "frozen-motion" streaks for the middle temporal area (MT) despite static-only optimization, face-like features for the fusiform face area (FFA), and consistent rectilinear line patterns for the parahippocampal place area (PPA). Optimized FFA stimuli drive the predicted region ~4x as much as a natural face photograph, consistent with feature visualization producing adversarial super-stimuli rather than canonical exemplars. The probe is simple, differentiable, and applicable to any brain encoder with a differentiable backbone, allowing for qualitative evaluation of brain encoders.

Advances in large language models (LLMs) have recently opened new and promising avenues for small-molecule drug discovery. Yet existing LLM-based approaches for molecular generation often suffer from high rates of invalid and low-quality ligand candidates, a result of the syntactic limitations of current models with regard to molecular strings. In this paper, we introduce $\texttt{ToolMol}$, an evolutionary agentic framework for de novo drug design. $\texttt{ToolMol}$ combines a multi-objective genetic algorithm with an agentic LLM operator that iteratively updates the ligand population. We build a comprehensive toolbox of RDKit-backed functions that allows our agentic operator to consisently make precise ligand modifications. $\texttt{ToolMol}$ achieves state-of-the-art performance on multi-objective property optimization tasks, discovering drug-like and synthesizable ligands that have $>10\%$ stronger predicted binding affinity compared to existing methods, evaluated on three protein targets. $\texttt{ToolMol}$ ligands additionally achieve state-of-the-art results in gold-standard Absolute Binding Free Energy scores, gaining over existing methods by over $35\%$. By studying chain-of-thought reasoning traces, we observe that tool-calling enables the model to more faithfully execute its planned modifications, efficiently exploiting the strong chemical prior knowledge in LLMs.

The ability to predict the future is of great value for biological and artificial cognitive systems alike. However, successfully predicting the future typically requires maintaining a memory of the recent past. It is currently unclear how biological or artificial spiking neural networks can learn to maintain past sensory information to help predict the future. Here we propose Predictive Coding Light+ (PCL+), a spiking neural network architecture for unsupervised sequence processing that learns recurrent excitatory connections with delays to enable short-term retention of information. We show that the PCL+ network reproduces classic findings on sequence learning in visual cortex. Furthermore, it learns to ``fill in'' missing input in a challenging gesture recognition task. Overall, our work shows how spiking neural networks can learn recurrent excitatory connections with delays to maintain a record of the recent past and successfully predict the future.

The perceptual representations supporting our ability to recognize faces remain a computational mystery. Deep neural networks offer mechanistic hypotheses for human face perception, but theoretically distinct models often make indistinguishable representational predictions for randomly sampled faces. To expose diagnostic differences among these hypotheses, we compared six neural network models sharing an architecture but trained on distinct tasks, using face pairs optimized to elicit contrasting model predictions ("controversial" pairs) alongside randomly sampled pairs. We tested model predictions against face-dissimilarity judgments from 864 human participants across stimulus sets differing in realism and pose variation. Models prioritizing high-level, invariant structures (trained via inverse rendering, face identification, or object classification) most robustly matched human judgments. Furthermore, models trained on natural images typically outperformed synthetic-trained counterparts. Together, these findings suggest that human face perception is shaped by mechanisms that infer latent causes of facial appearance, discount nuisance variation, and are tuned by natural image statistics.

Understanding what individual neurons encode is a core question in neuroscience. In primary visual cortex (V1), mathematical models (e.g., Gabor functions) capture neural selectivity, but no comparable framework exists for higher areas. We show that natural language can fill this role: across macaque V1 and V4, the selectivity of most neurons is captured by concise, verifiable semantic descriptions. Using digital twins of V1 and V4, we develop a closed-loop framework that translates each neuron's high- and low-activating images into dense captions, generates a semantic hypothesis and synthesized images, and verifies the hypothesis in silico. Descriptions range from oriented edges and spatial frequency in V1 to conjunctions of form, color, and texture in V4. In V4, images generated from activating and suppressing hypotheses drove 96.1% of neurons above the 95th and 97.6% below the 5th percentile of natural-image responses, respectively (vs. ~10\% for random images); V1 activation results matched V4, while V1 suppression was less describable in language. Representational similarity analysis reveals partial alignment between neural activity, vision embeddings, and language embeddings, with vision most aligned to neural activity; alignment lost in the text bottleneck is recovered when hypotheses are rendered back into images, showing that linguistic compression is lossy yet semantically faithful. Together, these results show that combining generative models with neural digital twins enables interpretable, testable descriptions of neural function at scale, toward agentic scientific discovery.

Strongly coupled, recurrent, balanced network models have been successful in describing and predicting many phenomena observed in cortical neural recordings. However, most balanced network models use current-based synapse models in place of more realistic, conductance-based models. Conductance-based synapse models predict unrealistically small membrane potential variability. On the other hand, introducing realistic levels of spike time correlations to models with current-based synapses predicts unrealistically large membrane potential variability. We use computer simulations to show that these two effects can cancel: Recurrent network models with conductance-based synapses and spike time correlations produce more realistic, moderate levels of membrane potential variability. Consistent with recent work on feedforward networks, our results show that including more realistic modeling assumptions produces more realistic dynamics, but only if when two modeling assumptions are included together.

Protein function prediction is dominated by representations grounded in sequence and static structure, neither of which captures the collective vibrational dynamics through which proteins act. Here we introduce frequency-space mechanics, a representational framework in which a protein is encoded as a mechanical harmonics graph (MHG): nodes are vibrational modes derived from molecular dynamics, and edges are harmonic couplings weighted by octave alignment between mode frequencies. The representation is coordinate-free, sequence-independent, scale-invariant, and inhabits a latent mechanical space in which the original atomic coordinates have been projected out. The same construction applies to any system with a tractable eigendecomposition. Trained on 5,238 SwissProt proteins under a strict 30% sequence-identity split and using no sequence information, a graph neural network over static MHGs predicts GO molecular function terms across the ontology, demonstrating that vibrational physics alone encodes broad functional class. Kuramoto entrainment of the harmonic coupling graph, formally a Hamiltonian operation over mode frequencies and directly compatible with quantum annealing hardware, improves prediction for proteins whose function depends on collective conformational dynamics. On CLIC1, a fold- and function-switching chloride channel excluded from training, entrainment amplifies channel-activity signal 7.5-fold and antioxidant signal 2.4-fold, recovering both functional states from dynamics alone.

We propose a novel multimodal deep learning framework for patient-level survival prediction, which integrates whole-slide histology features, RNA-seq expression profiles, and clinical variables. Our architecture combines an ABMIL module~\cite{ilse2018attention} for slide-level representation with feedforward encoders for RNA and clinical data. These embeddings are then integrated through low-rank bilinear cross-modal fusion~\cite{liu2018efficient} to model conditional interactions across modalities while controlling parameter growth. The model outputs continuous risk scores that are subsequently mapped to survival times using a nonparametric calibration procedure based on the Kaplan--Meier estimator~\cite{kaplan1958nonparametric}. By decomposing multimodal reasoning into independent pairwise interactions, the proposed fusion design promotes structural interpretability and parameter efficiency compared with full tensor and hierarchical fusion strategies. Experiments on the CHIMERA challenge dataset demonstrate improved predictive performance over concatenation-based baselines and competitive generalization on hidden evaluation cohorts. These results indicate that the proposed framework is a promising approach for multimodal survival prediction in HR-NMIBC. The implementation is publicly available at https://github.com/hassancpu/ChimeraChallenge2025_Task_3.

In this work, we introduce a Tropical Axial Attention neural reasoning architecture that replaces vanilla softmax dot-product attention with max-plus operators, inducing a piecewise-linear structure aligned with dynamic programming formulations. From multi-species sequence alignments, our model learns all possible pairwise distances and is trained using a combination of $\ell_1$ and tropical symmetric distance metric losses with an ultrametric violation penalty. We leverage the well known isomorphic relationship between the space of all phylogenetic trees with $n$ species and tropical Grassmannian to show that tropical attention provides a natural geometric framework for phylogenetic inference. On empirical $DS1-DS11$ alignments, where true trees are unknown, the tropical model produces distance matrices that are substantially closer to their BME-induced tree metrics than the baseline models. These results suggest that tropical attention is a useful geometric inductive bias for neural phylogenetic inference, especially under distribution shift and when tree-metric consistency is important.

Clinical interpretation often assumes that observable performance provides sufficient information about the organization of an adaptive system. However, similar observable performance may correspond to distinct latent organizations. This study extends a previous multi-level framework by introducing a fourth analytical level centered on longitudinal viability. Using an exploratory single-case design in a Parkinsonian patient, gait data were recorded with instrumented insoles under three occlusal conditions: neutral natural occlusion (ONL), a 2.5-degree increase in vertical dimension of occlusion (OC2.5), and a 3-degree increase in vertical dimension of occlusion (OC3). Two measurement sessions were conducted eleven weeks apart, during which the participant underwent a structured sensorimotor intervention. The vertical dimension of occlusion was considered as an experimentally varied constraint applied to an adaptive neuromechanical system. Although observable performance remained globally comparable across conditions, PCA-based latent-space analysis revealed differentiated longitudinal centroid displacements. OC3 exhibited the smallest displacement, ONL an intermediate displacement, and OC2.5 the largest displacement. This hierarchy supports the relevance of a Level 4 framework centered on viability, understood here as an exploratory proxy for a configuration's capacity to maintain lower longitudinal reorganization over time. These findings remain within-subject, exploratory, and non-causal. They do not establish a validated clinical threshold, causal occlusal effect, or therapeutic optimum. More generally, the work suggests that clinical relevance cannot be inferred solely from instantaneous performance or static latent structure, but may also depend on the capacity of a configuration to sustain a coherent trajectory over time.

The Inositol 1,4,5-trisphosphate receptor channel (IP 3 R) is an important calcium channel involved in calcium-induced calcium release, playing a prominent role in intracellular calcium signaling. However, accurately characterizing its gating behavior remains a challenge, particularly due to the temporal resolution of patch clamp techniques that is not large enough to detect all short-lived events. This limitation can significantly bias the inference of kinetic models describing the receptor activity. To address this issue, we focused on the quantitative analysis of IP 3 R gating behavior using patch clamp data, with particular attention to missed events. We modeled IP 3 R channel gating using Hierarchical Markov chains and used a Bayesian approach that integrates missed event correction directly into the likelihood function, enabling more accurate parameter inference and model evaluation. We show that accounting for missed events deeply clarifies the multi-modal model that emerges from model selection. In this new model, the Park and Drive modes both consist of the same 3-state Markov model, with mode-dependent kinetic parameters: the Drive mode stabilizes the closed state directly connected to the open one, whereas the Park mode stabilizes the other closed state, that is not connected to the open one. Intermediate Ca 2+ concentrations are found to strongly depress the Drive to Park transition rate, so that the IP 3 R channel undergoes frequent transitions to the Park mode only for __ 50 nM or micromolar Ca 2+ concentrations. Overall, our approach provides a refined perspective on IP 3 R channel modeling and highlights the critical importance of accounting for missed events upon model selection based on single-channel recordings.

NORI performs probabilistic inference to resolve ambiguous mappings between experimental observations and biological entities orders of magnitude faster than state-of-the-art methods. This makes large-scale analysis and extensive hyperparameter optimization possible, and supports a broader range of bioinformatics applications, including protein inference, taxonomic and functional analysis in omics-fields.

Topological data analysis (TDA) has established itself as a useful tool for capturing multiscale structures in complex networks, such as connected components, cycles, and cavities. Although Vietoris-Rips (VR) filtering is widely used in network analysis, it tends to be computationally expensive, especially for large networks. This work explores vertex function-based (VFB) filtering based on network measures, applying persistent homology to identify relevant topological structures in cancer-associated protein networks, and compares its effectiveness with the VR approach. The results show that VFB reproduces the second-order structures (Betti-2) identified by VR, recovering previously reported essential genes. In addition, VFB detected new driver genes, confirmed in databases such as IntOGen and NCG, and allowed analysis of third-order structures (Betti-3) that was not feasible with VR. Thus, VFB represents a scalable alternative to VR, preserving biological interpretability and complementing classical network metrics.

Bifunctional enzymes, which catalyze both the forward and reverse steps of a substrate modification reaction, arise naturally in bacterial two-component signaling systems and metabolic regulation. Beyond their well-known role in conferring absolute concentration robustness (ACR) on substrate species, bifunctional enzymes profoundly shape the dynamical landscape of the networks in which they appear. We study a class of dual-site futile cycles in which the reverse modification steps are carried out by bifunctional enzyme-substrate compounds, and provide a complete mathematical analysis of all four such networks, characterizing the existence, number, and stability of steady states, as well as the bifurcation structure as total substrate is varied. All four networks admit boundary steady states, in contrast to the non-bifunctional case. The networks differ in the number and stability of boundary steady states, in the maximum number of positive steady states (ranging from two to four), and in whether bistability is present. In two networks, a transcritical bifurcation connects the boundary and positive steady state branches; in one case this is a backward bifurcation, producing hysteresis. Perhaps the most striking phenomenon occurs in one of the four networks, which simultaneously exhibits bistability and ACR in the final modification state, where the system can settle into either of two stable steady states with different intermediate concentrations yet identical final product concentration.

We propose uncommon self-knowledge (USK) as a candidate criterion for consciousness: synergistic information a system carries about itself that exists only in the joint of its subsystems and is destroyed by decomposition. Drawing on Gottwald's partition-lattice grounding of Partial Information Decomposition (PID), where redundancy corresponds to Aumann's common knowledge and synergy to the gap between separate and joint observation, we propose the synergistic component of self-directed information as a candidate formal signature for conscious processing. If correct, the framework would (1) offer a clean separation between consciousness and metacognition (synergistic vs. redundant self-knowledge), (2) provide principled resolutions to counterexamples that challenge IIT, GWT, and HOT, (3) be operationalizable via Partial Information Rate Decomposition (PIRD) with self-targeting, and (4) generate distinctive empirical predictions, the strongest being a GWT timing dissociation (consciousness correlates with pre-broadcast synergy formation, not broadcast itself) and a specific dissociation between self-report disruption and task-performance disruption under middle-layer perturbation in LLMs. The proposal is consistent with recent empirical findings that both anaesthesia and Alzheimer's disease specifically reduce synergistic information processing while preserving or increasing redundancy.

The replication dynamics (differential equation system) is the foundation of evolutionary game theory. When n=2, there are four possible types of replication dynamics. When n=3, there are 49 possible types of replication dynamics. However, when n>3, the classification of replication dynamics has not been solved. In this article, the sufficient and necessary conditions of the replication dynamics equation with a unique fixed point in the interior of simplex $S_n$(Int$S_n$) for $n\geq 2$ are presented. Furthermore, the different types of replication dynamics equations with a unique fixed point in IntSn is discussed.

One of the classical results of mathematical population genetics states that the frequency of a beneficial mutant's offspring, on its way to fixation in a large population, looks like a logistic curve. A logarithmic scaling (both in height and time) of these selective sweep curves leads (in the case of strong selection) to a tent-like shape in the large population limit: First the logarithmic frequency of the mutant increases linearly from 0 to 1, then that of the former resident decreases from 1 to 0. For moderate selection the logarithmic frequencies develop (in the large population limit) a jump at the beginning/the end of the sweep, which takes the shape of the tent into that of a house. Our main result (proved for the Moran model) assesses the regularity of this convergence in the large population limit: It is uniform in the house's roof (phases of linear growth and decline) and "Skorokhod $M_1$" in the house's walls (closely around the jumps). Apart from interest in its own right, we anticipate that this result and the proof techniques will be instrumental for extending the description of clonal interference by Poissonian interacting trajectories (as it was done in Hermann et al. (2024) for strong selection) also to moderate selection.

The cerebellum and cerebral cortex form tightly coupled circuits thought to support flexible and efficient temporal processing. How this interaction shapes cortical learning dynamics, and whether such heterogeneous modularity can benefit artificial systems, remains unclear. Here, we augment a recurrent neural network (RNN) with a cerebellar-inspired feedforward module and evaluate the resulting architecture on temporal tasks of varying difficulty. The cortico-cerebellar RNN (CB-RNN) learns faster and reaches higher maximum performance than parameter-matched fully recurrent baselines across a variety of regimes. Crucially, freezing the recurrent core after minimal training and delegating subsequent learning to the cerebellar module preserves superior learning efficiency, suggesting the cerebellar module is a primary driver of efficiency and that the cortical network can largely function as a fixed reservoir. Our results suggest that heterogeneous modular architectures can act as a powerful structural inductive bias in neural systems.

Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of alignment parallels early psychology's focus on mental illness: necessary but incomplete. What we call Positive Alignment is the development of AI systems that (i) actively support human and ecological flourishing in a pluralistic, polycentric, context-sensitive, and user-authored way while (ii) remaining safe and cooperative. It is a distinct and necessary agenda within AI alignment research. We argue that several existing failures of alignment (e.g., engagement hacking, loss of human autonomy, failures in truth-seeking, low epistemic humility, error correction, lack of diverse viewpoints, and being primarily reactive rather than proactive) may be better addressed through positive alignment, including cultivating virtues and maximizing human flourishing. We highlight a range of challenges, open questions, and technical directions (e.g., data filtering and upsampling, pre- and post-training, evaluations, collaborative value collection) for different phases of the LLM and agents lifecycle. We end with design principles for promoting disagreement and decentralization through contextual grounding, community customization, continual adaptation, and polycentric governance; that is, many legitimate centers of oversight rather than one institutional or moral chokepoint.

Multilayer networks are widely used across biology to represent systems in which complex networks vary across space, time, or interaction types. However, interactive visualization tools remain limited. We present MiRA (Multilayer Interactive Rendering Application), a browser-based, installation-free web application for visualizing biological multilayer networks. MiRA offers seven complementary visualization modes and interactive features that enable researchers to visually navigate the high complexity of multilayer networks for research and education.

In Bayesian phylogenetics, our goal is to estimate the posterior distribution over phylogenetic trees. Markov chain Monte Carlo methods are widely used to approximate the phylogenetic posterior distributions. For large-scale sequence data, repeated evaluation of the likelihood function incurs a high computational cost. In this article, we propose a machine-learning algorithm with over 35 topological and branch-length features to predict the changes in the likelihood function caused by tree moves (\eg,~eSPR, stNNI) used in standard MCMC approaches. This algorithm is then used to design a delayed acceptance MCMC kernel, which utilized the predicted surrogate function for preliminary rejection, to accelerate tree space searches. Furthermore, we integrate our proposed MCMC kernel into the sequential Monte Carlo sampler framework. We validate the proposed delayed-acceptance sequential Monte Carlo approach (DA-SMC) on simulation and real data sets. Our delayed acceptance kernel can maintain robust estimation while reduces the number of likelihood evaluations significantly, yielding substantial computational time savings. We develop a Python package that is available at https://github.com/wentYu/DAphyloSMC.

Adults vary greatly in how effectively they learn a new language, but the signals driving the learning processes and individual differences remain unclear. Over seven days, we tracked behavioral learning and collected fMRI data from 102 adults as they learned an artificial language with corrective feedback. We trained matched transformer models with prediction, feedback, or combined objectives and compared their internal representations to brain activity. Representations derived from the prediction-focused model accounted for the largest share of unique neural variance at the group level, despite the human task being feedback-based. Throughout model training, both objectives showed a shift in brain-model alignment from sensory to higher-order language and associative networks, indicating abstraction processing. Conversely, neural patterns related to the feedback model were most useful for predicting individual generalization outcomes on Day 7. These findings support a multi-signal model of adult language learning, in which prediction shapes a common neural learning architecture across learners, whereas feedback-related mechanisms better explain individual differences over time.

As a critical component of sixth-generation (6G) wireless networks, ultra-reliable and low-latency communication (URLLC) is expected to support real-time and reliable information exchange in low-altitude environments. However, achieving URLLC often incurs significant resource overhead, including increased bandwidth consumption, higher transmit power, and denser access point (AP) deployment, which pose significant challenges to both spectral efficiency (SE) and energy efficiency (EE). Besides, existing iterative optimization algorithms are computationally intensive and struggle to meet the latency requirements of URLLC. To address these challenges, we propose a hybrid aerial-terrestrial cell-free massive MIMO (CF-mMIMO) network to support diverse services, along with a channel prediction network and a deep mixture of experts (MoE) network for uplink optimization. First, we design a channel prediction network (CP-Net) to mitigate channel aging caused by high-mobility user equipment (UE). CP-Net employs three Transformer-based sub-networks for aged channel state information (CSI) prediction, while a channel quality-aware loss function is introduced to improve the prediction accuracy of weak links. Based on the predicted CSI, we develop a deep MoE network (MoE-Net) for power allocation comprising three expert models targeting different objectives. Then, we introduce a weighted gating network (WT-Net) to learn an efficient adaptive combination of expert outputs. The proposed framework better captures heterogeneous UE requirements and improves communication performance under URLLC constraints. Numerical results demonstrate the effectiveness of the proposed method.

This paper presents an analytical framework for downlink pinching antenna systems (PASS) employing waveguide division multiple access (WDMA) and non-orthogonal multiple access (NOMA). A unified channel model is developed to capture antenna deployment, user spatial distribution, and path loss. Closed-form and single-integral expressions for the outage probability and average achievable rate are derived and validated via Monte Carlo simulations. The results show that NOMA achieves higher spectral efficiency at high transmit signal-to-noise ratio (SNR) due to successive interference cancellation (SIC), whereas WDMA offers more reliable performance at low to moderate SNR but suffers from an outage floor and rate saturation at high SNR. Moreover, WDMA performance is more sensitive to the user spatial distribution due to the spatially dependent inter-waveguide interference. These findings provide design insights for access-scheme selection and antenna placement in PASS.

Data-dependent secondary transforms, which aim to decorrelate coefficients of a separable primary transform, can improve residual coding efficiency; however, their deployment is often constrained by computational complexity. Recent video codecs use variants of the low-frequency non-separable transform (LFNST), which discards some high-frequency secondary transform coefficients, limiting achievable coding gains. Moreover, existing data-dependent secondary transforms lack explicit rate-distortion (RD) optimal design criteria. In this work, we propose a framework for designing low-complexity data-dependent secondary transforms, termed Fast Sparsifying Secondary Transforms (FaSSTs). Our approach approximates data-driven sparse orthonormal transforms (SOTs) by factorizing them into a sequence of Givens rotations. The rotations are efficiently determined using an alternating minimization strategy combined with an approximate Givens factorization procedure. Our method adapts the number of rotations based on the prediction mode, further reducing computational complexity. We design mode-dependent secondary transforms for intra-prediction residuals in AV2 using FaSST. Experimental results show that mode-adaptive FaSST matches the RD performance of LFNST while reducing the number of computations by 83.67%. Moreover, by avoiding fixed-coefficient truncation, FaSST achieves up to 1.80% BD-rate savings relative to LFNST while operating at 66.24% lower complexity.

Intelligent Reflecting Surfaces (IRSs) are a promising technology for enhancing the spectral and energy efficiency of millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. In these systems, accurate channel estimation remains challenging due to the passive nature of IRS elements and the high pilot overhead in large-scale deployments. This paper presents a deep learning-based Multi-Block Attention (MBA) framework for efficient cascaded channel estimation in IRS-assisted mmWave MIMO systems that utilize orthogonal frequency division multiplexing (OFDM). First, we show the optimality of the discrete Fourier transform (DFT) and Hadamard matrices as phase configurations for least squares (LS) estimation. To reduce training overhead, we selectively deactivate IRS elements and compensate for induced feature loss using a two-stage architecture: (i) a Convolutional Attention Network (CAN) for spatial correlation recovery and (ii) a Complex Multi-Convolutional Network (CMN) for noise suppression. The MBA architecture mitigates error propagation through attention-guided feature refinement and denoising. Simulation results indicate that the MBA method reduces pilot overhead by up to 87% compared to the LS estimator. Additionally, at signal-to-noise ratios of 10 dB, our proposed method achieves approximately 51% lower normalized mean squared error (NMSE) than leading methods. It also maintains low computational complexity and adapts effectively to various propagation environments.

Angle power spectrum (APS) characterizes the directional distribution of received signal power and is directly relevant to beam management and MIMO processing. While environment-aware learning has been widely studied for radio maps and path loss, direct map-to-APS prediction still lacks a standardized large-scale benchmark. This paper presents Map2APS, a physically grounded benchmark constructed from intelligent ray-tracing (IRT) path-level propagation records. Map2APS covers 51 equal-height urban maps and approximately 2.55 million Tx--Rx samples, with a strict cross-map split for evaluating generalization to unseen urban layouts. We benchmark representative model families and introduce MS-AReg as a strong reference baseline. On the full held-out test set of 249{,}993 samples, MS-AReg achieves a cosine similarity of 0.948, a peak location error of 1.20$^\circ$, and an inference latency of 0.101 ms/sample. We further report dominant-direction metrics, including Top-1 dominant peak hit rate and dominant peak recall, to evaluate whether predicted spectra preserve decision-relevant arrival directions. The benchmark, code, and evaluation scripts are released at https://github.com/UNIC-Lab/aps-data.

Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Conventional ultrasound assessment is commonly based on intima-media thickness, plaque appearance, stenosis degree, and peak systolic velocity, but these morphology- and velocity-based indicators may not fully capture patient-specific vascular risk. This study presents AtheroFlow-XNet, a CUBS-compatible ultrasound morphology and uncertainty-aware learning baseline for carotid intima-media segmentation and preliminary risk prediction. Using the Carotid Ultrasound Boundary Study dataset, manual lumen-intima and media-adventitia boundary annotations were converted into dense intima-media masks for supervised segmentation. Clinical variables were incorporated into an auxiliary risk-prediction branch, and Monte Carlo dropout was used for uncertainty-aware inference. The model was evaluated using a patient-level train-validation-test split with 1,522 training images, 326 validation images, and 328 testing images. The proposed model achieved a Dice coefficient of 0.7930 for LI-MA mask segmentation, a segmentation loss of 0.2359, and an area under the receiver operating characteristic curve of 0.6910 for preliminary risk prediction. Qualitative results showed that predicted masks were generally aligned with manual annotations, while uncertainty maps highlighted ambiguous wall-boundary regions. These results suggest that ultrasound-derived carotid morphology can support automated wall analysis and uncertainty-aware interpretation. Since CUBS does not provide Doppler waveforms or CFD-derived hemodynamic biomarkers, this work should be interpreted as a reproducible morphology-driven baseline. Future work will incorporate Doppler-derived flow profiles, patient-specific vascular reconstruction, and CFD-based wall shear biomarkers.

Electroencephalogram (EEG) signals are highly susceptible to artifacts, resulting in a low signal-to-noise ratio which makes extraction of meaningful neural information challenging. Artifact Subspace Reconstruction (ASR) is one of the most widely used artifact filtering techniques in EEG-based BCI applications, owing to its real-time applicability. ASR reconstructs artifact-free signals by operating in Principal Component (PC) space within sliding windows. However, ASR performance is critically sensitive to its threshold parameter - an incorrect threshold risks removing task-relevant neural features alongside artifacts. Furthermore, since PCs are linear combinations of all channels, subspace reconstruction in PC space may alter the underlying data structure, potentially discarding essential neural information. To address these limitations, we propose nASR, a novel end-to-end trainable Keras layer that jointly optimizes artifact rejection and downstream decoding. nASR introduces two trainable threshold parameters: K, which governs artifact detection in PC variance space, and L, which quantifies eigen-spread to pinpoint the primary artifact--contributing channels, enabling selective channel-level reconstruction that preserves clean channel information. An ablation study comprising five model variants (m01 - m05), evaluated across two subjects from the BCI Competition IV Dataset 1, confirms that nASR variants consistently outperform traditional ASR on test classification metrics, while achieving a 6-8x reduction in inference time, making nASR a strong candidate for real-time BCI applications demanding both low latency and high decoding performance.

Semantic communication systems for goal-oriented transmission must protect task-relevant information not only through source compression but also via physical layer mapping. Existing approaches decouple constellation design and semantic encoding, exposing critical symbols to channel errors at the same rate as irrelevant ones. Contrary to this, in this paper, a joint semantic-physical layer framework is proposed, which is composed of a vector quantized-variational autoencoder that extracts discrete latent concepts, a semantic criticality indicator (SCI) that scores each concept by task relevance, and a deep reinforcement learning agent that dynamically selects the transmission subset based on instantaneous channel conditions. At the physical layer, a learned semantic-aware M -QAM constellation assigns symbol positions according to joint co-occurrence statistics and SCI scores, departing from the uniform spacing and Gray coding of standard M -QAM which minimizes average BER without regard for semantic content. We introduce a novel semantic symbol vulnerability (SSV) metric and a semantic protection probability (SPP) to quantify the exposure of task-critical symbols to decoding errors, and prove that any Gray-coded constellation is strictly suboptimal in SCI-Weighted SSV whenever the source exhibits non-uniform semantic importance and co-occurrence statistics. Simulation results demonstrate that the proposed constellation achieves near 100% SPP across modulation orders from 4-QAM to 1024-QAM versus 50% for standard constellations at high spectral efficiency, a 21:1 compression ratio with semantic quality above 0.9, generalizing across MNIST, Fashion-MNIST, and FSDD without modification.

Transmit beamforming for underwater acoustic communication is challenging because it requires perfect knowledge of the channel to the receiver in advance. In practice, channel estimates must be learned through feedback and are often noisy or outdated because of feedback delay and channel variation. In this paper, we investigate angle-based beamforming strategies for a single-user link that reduce dependence on full channel knowledge by exploiting stable components of the geometric structure in the propagation field. In particular, we focus on scenarios in which there exists a dominant path that remains relatively stable over time, making it a suitable candidate for transmit beamforming. Experimental results using the SPACE and MACE data sets demonstrate the effectiveness of the proposed method in terms of data-detection mean-squared error and bit error rate.

Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-established marker of mTBI, motivating the development of portable tools that capture both eye-movement behavior and underlying neurophysiology. In this work, we present an initial framework that integrates electroencephalogram (EEG) with augmented-reality (AR)-based Vestibular/Ocular Motor Screening (VOMS) tasks to estimate subject-specific ocular response times. Pre-processed EEG signals, obtained through band-pass filtering and average referencing, are analyzed using a Redundant Discrete Wavelet Transform (RDWT)-driven deep neural framework. The RDWT coefficients are subjected to trainable zero-phase convolutional filtering and reconstructed into the time domain via inverse RDWT, followed by channel-wise temporal and spatial filtering using 2D convolution layers and convolutional-LSTM-based decoding. An ablation study demonstrates that wavelet-domain filtering serves as an effective denoising strategy, improving prediction performance. Sliding-window predictions were validated using Pearson correlation (>= 0.5), and Dynamic Time Warping (DTW) was subsequently used to estimate ocular response times. DTW-derived metrics revealed significant inter-subject differences across all VOM tasks, supported by Mann-Whitney U tests. Cross-correlation analysis further revealed task-dependent temporal behaviors: pursuit tasks exhibited reactive tracking, whereas saccades showed anticipatory responses. Overall, the results highlight pursuit tasks as particularly informative for distinguishing timing differences and demonstrate the potential of RDWT-based EEG features combined with DTW metrics for multimodal mTBI assessment.

Forecasting within signal processing pipelines is crucial for mitigating delays, particularly in predicting the dynamic movements of objects such as NBA players. This task poses significant challenges due to the inherently interactive and unpredictable nature of sports, where abrupt changes in velocity and direction are prevalent. Traditional approaches, including (S)ARIMA(X), Kalman filters (KF), and Particle filters (PF), often struggle to model the non-linear dynamics present in such scenarios. Machine learning (ML) methods, such as long short-term memory (LSTM) networks, graph neural networks (GNNs), and Transformers, offer greater flexibility and accuracy but frequently fail to explicitly capture the interplay between temporal dependencies and contextual interactions, which are critical in chaotic sports environments. In this paper, we evaluate these models and assess their strengths and weaknesses. Experimental results reveal key performance trade-offs across input history length, generalizability, and the ability to incorporate contextual information. ML-based methods demonstrated substantial improvements over linear models across forecast horizons of up to 2s. Among the tested architectures, our hybrid LSTM augmented with contextual information achieved the lowest final displacement error (FDE) of 1.51m, outperforming temporal convolutional neural network (TCNN), graph attention network (GAT), and Transformers, while also requiring less data and training time compared to GAT and Transformers. Our findings indicate that no single architecture excels across all metrics, emphasizing the need for task-specific considerations in trajectory prediction for fast-paced, dynamic environments such as NBA gameplay.

Log-homotopy particle flow filters realize nonlinear Bayesian estimation by continuously migrating samples from the prior to the posterior distribution. This transport is governed by a pseudo-time ordinary differential equation (ODE). A major practical challenge of these filters is the need for numerical integration, which suffers from high computational cost and susceptibility to stiffness. This paper develops an exact, integration-free closed-form solution for the exact Daum--Huang (EDH) deterministic particle flow under vector linear Gaussian measurements. By transforming the ODE into a specific eigenspace, closed-form algebraic expressions are derived for both the homogeneous state transition matrix and the inhomogeneous forcing term. We prove that this analytic solution is mathematically equivalent to the exact Kalman measurement update. Furthermore, we demonstrate how this closed-form evaluation can be embedded within an $N$-step slicing method, providing a stiffness-mitigating, integration-free particle update for highly nonlinear measurement models.

Traditional methods for classifying global navigation satellite system (GNSS) jamming signals typically involve post-processing raw or spectral data streams, requiring complex and costly data transmission to cloud-based interference classification systems. In contrast, our proposed approach efficiently compresses GNSS data streams directly at the hardware receiver while simultaneously classifying jamming and spoofing attacks in real time. Given the growing prevalence of GNSS jamming, there is a critical need for real-time solutions suitable for power-constrained environments. This paper introduces a novel method for compressing and classifying GNSS jamming threats using generative artificial intelligence (GenAI), specifically variational autoencoders (VAEs), deployed on Google Edge tensor processing units (TPUs). The study evaluates various autoencoder (AE) architectures to compress and reconstruct GNSS signals, focusing on preserving interference characteristics while minimizing data size near the receiver hardware. The pipeline adapts large-scale AE models for Google Edge TPUs through 8-bit quantization to ensure energy-efficient deployment. Tests on raw in-phase and quadrature-phase (IQ) data, Fast Fourier Transform (FFT) data, and handcrafted features show the system achieves significant compression (>42x) and accurate classification of approximately 72 interference types on reconstructed signals (F2-score 0.915), closely matching the original signals (F2-score 0.923). The hardware-centric GenAI approach also substantially reduces jammer signal transmission costs, offering a practical solution for interference mitigation. Ablation studies on conditional and factorized VAEs (i.e., FactorVAE) explore latent feature disentanglement for data generation, enhancing model interpretability and fostering trust in machine learning (ML) solutions for sensitive interference applications.

Affine frequency division multiplexing (AFDM) has recently emerged as a promising waveform for high-mobility communications due to its resilience to Doppler effects and its advantages for integrated sensing and communication (ISAC). AFDM modulates transmit data symbols using chirp subcarriers with two adjustable parameters. One is used for dealing with the Doppler effect and the second parameter can be used for physical layer security (PLS). In this paper, we focus on designing the second chirp parameter in the form of a generic phase function to enhance the robustness of the waveform against brute-force demodulation by the eavesdropper. In particular, we first derive a design criterion that reveals the brute-force demodulation complexity depends on the first derivative of the phase function. Then, we introduce a family of phase functions that can increase the brute-force demodulation complexity in an unbounded and controllable manner, while preserving chirp structure of AFDM. Our simulation results demonstrate that the proposed phase function design enhances the PLS performance of AFDM by several orders of magnitude compared with the conventional AFDM in terms of brute-force demodulation complexity.

As sixth-generation (6G) wireless networks evolve toward increasingly heterogeneous scenarios, tasks, and service requirements, conventional artificial intelligence (AI) models remain limited in task-aware decision-making and autonomous adaptation. To address this issue, this paper first proposes a ChannelAgent-empowered electromagnetic space world model, in which wireless intelligence is organized into a closed-loop process consisting of multi-modal sensing, ChannelAgent as the intelligent core, and execution with feedback update. As a case study, agent-driven channel generation is instantiated through path loss prediction. Specifically, a task-oriented intelligent feature selection mechanism is designed by integrating reinforcement-learning-inspired policy adaptation with evolutionary search, enabling the agent to iteratively derive compact and task-suitable feature subsets according to the current scenario and performance feedback. Simulation results demonstrate superior performance in both single-scenario and multi-scenario tasks, highlighting the potential of the proposed model for autonomous, adaptive, task-oriented, and closed-loop wireless intelligence.

This paper investigates the effect of oscillator phase noise in orthogonal time frequency space (OTFS) systems. The paper provides in-depth analysis of the interference due to phase noise in the delay-Doppler domain and derives expressions for SINR for three different oscillator types, namely free-running oscillators, continuous-time phase locked loops (PLLs) and discrete-time PLLs. The analysis demonstrates the OTFS is sensitive to phase noise and requires appropriate estimation and compensation. In particular, the analysis shows phase noise imposed inter-Doppler-interference (IDI) is severe and that existing phase noise estimation techniques which only consider the common-phase-error (CPE) can not compensate this IDI effectively. Additionally, the existing methods in the OTFS literature on phase noise assume the channel to be a known single tap channel. Hence, in this paper, we propose a method for joint channel and phase noise estimation using a Wiener filtering approach. Our proposed method exploits the statistical nature of both the phase noise and the Doppler spread channel. Our numerical results demonstrate the superior performance of our proposed technique, with gains of up to 8~dB in terms of bit error rate (BER) over existing methods in the literature.

Accurate beam prediction is essential for mitigating signalling overhead and latency in integrated sensing and communication-enabled massive multi-input multi-output systems. With the aid of multimodal learning, the prediction accuracy can be enhanced by leveraging the complementary information from other existing sensors, but the practical deployment is often constrained by the high cost of acquiring semantically aligned multimodal datasets. This paper proposes a variational-inference-based multimodal framework that decouples the optimization problem into modular feature extraction and cross-modal semantic alignment. Specifically, we develop a two-stage training strategy where the model utilises abundant unimodal data for representation learning before performing refined alignment on limited multimodal samples. This design enhances data efficiency and ensures robust feature fusion under sensing uncertainties. Experimental results on the DeepSense6G dataset demonstrate that the proposed framework achieves competitive beam prediction accuracy and maintains high reliability, while only requiring 20% of the multimodal training data compared to conventional end-to-end benchmarks.

Kunchenko's method of polynomial maximization provides a semiparametric apparatus for parameter estimation under non-Gaussian errors, but its classical power basis relies on finite higher-order integer moments. This paper introduces the Parametrically Adaptive Transition Polynomial (PATP), a signed-parity fractional-power family controlled by a continuous parameter alpha in [0,1]. The quadratic exponent map p_i(alpha) connects the fractal regime p_i(0)=1/i, the degenerate linear point p_i(1/2)=1, and the signed-parity integer-power regime p_i(1)=i. For the degree-S=2 case we derive a closed-form variance-reduction coefficient g_2(alpha) in terms of signed and absolute fractional moments, identify the singular behavior at alpha=1/2, and state the moment and regularity conditions under which the formula is meaningful. The construction should be read as a Form-B PATP analogue within Kunchenko's generalized apparatus, not as an exact recovery of the canonical even-power PMM basis at alpha=1. Numerical illustrations on canonical distributions are used to examine the finite-sample behavior of the signed-parity estimator and to mark the boundary of applicability for extremely heavy-tailed cases such as Cauchy.

This paper addresses the critical sensitivity issue of narrow-beam communication systems to physical misalignments and exploits the potential of Integrated Sensing and Communications (ISAC) technology to propose a sensor-free antenna tilt failure detection and estimation framework. The proposed methods utilize environmental static clutter as geometric anchors to monitor systematic gain shifts in clutter heat maps. The proposed methods are introduced for precise antenna tilt detection and estimation using the standard 5G NR frame structure and two different waveforms. Numerical results show the potential of the proposed framework to enable autonomous, self healing network maintenance without the need for external sensors.

We propose Walsh-Hadamard Transform Division Multiplexing (WHTDM), a multicarrier waveform that replaces the conventional IFFT/FFT pair in OFDM with a real-valued, unitary Walsh-Hadamard transform (WHT). WHTDM inherits the CP-OFDM transceiver structure while eliminating all complex multiplications from the transform stage, yielding a transmitter with zero real multipliers in the core modulation block. For detection under doubly-selective channels, we adopt a cross-domain memory approximate message passing (CD-MAMP) equalizer that operates on the banded structure of the equivalent WHT-domain channel matrix. Simulation results under the 3GPP TDL-C channel model at 28 GHz demonstrate that WHTDM with CD-MAMP significantly outperforms conventional OFDM 1-tap MMSE at high mobility, achieving over an order of magnitude lower BER at 120 km/h. Among the compared CD-MAMP-equalized new waveforms, WHTDM achieves the best BER performance while maintaining a transmitter complexity 2.5 $\times$ lower than OFDM and completely eliminating complex multipliers from the transform stage, making it well-suited for low-power IoT terminals.

Rydberg atomic quantum receivers have been seen as novel radio frequency measurements and the high sensitivity to a large range of frequencies makes it attractive for communications reception. However, their performance can be significantly degraded by hardware-induced noise, particularly the noise from laser, which impacts the overall system noise floor and exhibits correlation. To address this challenge, this paper proposes a weight hybrid (WH) architecture for Rydberg-atomic sensors, a novel four-channel combining scheme designed for atomic sensors operating in correlated noise environments. By jointly processing dual signal channels and dual noise reference channels, the WH architecture effectively mitigates noise contributions from lasers and other hardware components. All channels are optimally combined via maximum likelihood estimation within an expectation maximization framework, enabling robust signal extraction under correlated noise. Moreover, the proposed WH architecture is universal and can be readily extended to other types of Rydberg receivers to achieve consistent performance improvements.

The inherent randomness of communication symbols creates a fundamental tension in Integrated Sensing and Communications (ISAC). On the one hand, they enable data transmission while allowing sensing to fully reuse communication resources. On the other hand, their randomness induces waveform-dependent fluctuations that directly affect sensing accuracy. This paper investigates a foundational question arising from this tradeoff: \textit{How does the modulation waveform affect the ranging Cramér--Rao Bound (CRB) when sensing reuses random data symbols?} We address this question by revealing a structural factorization of the Fisher information matrix (FIM) for joint delay-amplitude estimation, which separates the deterministic Jacobian of the target geometry from the random frequency-domain signal power induced by the data symbols. This structure yields a Jensen-type universal lower bound on the CRB, which is exactly attained by CP-OFDM under PSK constellations. For QAM and broader sub-Gaussian constellations, we develop an asymptotic perturbation analysis of the inverse FIM and prove that, when the number of transmitted symbols $N$ grows large, CP-OFDM achieves a lower ranging CRB than any frequency-spread orthogonal waveform over the almost-sure event where the random FIM is invertible. This superiority is further extended to amplitude estimation and full joint delay-amplitude estimation. We also characterize the local geometry of the stochastic CRB minimization problem over the unitary group. The analysis reveals that CP-OFDM is a stationary point for finite $N$, and its Riemannian Hessian is positive semidefinite for sufficiently large $N$, establishing its asymptotic local optimality. Numerical results confirm that OFDM outperforms representative waveforms including SC, OTFS, and AFDM.

As artificial intelligence (AI) is increasingly embedded in wireless networks, models are becoming core components that influence signal processing, resource scheduling and network control. However, model anomalies, tampering and malicious functions also introduce new security risks. In this article, we focus on model forensics in AI-native wireless networks. Specifically, we first discuss key problems including model authenticity verification, malicious function identification and accountability tracing, and summarize the main categories of model forensics. We then explain the role of model forensics in AI-native wireless networks and review representative application scenarios. In the case study, we use RF fingerprinting as an example and present two concrete workflows based on watermark authentication and backdoor detection, illustrating how provenance authentication and malicious behavior identification can be implemented in practice. The results show that model forensics can provide important support for anomaly assessment, provenance tracing and trustworthy operation in AI-native wireless networks. Finally, we outline several promising directions for future research in this emerging area.

Modern edge devices increasingly rely on neural networks for intelligent applications. However, conventional digital computing-based edge inference requires substantial memory and energy consumption. In analog radio frequency (RF) computing, a base station (BS) encodes the weights of the neural networks and broadcasts the RF waveforms to the clients. Each client reuses its passive mixer to multiply the received weight-encoded waveform with a locally generated input-encoded waveform. This enables wireless receivers to perform the matrix-vector multiplications (MVMs) that account for most of the computation burden in edge inference with ultra-low energy consumption. Unlike conventional downlink transmissions which are optimized for communications, analog RF computing requires a computing-centric physical layer that controls both the analog MVM accuracy and the energy consumption for inference. Motivated by this, in this paper, we propose a physical layer design framework for analog RF computing in MU-MIMO wireless systems. We derive tractable models for computing accuracy and energy consumption for inference, formulate a joint BS beamforming and client-side scaling problem subject to computing accuracy, transmit power, and hardware constraints, and develop a low-complexity algorithm to solve the non-convex problem. The proposed design provides client- and layer-specific accuracy control for both uniform- and mixed-precision inference. Simulations under 3GPP specifications show that analog RF computing can significantly reduce client-side energy consumption by nearly two orders of magnitude compared to digital computing, while mixed-precision inference requires even lower energy consumption than uniform-precision inference. Overall, these results establish analog RF computing over wireless networks as a promising paradigm for energy-efficient edge inference.

This letter investigates the problem of energy efficient collaborative strategy for mobile embodied artificial intelligence network (MEAN) over wireless communication. In the considered model, the agents execute the tasks through collaboration, and they can switch between two operating modes based on the signal-to-noise ratio (SNR) and global collaboration. The dual-mode comprises the base station (BS)-assisted collaborative mode, in which agents make decisions through semantic communication with BS and then collaborate on tasks, and the local computing mode, in which the agents make decisions and execute tasks independently. Due to the dynamic wireless communication and flexible collaboration strategy, we jointly consider computation energy, communication energy, and task-execution energy with specific collaborative gains into a mixed-integer nonlinear programming (MINLP) optimization problem whose goal is to minimize the total system energy consumption. To solve it, we propose a lower-complexity enumeration algorithm: first, we get the optimal closed-form solution for semantic compression ratio and transmit power by proving the strict convexity. Second, we determine the scale of collaboration and the operating mode of each agent by a greedy sorting algorithm based on individual energy-saving potentials. Simulation results show that the proposed algorithm can significantly reduce the total energy consumption compared to benchmark schemes.

This paper studies the synthesis of control policies for heterogeneous and interconnected multi-agent systems that collaborate through data exchange over a communication network to minimize a collective cost. We propose a distributed encoded corrective double actor-critic framework that integrates a novel message-passing mechanism. Existing methods assume noise-free and delay-free access to the global or partial states and overlook the fact that the global states, though noisy and delayed, can be progressively reconstructed and refined over time. In contrast, this work explicitly models communication sampling asynchrony, delay, and link noise based on the network configuration. The proposed message-passing mechanism characterizes timing and information flow to refine and time shift global state information, which is then used to incrementally correct the Q-networks. The double Q-network design mitigates overestimation bias, while the shared encoder coupling the actor-critic networks captures inter-agent dependencies. We evaluate our approach in multiple test cases, demonstrate its effectiveness over various baselines, and provide a numerical regret analysis.

Uncrewed aerial vehicles (UAVs) are gaining increasing attention in wireless systems, providing new opportunities to expand the reach and improve the quality of wireless services. Despite their versatility, UAVs are limited by available energy onboard, which results in significant challenges in deploying UAV-enabled wireless systems. Modeling energy consumption is an essential component of the deployment and trajectory optimization of UAVs. This article presents a comprehensive overview of UAV energy consumption models, with a focus on their relevance to wireless systems research. We deliberately exclude data-driven and overly complex models to provide clear and practical guidelines for their use in wireless systems research. We begin by categorizing the most common types of UAVs and describing the typical flight phases considered in the literature. We then review existing energy consumption models, focusing on their scope with respect to UAV types and flight phases. We also discuss common mistakes in the use of these models and highlight the existing gaps in the literature. In particular, we show how the use of a wrong model can lead to significant errors in energy consumption calculations. Finally, we emphasize the need to develop energy consumption models for missing scenarios.

Frequency-modulated continuous-wave (FMCW) lidar conventionally estimates distance and velocity from constant beat frequencies generated through interferometry. Existing FMCW implementations emphasize simple signal processing -- e.g., beat frequency estimation via a fast Fourier transform (FFT) algorithm plus peak-finding -- which results in hardware-focused solutions requiring linear swept-frequency laser sources or linearized resampling. However, the maximum achievable distance by this method is limited by the need to sample the interference signal without aliasing. In this work, we propose two signal processing methods: matched filtering and instantaneous frequency fitting. These two methods can recover larger ranges of distance and velocity by considering the full waveform despite aliasing in the frequency domain. Furthermore, the FMCW lidar signal is often corrupted by phase noise, and we show that the instantaneous frequency fitting approach is more robust than matched filtering by considering the deviation in the phase. We present comprehensive simulation studies along with theoretical analysis using the misspecified Cramér--Rao bound. As these methods are flexible to arbitrary frequency modulation, we also show results for non-linear modulations that could yield better sensitivity to distance and velocity compared to the popular triangular modulation.

Air-sea surface interactions play a critical role in underwater-to-air optical wireless communication (OWC) links, particularly in vertical autonomous underwater vehicle (AUV) to unmanned aerial vehicle (UAV) scenarios, where the stochastic nature of the sea surface introduces optical distortions that impair link reliability. This work investigates the impact of air-sea surface roughness on AUV-to-UAV OWC systems using two experimentally validated models: the classical Cox-Munk and the Elfouhaily-Chapron-Katsaros-Vandemark (ECKV). A tractable analytical representation of the ECKV model is derived and validated against measured sea-state data. Using both analytical and Monte Carlo approaches, the link ergodic capacity is evaluated with particular emphasis on operating range, pointing errors, receiver field-of-view, and solar noise level, providing practical system design insights.

Near-infrared spectroscopy (NIRS) is rapid and non-destructive, but reliable calibration still depends heavily on spectral preprocessing. In routine practice, preprocessing is often selected by large external pipeline searches that are costly, unstable on small calibration sets, and difficult to audit. We introduce operator-adaptive calibration, a framework that moves linear preprocessing selection inside the calibration model. Candidate treatments are encoded as linear spectral operators, while nonlinear or sample-adaptive corrections such as SNV, MSC, and ASLS are handled as fold-local branches to prevent leakage. We instantiate the framework for PLS and Ridge regression. For PLS, covariance identities enable fast NIPALS and SIMPLS variants while preserving original-wavelength coefficients. For Ridge, operator-adaptive kernels yield a dual formulation with recoverable original-space coefficients. The approach was evaluated on more than 50 heterogeneous NIRS datasets against conventional PLS, Ridge, CatBoost, and CNN baselines under documented search budgets. Compact operator-adaptive PLS with ASLS branch preprocessing achieved a median RMSEP/PLS ratio of 0.960 with 42 wins on 57 datasets, while a deployable AOM-Ridge selector improved over tuned Ridge by a median 2.22% with 35 wins on 52 datasets. The proposed models reduce dependence on large preprocessing-HPO campaigns, produce traceable operator choices, retain interpretable coefficients, and fit in seconds for compact AOM-PLS. Operator-adaptive calibration therefore offers a practical route to faster, more robust, and more auditable NIRS method development.

This article analyzes the achievable sum-rate of multiuser uplink segmented waveguide-enabled pinching-antenna systems (SWANs). To unveil system-design insights, an upper bound on the achievable sum-rate is derived, based on which the existence of an optimal segment activation level is theoretically established. Motivated by this result, hybrid segment selection and aggregation (HSS/A) schemes are proposed to jointly optimize segment activation and pinching-antenna (PA) placement. Correspondingly, low-complexity greedy algorithms are developed for the considered optimization problem. Numerical results validate the theoretical analysis and demonstrate that the proposed HSS/A schemes outperform conventional full-segment aggregation.

We prove a regret lower bound for Gaussian-process bandits on a smooth compact Riemannian manifold $\M$ of dimension $d$ with intrinsic Matérn-$ν$ kernel ($ν>d/2$) that exposes how the geometry of the arm space enters the constant. For any algorithm and time horizon $T$ exceeding an explicit threshold, the worst-case expected regret over the RKHS-ball $\|f\|_{\Hil_{k_ν}}\!\le\!B$ satisfies \begin{multline*} \E[R_T(f)]\;\ge\;c_*(d,ν)\,B^{d/(2ν+d)}\,σ_n^{2ν/(2ν+d)} \\ \cdot\,\vol_g(\M)^{ν/(2ν+d)}\,T^{(ν+d)/(2ν+d)}(\log T)^{ν/(2ν+d)}. \end{multline*} The exponent matches the Vakili--Khezeli--Picheny upper bound \cite{vakili2021information}; the $\vol_g(\M)^{ν/(2ν+d)}$ factor is, to our knowledge, the first explicit volume-dependent geometric constant in a manifold GP-bandit lower bound. We extend the analysis in five directions: (i)~a companion Assouad-style proof gives a different lower bound with a strictly smaller $T$-exponent $(2ν+3d)/(4(ν+d))$ but with a polylog factor of the form $1/(\log\log T)^{(2ν+d)/(4(ν+d))}$, sharpening the $(\log T)^{ν/(2ν+d)}$ Fano polylog of Theorem~\ref{thm:main}; (ii)~we prove a $|G|^{1/2}$ upper bound on the regret of an extrinsic-kernel GP-UCB algorithm on a quotient space $\M=\Mt/G$, plus a bracketing theorem (Theorem~\ref{thm:gauge-bracket}); the precise constant is conjectured to take the modulated form $(1+(|G|-1)h(\rinj/κ))^{1/2}$ (Conjecture~\ref{conj:gauge-modulated}), validated numerically on $\SO(3)$; (iii)~we write the leading constant $c_*(d,ν)$ out fully; (iv)~we extract a curvature dependence $1+O(K\eps_T^2)$ via Bishop--Gromov; (v)~we transfer the bound to the Bayesian regret framework via the Yang--Barron / Castillo et al.\ Bayesian-Fano transfer.

In this paper, a sensing-assisted non-line-of-sight (NLoS) identification method for dynamic uncrewed aerial vehicle (UAV) positioning is proposed for the first time. For urban UAV-to-ground scenarios, a new multi-modal sensing-communication integrated dataset is constructed to support line-of-sight (LoS)/NLoS identification, covering two typical urban scenarios and a wide range of flight altitudes. Based on the constructed dataset, a novel dual-input feature fusion network is proposed, which addresses the challenge of heterogeneous representations between RGB images and channel impulse response (CIR) data to enable the joint extraction and fusion of sensing and communication features for LoS/NLoS identification. Simulation results show that the identification accuracy can reach up to 97.69%, while achieving an improvement of at least 3.59% compared to traditional CIR-only and RGB-only methods. Moreover, strong few-shot generalization is observed, as the proposed method stabilizes and approaches full-sample performance with fewer than 200 target samples and exceeds traditional CIR-only and RGB-only methods with fewer than 100 target samples in all cross-scenario and cross-altitude experiments. Even under Gaussian noise with a variance of 0.35 applied to RGB images, the accuracy degradation remains approximately 0.5%. By utilizing the proposed LoS/NLoS identification method, the error of trilateration positioning can be reduced by approximately 70% in a crossroad scenario, verifying the utility of the proposed method.

This paper proposes a novel UAV-to-Vehicle (U2V) channel model for sixth-generation (6G) intelligent sensing-communication integration, based on three-dimensional (3D) scatterer prediction. To explore the mapping relationship between physical environment and electromagnetic space, a new high-fidelity mixed sensing-communication integration U2V simulation dataset under wide-lane scenarios with different vehicular traffic densities (VTDs) and UAV heights is constructed. Based on the constructed dataset, a novel 3D Scatterer Prediction and Distribution Estimation (3D-SPADE) algorithm is proposed, which leverages LiDAR point clouds to accurately predict the spatial distribution of scatterers. Furthermore, the clustering of scatterers and the subsequent classification into dynamic and static types are meticulously designed for highly dynamic U2V scenarios, while reducing computational complexity and improving modeling accuracy. As LiDAR point clouds vary over time, dynamic and static clusters evolve via 3D-SPADE, enabling precise modeling of channel non-stationarity and consistency. Simulation results demonstrate that, in the wide-lane scenario with varying VTDs and UAV heights, the proposed 3D-SPADE consistently achieves high scatterer occupancy detection performance within the voxel grid. In particular, under favorable configurations, recall reaches 93.26%, and precision reaches 95.74%, highlighting the reliability of 3D-SPADE. Key channel statistical characteristics are simulated and analyzed. These characteristics from the simulation experiments are highly consistent with ray-tracing results and exhibit better agreement than with the standardized model and inconsistent model, validating the necessity of exploring the mapping relationship and the effectiveness of the proposed model.

Uniform rectangular arrays (URA), structured non-uniform rectangular arrays (NURA), and parallelogram shaped (UPgA and NUPgA) arrays admit steering vectors that can be expressed as the Kronecker product of azimuth and elevation steering vectors. Accordingly, the full steering matrix can be represented as the Khatri Rao product of the corresponding azimuth and elevation steering matrices. This paper exploits this structure to develop an economical subspace decoupling framework for two dimensional angle of arrival (AoA) estimation. The proposed method first extracts the joint signal subspace from the spatial covariance matrix. Then it applies a low complexity decoupling scheme to recover the column spaces of the azimuth and elevation steering matrices. With the estimated decoupled subspaces, conventional one dimensional algorithms such as MUSIC, root MUSIC, and ESPRIT can be applied independently along each dimension, followed by pairing through a two dimensional spectral function. Monte Carlo simulations show that the proposed approach achieves higher accuracy than state of the art methods, i.e., two dimensional MUSIC, reduced-dimension MUSIC, and two-dimensional ESPRIT, for medium- and large scale arrays while requiring fewer snapshots, consequently with improved spectral efficiency.

Research on sixth-generation (6G) integrated sensing and communication (ISAC) increasingly depends on multimodal datasets. These datasets need to jointly characterize wireless propagation, onboard sensing, and platform mobility. Existing tools cover only part of these aspects. Robotics simulators model physics and perception but not site-specific channels, while ray tracing and link level tools lack vehicle dynamics and onboard sensors. Combining them manually leads to workflows that are fragile and hard to reproduce. Rather than introducing another standalone simulator, this article presents SimART. It integrates mature robotics, ray tracing, and wireless evaluation engines into a single reproducible pipeline. The key idea is a robot operating system (ROS) backbone that both synchronizes and organizes all multimodal streams. A shared clock, a common coordinate frame, and timestamped messages keep the streams aligned in time and space, and a single rosbag recording captures the full session into one reproducible file. This design decouples the sensing front end from the wireless back end, so that any ROS-compatible simulator can be plugged in while reusing the same back end across aerial, ground, indoor, and maritime ISAC settings. On top of this backbone, SimART contributes a scene construction pipeline that converts both OpenStreetMap extracts and user-defined layouts into spatially aligned visual and electromagnetic assets, and a channel knowledge map (CKM) generator that aggregates ray tracing and system level outputs into spatial priors for ISAC algorithms. A case study on vision and position aided beam prediction demonstrates the utility of the platform. The code is publicly available at https://github.com/guchuanv-alt/SimART.

Metasurface-based fluid antenna systems (FASs) have been recently proposed as an inexpensive, scalable and practical alternative implementation for the fluid-antenna concept. This work thoroughly evaluates the performance of metasurface-based FASs in the context of multi-user communications. We extend the state-of-the-art signal model of FASs to electronically-reconfigurable designs, explicitly including the antenna response in the equivalent channel and resulting correlation structure. A general codebook design procedure, accounting for practical aspects like reflections and radiation efficiency, is presented and used to design the different antenna configurations (regarded as FAS ports). Importantly, we show that, with proper design, metasurface-based FASs can significantly outperform conceptual ones. While state-of-the-art theoretical embodiments of FAS rely on spatial flexibility for constructive/destructive interference, metasurface-based FASs exploit interference cancellation through projection onto the interference null space. Numerical results show a remarkable improvement when the system is dominated by interference (i.e., the natural FASs operational regime), regardless of spatial propagation characteristics.

The integration of non-terrestrial networks (NTNs) with terrestrial networks (TNs) is an important step toward ubiquitous connectivity in sixth-generation (6G). Despite growing interest, the geometric impact of urban blockages on an integrated satellite-terrestrial network (ISTN) has not been rigorously quantified. In this paper, we develop a stochastic geometry-based analytical framework that incorporates a Boolean blockage model to characterize the downlink coverage probability of the ISTN and to provide insights for blockage-aware system design. Our analysis reveals that blockages affect satellite links in two competing ways: while they attenuate desired signals, they can also act as spatial shields that suppress aggregate interference. Leveraging this observation, we analytically show that satellite-terrestrial integration can enhance coverage probability across diverse environments ranging from open areas to dense urban deployments, offering a resilient and mathematically tractable approach to maintaining connectivity under heterogeneous blockage conditions.

Beam alignment in mmWave phased arrays and RIS-assisted links is a stochastic bandit under both short TTI budgets and Doppler-induced non-stationarity. The arm space is a Riemannian manifold: $\sphere^2$ for steering, $\torus^n$ for phase combining, $\SO(3)$ for panel orientation, or the discrete torus $(\mathbb Z_B)^M$ with up to $K\!\sim\!10^{90}$ configurations for $B$-level RIS ($B\!=\!2^b$, $b$ bits/element); the intrinsic Matérn kernel of Borovitskiy et al.\ provides the base GP. We contribute two algorithmic pieces. \textbf{(C1)} A Kronecker-factorised intrinsic-product Matérn kernel on $(\mathbb Z_B)^M$ evaluating in $O(M)$ table lookups, making GP-UCB tractable at $K\sim 10^{90}$ where the extrinsic alternative is infeasible. \textbf{(C2)} AdaptiveGP-v2, an online sliding-window controller that selects $W$ by per-sample marginal likelihood, with predictive-variance and drift $z$-score reset triggers and a post-reset $β$-boost. On a four-speed ($v\!\in\!\{0.02,0.08,0.12,0.20\}$~km/h), $20$-seed paired campaign at $T\!=\!3000$, AdaptiveGP-v2 is statistically indistinguishable from the hand-tuned fixed-window oracle at every speed (Holm--Bonferroni-corrected paired differences cross zero); the operational benefit is the absence of a deployment-time per-speed calibration step, not a mean-regret improvement. On four static 3GPP-style mmWave benchmarks, intrinsic-kernel GP-UCB reduces cumulative regret by $25$--$45\%$ vs.\ codebook UCB1/Thompson and by $10$--$33\%$ vs.\ Euclidean-ambient GP-UCB on the toroidal arm spaces; a wideband OFDM ablation on a $100$~MHz channel confirms the advantage persists under frequency-selective fading ($\sim\!32$~Mbps/UE at initial access vs.\ UCB1). A third-party-simulator sanity check on Sionna CDL is reported in Section~V.

We study exact-regenerating codes for entanglement-assisted distributed storage systems. Consider an $(n,k,d,α,β_{\mathsf{q}},B)$ distributed system that stores a file of $B$ classical symbols across $n$ nodes with each node storing $α$ symbols. A data collector can recover the file by accessing any $k$ nodes. When a node fails, any $d$ surviving nodes share an entangled state, and each of them transmits a quantum system of $β_{\mathsf{q}}$ qudits to a newcomer. The newcomer then performs a measurement on the received quantum systems to generate its storage. Recent work [1] showed that, under functional repair where the regenerated content may differ from that of the failed node, there exists a unique optimal regenerating point that \emph{simultaneously minimizes both storage $α$ and repair bandwidth $d β_{\mathsf{q}}$} when $d \geq 2k-2$. In this paper, we show that, under \emph{exact repair}, where the newcomer reproduces exactly the same content as the failed node, this optimal point remains achievable. Our construction builds on the classical product-matrix framework and the Calderbank-Shor-Steane (CSS)-based stabilizer formalism.

Deep learning-based channel state information (CSI) feedback has achieved empirical success in massive multiple-input multiple-output (MIMO) systems. However, existing approaches largely rely on dense artificial neural networks (ANNs), whose computational overhead limits their practical applications. In this article, we exploit bio-inspired spiking neural networks (SNNs) for massive MIMO CSI feedback, referred to as SpikingCSINet, where both the feedback and the main network computations are implemented through spikes. To overcome the information bottleneck of binary spikes in high-dimensional reconstruction, we develop a progressive residual (PR) architecture that exploits the natural temporal dimension of SNNs, encoding successive residuals across time steps to enhance information compactness. Experiments on the COST 2100 benchmark show that SpikingCSINet attains a more favorable performance-efficiency tradeoff than lightweight convolutional baselines. Moreover, it achieves performance competitive with Transformer-based feedback while reducing energy consumption by over $93\%$.

Motor imagery (MI) BCIs are sensitive to EEG artifacts, yet the practical impact of automated artifact rejection on downstream MI decoding performance remains unclear. While most work focuses on decoder design, the contribution of data curation, particularly automated rejection policies, has received comparatively less attention, despite its importance for robust ML pipelines. Here, we propose Fast Automatic Artifact Rejection (FAAR), a lightweight method that computes a compact set of artifact-sensitive features, derives an epoch-level Signal Quality Index, adaptively selects rejection thresholds, and automatically rejects contaminated epochs without requiring prior knowledge of artifact types or manual threshold tuning. We evaluate FAAR on 13 publicly available MI datasets and compare it to a no-rejection baseline, AutoReject, and Isolation Forest. We show rejection effects are strongly subject- and regime-dependent, with the largest gains in low-baseline/low-SNR conditions, so it should be used adaptively. FAAR reduces inter-subject performance variability, an important property for MI-BCI reliability and BCI-illiteracy, without aggressive data removal. Finally, FAAR's lightweight and fully automated thresholding yields consistent rejection behavior across offline curation, training, and online filtering, and supports real-time BCI constraints.

This paper proposes Block-Filtered Long-Context Attention (BFLA), a training-free sparse prefill attention mechanism for long-context inference. BFLA adopts a two-stage design. In Stage 1, query and key sequences are compressed into coarse blocks, and lightweight block-level softmax mass estimation is performed to construct an input-dependent block importance mask. In Stage 2, the coarse mask is expanded to the Triton attention-tile grid. Several tile-level rescue strategies are applied to reduce information loss, where a fused sparse prefill kernel skips unimportant KV tiles while preserving exact token-level attention inside every retained tile. BFLA requires no retraining, calibration, preprocessing, or model modification and can be plugged into existing vLLM-style paged-attention workloads. Experiments on Gemma 4, Llama 3.1, Qwen 3.5, and Qwen 3.6 series models show that BFLA substantially accelerates long-context prefilling with minimal accuracy degradation compared to dense Triton FlashAttention. Project website: https://github.com/Alicewithrabbit/BFLA.

Movable antenna (MA) has recently emerged as a promising paradigm for enhancing wireless communication performance by exploiting spatial degrees of freedom through flexible antenna repositioning. However, most existing designs rely on short-term user-specific instantaneous/statistical channel state information (CSI), which incurs excessive channel estimation overhead and complexity due to frequent antenna movement. To address this issue, this paper proposes a new design framework for antenna position optimization over a much longer timescale based on the cell-level statistical channel information acquired at the base station (BS). To this end, a cell-specific statistical channel model is developed for MA-aided multiuser communication systems, based on which the antenna position optimization framework for maximizing the ergodic system utility is formulated. Then, the covariance-eigenvalues-balancing antenna positions (CEBAP) design is derived to asymptotically approximate optimal solutions by statistically reducing users' channel correlation. Notably, the CEBAP solution solely depends on the BS-side angular power spectrum (APS) of wireless channels for mobile users across the cell, which significantly alleviates the overhead of channel acquisition and antenna movement, and yet remains effective for improving various system utilities over long timescales, such as weighted sum rate and minimum signal-to-interference-plus-noise ratio. Moreover, a low-complexity log-barrier penalized optimization (LOBPO) method is proposed to numerically solve the CEBAP. Simulation results based on realistic urban layouts and ray-tracing channels demonstrate consistent performance gains of the proposed CEBAP over fixed-position antenna systems across different utility functions, which closely approaches the upper bound achieved by instantaneous CSI-based MA optimization for moderately large antenna regions.

In this paper, we propose a low-complexity blind estimator for the average noise power, average signal power, and signal-to-noise ratio (SNR) in millimeter-wave (mmWave) massive multi-antenna uplink systems. In particular, the proposed method is designed to operate using only a single received signal sample, without relying on pilot signals, iterative optimization, or multiple observations, and without requiring prior knowledge of the transmitted signal. By exploiting the inherent sparsity of mmWave channels in the beamspace domain, the estimator identifies noise-dominant components through a sorting-based procedure combined with a finite-difference criterion. This separation is further supported by the order statistics of noise power under Gaussian assumptions, enabling statistically grounded discrimination between signal and noise elements. The average noise power is estimated from the identified noise-only components, and the signal power and SNR are subsequently obtained through simple arithmetic operations. The proposed algorithm achieves low computational complexity and is well-suited for real-time implementation. To demonstrate its practical feasibility, a hardware-efficient very large-scale integration (VLSI) architecture is developed and implemented on a AMD-Xilinx Kintex UltraScale+ KCU116 Evaluation Kit, with corresponding field-programmable gate array (FPGA) results provided. The implementation exhibits low latency and sublinear scaling of hardware resource utilization with respect to the number of antennas, and enables parameter estimation within a duration shorter than a single symbol of conventional wireless systems. Simulation results verify that the proposed estimator achieves high estimation accuracy compared to existing single-sample-based methods.

This paper addresses the challenge of power control in Rate-Splitting Multiple Access (RSMA) systems for downlink Multi-Input Multi-Output (MIMO) networks under practical impairments such as spatial correlation, imperfect Channel State Information (CSI), and residual Successive Interference Cancellation (SIC) errors. We propose a novel degeneracyaware framework that adaptively adjusts the power allocation between the common and private streams, ensuring optimal performance despite CSI uncertainty and imperfect SIC. Our approach incorporates a dynamic switching mechanism between RSMA and Orthogonal Multiple Access (OMA) to maintain system feasibility and resilience in the face of these impairments. Extensive analytical and simulation results demonstrate that the proposed framework significantly enhances power efficiency, mitigates outage probability, and improves overall system robustness, making RSMA a viable and efficient solution for modern wireless networks with realistic CSI and SIC conditions.

We propose a new method for spatial power spectrum estimation in array processing that leverages the Riemannian geometry of Hermitian positive definite (HPD) matrices. We show that conventional approaches minimize variants of the Euclidean distance between the sample covariance matrix and a model covariance matrix, without considering the fact that covariance matrices lie on the Riemannian manifold of HPD matrices. By exploiting this manifold, we present a Riemannian-aware covariance matching algorithm, termed SERCOM, using the Jensen-Bregman LogDet (JBLD) divergence, which, unlike other Riemannian distances, can be evaluated efficiently without eigen-decomposition. We theoretically compare the JBLD divergence to other Euclidean- and Riemannian-based distances, demonstrating robustness to spectral distortions. Experimental results demonstrate that SERCOM consistently outperforms existing methods in direction-of-arrival (DOA) and power estimation, particularly in challenging scenarios with low SNR, limited number of snapshots, and correlated sources.

In this paper, we propose a resource allocation framework for federated learning (FL) in integrated sensing and communication (ISAC) systems, where we consider not only the reliability of model transfer through communication, but also the quality of data acquisition through sensing in the first place. Unlike existing works that assume training data is pre-collected or only impose a fixed sensing signal-to-noise ratio (SNR) threshold to reflect data quality, we explicitly characterize the relationship between sensing data quality (measured by sensing SNR), dataset size, and the upload reliability in FL training, and exploit this relationship to allocate resources between sensing and communication under a shared energy budget. This is non-trivial due to the intricate coupling among sensing data quality, transmission reliability, and communication resource allocation; nevertheless, it enables a principled joint optimization framework that directly enhances learning performance. Specifically, we derive a closed-form convergence upper bound that quantifies the joint impact of these factors on the FL optimality gap. Utilizing this upper bound, the original intractable optimization problem can be reformulated into a tractable resource allocation problem that jointly optimizes the sensing transmit power, number of sensing snapshots, and communication transmit power at each device subject to individual energy budget constraints. To solve the reformulated problem, we propose a two-layer optimization algorithm with linear complexity, where the outer layer employs golden section search and the inner layer solves per-device subproblems with closed-form solutions.

Ray tracing (RT) has emerged as a key tool for propagation channel modeling and network planning. Conventional RT is based on electromagnetic (EM) wave theory and its application relies on detailed mesh-based environment representations and material properties. In realistic environments, limited environmental geometry and material uncertainties hinder its scalability to complex scenarios. In this paper, we propose a novel physics aware neural RT surrogate named PointNeRT to address these limitations. The proposed model directly takes point clouds as environmental input, and efficiently reconstruct multipath without explicitly constructing mesh models or manually defining EM interaction rules. PointNeRT adopts a hop-by-hop modeling strategy guided by physical interaction constraints. It supports sequential prediction of multipath propagation and power attenuation. Numerical results and experiments demonstrate that the proposed method implicitly captures surface normal characteristics and EM material effects. It further achieves robust generalization in mobility scenarios and provides a physics-guided neural modeling of multipath propagation.

Continued progress towards energy-neutral Internet of Things (IoT) nodes expose the wireless communication link as the dominant energy bottleneck. While low-power wide-area network (LPWAN) technologies achieve long-range communication with multiple years of battery life, their active radios hinder reaching full energy neutrality. Long-range backscatter communication emerged as a key enabler, reaching one to three order of magnitude lower power consumption. New advancements leverage concepts from active radio systems such as chirp spread spectrum (CSS) modulation and integrate them on a low-power backscatter tag. This paper presents a comprehensive survey of long-range backscatter communication, using a bottom-up analysis spanning system topologies, hardware architecture, modulation techniques and medium access. Backscatter communication requires different topologies compared to active radios to reach longer communication distances. Different hardware architectures support backscattering a modulated signal with differing complexity, power consumption and spectral efficiency. At the physical layer binary switch-based modulation are well known and provide an easy form of modulation while chirp spread spectrum (CSS)-based modulation gain traction due to their robustness. Medium Access Control (MAC) techniques are examined with a focus on synchronization, concurrency and lightweight feedback mechanisms requiring low-power, low-complexity hardware. Building on these established solutions the paper evaluates the feasibility of long-range backscatter communication in different energy-neutral Internet of Things (IoT) applications. Starting from the available energy budget, harvested through solar, radio frequency (RF) or capacitive harvesting, feasible hardware, modulation and Medium Access Control (MAC) solutions are explored.

This work describes and assesses different methods for estimating the time-of-arrival (TOA) of impact-induced waves in isotropic plate-like structures. The methods considered include threshold crossing (TC), continuous wavelet transform (CWT), short/long term average (SLA), modified energy ratio (MER), and the Akaike information criterion (AIC). Their advantages, limitations, and sensitivities to method-specific parameters are systematically investigated. The assessment is based on synthetic data from transient finite element simulations that are experimentally calibrated with respect to excitation and dispersion characteristics. Wave propagation is monitored using piezoceramic patch sensors bonded to the plate surface, and robustness is evaluated for impacts of varying positions and force profiles, including noise-contaminated sensor signals in order to account for practically relevant measurement conditions. The results show that the methods are capable of detecting the fundamental Lamb wave modes, with nearly all capturing both the symmetric and anti-symmetric mode arrivals under noise-free conditions. In particular, noise primarily impairs the detection of the earliest symmetric-mode arrivals, while meaningful anti-symmetric-mode TOA-estimates can still be obtained by suitable preprocessing or time-frequency analysis. Besides, new contributions to the assessed TOA-estimation methods include a frequency-domain threshold crossing within the CWT framework that improves both robustness and accuracy of TOA-estimation, and the consideration of local minima in the AIC that proves effective for detecting the TOA of the fundamental symmetric mode. Beyond these findings, the research provides practical guidelines and insights into the specific characteristics of each assessed method, supporting accurate and reliable TOA-estimation for applications such as impact localization.

This article proposes an estimate of multiport antenna bandwidth based on a generalization of a single-port Q-factor. The explicit derivation is based on converting the stored energy matrix to its port equivalent and on the port parameters themselves. The work discusses the bandwidth dependencies on feeding and matching. Derived formulas are shown to utilize the total active reflection coefficient and allow for a single-frequency bandwidth evaluation. Examples comprising two different dipole arrays and electrically large patch antenna arrays validate the theory.

Affine frequency division multiplexing (AFDM) has emerged as a promising modulation scheme for doubly selective channels, but its canonical continuous-time realization, referred to herein as piecewise continuous AFDM (PC-AFDM), has been observed to exhibit high out-of-band emission (OOBE) whose mechanism has not been analytically characterized. This paper shows that the underlying cause is frequency wrapping, which introduces internal envelope jumps between AFDM sampling instants and generates a high-frequency spectral tail distinct from ordinary block truncation. To eliminate these discontinuities without altering the inverse discrete affine Fourier transform (IDAFT) output sequence, we propose stepped frequency division multiplexing (SFDM). In SFDM, the instantaneous frequency is kept constant at the midpoint of the wrapped chirp within each sampling interval, while the phase is continuously accumulated across interval boundaries. We prove that, under continuous phase accumulation and without additional phase correction, the midpoint choice is the unique sample-preserving choice for arbitrary chirp-rate parameter. The resulting waveform is continuous within each AFDM block, reduces OOBE, and preserves the standard AFDM modulation matrix, guard-interval structure, and receiver processing. Moreover, under fractional-delay propagation, SFDM mitigates the receiver sensitivity that arises when delayed sampling points fall near wrapping-induced discontinuities in PC-AFDM. Numerical results verify the theoretical tail coefficients, demonstrate OOBE reduction, and show improved receiver robustness in the high-percentile and worst-case regimes. These findings establish SFDM as a spectrally cleaner and more reliable physical layer for AFDM systems.

We unify the discrete Fourier transform (DFT), discrete cosine transform (DCT), Walsh-Hadamard, Haar wavelet, Karhunen-Loève transform, and several others along with their continuous counterparts (Fourier transform, Fourier series, spherical harmonics, fractional Fourier transform) under one representation-theoretic principle: each is the eigenbasis of every covariance invariant under a specific finite or compact group, with columns constructed from the irreducible matrix elements of the group via the Peter-Weyl theorem. The unification rests on the Algebraic Diversity (AD) framework, which identifies the matched group of a covariance as the foundational object of second-order signal processing. The data-dependent KLT emerges as the trivial-matched-group limit; classical transforms emerge as the cyclic, dihedral, elementary abelian, iterated wreath, and hybrid wreath cases. Composition rules cover direct, wreath, and semidirect products. The Reed-Muller and arithmetic transforms appear as related change-of-basis transforms on the matched group of Walsh-Hadamard. A polynomial-time algorithm for matched-group discovery, the DAD-CAD relaxation cast as a generalized eigenvalue problem in double-commutator form, closes the operational loop: the matched group of any empirical covariance is discovered without expert judgment, with noise-aware variants via the commutativity residual $δ$ and algebraic coloring index $α$ for finite-SNR settings. The fractional Fourier transform is treated as the metaplectic $SO(2)$ case with Hermite-Gauss matched basis, and a structural principle relates matched group size inversely to transform resolution. Modern applications (massive-MIMO, graph neural networks, transformer attention, point cloud and 3D vision, brain connectivity, single-cell genomics, quantum informatics) are sketched with their matched groups.

The concept of spatial coupling is among the most significant breakthroughs in coding theory over the past decade. The excellent waterfall and error floor performance of spatially coupled codes has positioned them as promising coding candidates for future communication and data storage systems. This article presents an overview of recent advances in spatially coupled codes. In particular, we first review several representative examples of recently proposed spatially coupled codes and highlight their unique features that make them appealing for different applications. Next, we discuss the useful properties of spatially coupled codes and how to design good spatially coupled codes. The article concludes with some future research directions and open problems.

Channel modeling is fundamental to the analysis, design, and optimization of wireless communication systems, which, however, accurate wireless channel modeling remains challenging, especially given the increasingly complex wireless environments. As an emerging paradigm, 3D Gaussian Splatting (3DGS)-based channel modeling methods achieve accurate wireless radiation field (WRF) reconstruction and high-fidelity spatial spectrum synthesis. However, existing works only consider a single carrier frequency and fail to adapt to wide-range cross-frequency channels. To address this challenge, we propose XFreq-GS, a cross-frequency Gaussian splatting framework for WRF reconstruction. It employs 3D Gaussian primitives with shared geometry and frequency-adaptive radio frequency (RF) attributes to reconstruct cross-frequency WRF, and synthesizes power angular spectrum (PAS) maps for wireless channel modeling. Experiments show that XFreq-GS outperforms state-of-the-art 3DGS-based methods in PAS synthesis and achieves superior cross-frequency generalization. Code is available at https://github.com/KINGAZ1019/XFreq-GS.

We study the problem of estimating a parametric discrete memoryless channel \( p(y \mid x; \boldsymbolθ) \) when the transmitter selects its input distribution \( π\) to maximize mutual information under the true parameter \( \boldsymbolθ^* \). Using only i.i.d.\ observations of the channel output, we aim to jointly estimate the capacity-achieving input distribution \( \boldsymbolπ^* \) and the true channel parameter \( \boldsymbolθ^* \). In general, recovery of \( \boldsymbolπ^* \) and \( \boldsymbolθ^* \) can be challenging. To that end, we propose two efficient algorithms based on the Blahut--Arimoto (BA) optimality conditions: (i) a bilevel fixed-point method and (ii) an augmented Lagrangian method. Empirical results demonstrate that both proposed algorithms successfully recover the true \( \boldsymbolθ^* \) and \( \boldsymbolπ^* \), whereas a naive maximum-likelihood approach that ignores the mutual-information maximization constraint fails to do so.

Reliable adaptive beamforming is critical for large microphone arrays operating in highly dynamic acoustic environments. In scenarios characterized by fast-moving talkers and interferers, the available sample support for estimating the spatial correlation matrix is often snapshot-deficient. This deficiency degrades the White Noise Gain (WNG), leading to severe target signal cancellation. To ensure stable and robust beamforming, we previously proposed an adaptive diagonal loading method that leverages the Kantorovich inequality to guarantee the WNG remains strictly within specified bounds. However, accurately determining the smallest necessary loading level requires calculating the extreme eigenvalues of the spatial correlation matrix, a computationally expensive $\mathcal{O}(M^3)$ operation for large arrays. In this paper, we introduce a highly efficient $\mathcal{O}(kM^2)$ estimation technique using Lanczos iterations to build a small Krylov subspace. By projecting the correlation matrix onto a tridiagonal matrix of dimension $k \ll M$, we extract Ritz values that rapidly converge to the exact extreme eigenvalues. Our evaluations demonstrate that this Lanczos-accelerated approach achieves performance identical to exact Eigenvalue Decomposition (EVD), ensuring optimal interference suppression and strict WNG adherence at a fraction of the computational cost.

The integration of communication and computation is essential for next-generation wireless systems, especially in scenarios demanding massive connectivity and ultra-low latency. Over-the-air federated learning (AirFL), leveraging the superposition nature of wireless channels, enables fast data aggregation, while non-orthogonal multiple access (NOMA) offers spectrum-efficient connectivity. This paper investigates a fluid antenna (FA)-aided hybrid network, supporting hybrid users comprising both AirFL and NOMA participants. The dynamic reconfigurability of FAs offers significant potential for mitigating interference and enhancing network performance by adapting antenna positions in response to changing channel conditions. We consider practical challenges arising from imperfect channel state information (CSI) and residual interference due to imperfect successive interference cancellation (SIC). To jointly evaluate the learning and communication performance, a hybrid rate metric is introduced. Subsequently, we formulate a robust optimization problem that jointly minimizes the aggregation error while ensuring reliable user communication under CSI and SIC uncertainties. This joint optimization is formulated as a non-convex problem, complicated by the intricate interactions between NOMA and AirFL users and the impact of imperfect CSI and SIC. To solve this problem effectively, we reformulate the optimization as a Markov decision process and solve it using a long short-term memory deep deterministic policy gradient (LSTM-DDPG) algorithm, a memory-based approach within the realm of deep reinforcement learning. Simulation results demonstrate the superiority of the proposed FA-assisted approach over fixed-antenna baselines, particularly under imperfect CSI and SIC conditions, in terms of hybrid rate performance.

Surface electromyography (sEMG) is a noninvasive technique widely used to control myoelectric prostheses and other human-machine interfaces. However, the high cost of commercial systems limits accessibility in academic and research environments, especially in developing countries. This study presents a validation protocol for a low-cost eight-electrode sEMG wristband prototype based on IEC 60601 and ANSI/AAMI EC13 standards. The protocol includes electrical safety tests, such as leakage current measurement, insulation evaluation, and continuity verification between electrodes and circuits. Functional performance was evaluated by comparing signals acquired with the prototype against those obtained from a commercial reference device (PortiLab2) using Pearson correlation, Bland-Altman analysis, and mean squared error. Additional tests included signal stability during rest and contraction, UART and Bluetooth communication, frequency response, mechanical characterization of the casing, and user comfort assessment. Results showed leakage currents between 11.4 uA and 13.5 uA, adequate insulation, stable signal acquisition, and high correlation with the reference system (r > 0.85). Reliable wireless transmission without packet loss was also observed. Limitations included power supply constraints during wireless testing and discrepancies in the frequency response at high-gain stages compared with simulations. Mechanical tests showed elastic behavior of the casing under loads up to 98 N. The proposed protocol provides a practical and reproducible framework for the technical and functional validation of low-cost sEMG systems for research and educational applications.

Designing the sensing architecture for large-scale spatio-temporal systems is hard when accuracy requirements are specified but sensor models are uncertain or unavailable. Classical design treats sensor placement and estimation sequentially, requiring valid forward models for each sensing modality. This paper inverts the design flow: given an error budget, synthesize the measurement likelihood that enforces it while injecting minimal information beyond the dynamical prior. The likelihood is constructed by constrained optimization: among all posteriors satisfying a prescribed accuracy bound relative to a target, select the one minimizing Kullback-Leibler divergence from the prior. The solution is a maximum-entropy posterior in relative-entropy form, and the induced likelihood is the Radon-Nikodym derivative. The framework accommodates arbitrary discrepancies and is instantiated for Wasserstein distance, maximum mean discrepancy, $f$-divergences, moment constraints, and hybrid metrics. For each, we derive the discrete particle-level problem, analyze its convex or convex-relaxed structure, and present solvers with complexity scaling. A closed-form solution exists for the symmetric exponential-tilt case, and a distillation procedure converts nonparametric likelihood samples into parametric forms. A two-layer sensor design architecture embeds the synthesized likelihood in the recursive predict-update loop, connecting accuracy budgets to physical sensor placement, precision, and configuration. Numerical experiments comparing four metrics on unimodal and multimodal scenarios confirm the accuracy constraints are reliably enforced and reveal how metric choice determines the amount and spatial distribution of injected information.

In this paper, we present a two-layer architecture for bearing-only sensor placement that improves upon classical D-optimal design. The first layer reweights particles by minimizing Kullback-Leibler divergence from the current distribution subject to a distributional accuracy bound, concentrating mass on regions where the posterior is likely to settle, without reference to the sensor model. The second layer performs D-optimal sensor placement with respect to the reweighted Fisher information matrix, steering sensors toward geometrically informative configurations. Because the two layers are structurally decoupled, the reweighting generalizes across sensing modalities while the placement remains specific to bearing geometry. Systematic experiments on multi-source localization at two noise levels show that this reweighting reduces localization error on average, with the benefit growing as the sensor-to-source ratio increases and as measurements become more informative. The improvement is established in the first few iterations of the sequential procedure and persists as the posterior concentrates.

We reformulate the definition of privacy in the private information retrieval (PIR) problem to accommodate flexible privacy requirements. We focus on graph-replicated PIR, with a generalized privacy requirement, instead of requiring all messages to be private from all servers, during retrieval. Towards this, we define a privacy requirement set for each server, which can be an arbitrary subset of all message indices, as long as the stored message indices are in their privacy requirement set. Since both the storage and privacy requirement sets have many possibilities, we focus on two specific storage settings, namely the path and cyclic graphs. We consider several privacy settings for each of them, which are not necessarily the same, to give different examples for privacy sets. Of particular interest are the privacy sets that comprise the indices of messages stored at servers within a neighborhood range. The neighborhood range parameter allows a transition from the recently introduced local PIR [1] to the standard graph-replicated PIR. In these cases, we derive bounds on the capacity or find the exact capacity.

We rethink the definition of privacy in multi-server, graph-replicated private information retrieval (PIR) systems, and introduce a novel setting where the user's privacy is governed by the servers' storage structure. In particular, while retrieving a message from a server, the user is concerned with hiding their desired message index from the server, only if the server stores the corresponding message. We coin this privacy requirement as local user privacy and the resulting PIR problem as local PIR on the graph. Our goal is to measure the gain in communication efficiency of local PIR, compared to that of canonical PIR, by establishing its capacity, i.e., the maximum number of message symbols retrieved, per downloaded symbol. To this end, we observe a remarkable gain in the local PIR capacity of graphs, that are disjoint union of distinct graphs, which is multiplicative, compared to the PIR capacity, when the individual graphs are identical. For connected graphs, we propose schemes to establish capacity lower bounds for edge-transitive and bipartite graphs, which are greater than the best-known PIR capacity bounds. Finally, we derive the exact local PIR capacity for the cyclic graph, and the path graph with an odd number of vertices.

This thesis develops a theoretical framework to evaluate the monitoring capability of IoBNT networks. We consider a scenario in which nanosensors passively flow in the bloodstream and detect biomarkers associated with potential diseases, reporting their detections to external gateways on the skin that host a monitoring device. The nanosensors thus realize an artificial point-to-point communication channel between the disease region and the monitor: some packets reach the destination directly, while others are lost through vessel paths that bypass the gateway. We evaluate the network's monitoring capability over this artificial channel using the \ac{AoI} concept, which jointly integrates sample generation (at the disease region), carrying (nanosensor travel through vessels), and delivery (nanosensor-to-gateway) as random events. These are modeled through (i) a Markov model that follows cardiovascular physiology and (ii) channel models of reported nanocommunication technologies. We compute the Markov transition probabilities using a cardiovascular simulator built as a low-complexity electric circuit model of the human vessels. For the nanosensor-to-gateway link, we model two well-known schemes: ultrasonic and terahertz channels. Integrating these components within the \ac{AoI} framework, we report information freshness via the average \ac{PAoI} metric. Under realistic physiological and communication assumptions, fresh information appears on the monitor within tens of seconds. The network is therefore suitable for monitoring tissue-level processes such as bacterial infections, while more adequate architectures are needed to monitor cellular-scale processes, which occur on timescales below tens of seconds.

This paper introduces a proactive Unmanned Aerial Vehicle (UAV) mobility management xApp for Open Radio Access Network (O-RAN) Near Real-Time Radio Intelligent Controller (Near-RT RIC) environments, employing Double Deep Q-Network (DDQN) reinforcement learning (RL) enhanced with transfer learning to optimise handover decisions for UAVs operating along predetermined flight trajectories. Unlike reactive approaches that respond to signal degradation, the proposed framework anticipates network conditions and minimises both outage probability and handover frequency through predictive optimisation. The system leverages centralised weight averaging to consolidate knowledge from multiple flight scenarios into a global model capable of generalising to previously unseen operational environments without extensive retraining. A comprehensive evaluation demonstrates that the proposed framework achieves a favourable trade-off between handover frequency and connectivity reliability, reducing handover events by up to 54.6% compared to greedy approaches while maintaining outage probability at practically negligible levels. The results validate the effectiveness of intelligent learning-based approaches for UAV mobility management in next-generation O-RAN architectures, thereby contributing to seamless integration of aerial user equipment into cellular networks.

This paper proposes the joint design of reconfigurable intelligent surfaces (RIS) and zero-forcing (ZF) precoding for the downlink (DL) multiuser multiple-input single-output (MU-MISO) setup in millimeter-wave (mmWave) bands, where ZF is particularly attractive due to its ability to suppress inter-user interference by exploiting the large antenna arrays and sparse directional channels characteristic of mmWave systems. This ensures efficient spatial multiplexing with manageable complexity, making ZF a practical and in modern 5G/6G deployments. However, a careful design is necessary to overcome potential rank deficiency in the channel matrix. For the MU-MISO case, rank deficiency may arise if users exhibit significantly different channel gains or if, being in far-field, they are aligned with the position of the transmitter. On the other hand, the deployment of a RIS introduces artificial scattering which can shape the radio environment to address those situations. We explore the joint design under perfect channel knowledge, assess the impact of imperfect channel estimation on the bit error rate (BER) and propose a robust design of pilot transmissions that equalizes multiuser interference across users in the presence of channel errors in the precoder design. This evaluation shows the advantages of optimized RIS-aided ZF MU-MISO communication for the DL of wireless systems.

Integrated Sensing and Communications (ISAC) is emerging as a key paradigm for future Sixth-Generation (6G) networks, with communication-centric designs favored for their compatibility with existing standards. Communication signals contain both known deterministic pilot symbols and unknown random data payloads. Most localization approaches rely solely on pilots, discarding the position information contained in the data symbols, which constitute the majority of each transmitted frame. Alternatively, Decision-Directed (DD) approaches exploit data decisions, thereby inherently limiting positioning performance to that of the communication system. In this paper, we derive a Marginal Maximum Likelihood (MML) estimator that jointly leverages pilot and data payloads without requiring data decoding, enabling operation with high-order constellations and under challenging noise conditions. We consider an opportunistic scenario in which an Orthogonal Frequency-Division Multiplexing (OFDM) signal transmitted by a User Equipment (UE) is captured by a distributed receiver array. Through numerical simulations, we demonstrate that the proposed method achieves superior localization performance compared to existing approaches and consistently converges to the genie bound (where data symbols are assumed perfectly known) at a lower Signal-to-Noise Ratio (SNR) than any DD method. Furthermore, the proposed method remains robust to constellation size, unlike DD approaches, whose performance degrades with increasing modulation order. Finally, we provide a computational complexity analysis of the proposed method and the considered baselines, highlighting the impact of system parameters on their respective computational costs.

This paper studies the robustness of type-based multiple access (TBMA) in over-the-air computation (AirComp) under nonparametric estimation, where no prior knowledge of the data distribution is available. While conventional AirComp approaches rely on amplitude modulations and suffer from noise sensitivity, TBMA enables the use of more structured modulation formats that can be exploited for improved performance. We show that the superposition of transmitted signals in TBMA induces a discrete lattice structure in the received signal space, where each lattice point corresponds to the number of devices accessing a given channel resource. By exploiting this structure through nearest-lattice-point projection, noise effects can be substantially suppressed. The proposed technique achieves an exponential decay of the mean squared error (MSE) with respect to the energy-to-noise spectral density ratio, whereas in conventional techniques the MSE only scales inversely with this ratio. Simulation results validate the theoretical findings and demonstrate that TBMA provides a fundamental robustness advantage over traditional AirComp.

Min-Sum (MS) decoding is a popular low-complexity alternative to belief propagation (BP), retaining only the minimum incoming message magnitude during check-node (CN) processing, at the cost of systematic message magnitude overestimation. The scaled MS (SMS) decoder compensates for this effect using a fixed scaling factor. We propose the syndrome adaptive gain Min-Sum (SAGMS) decoder for quantum low-density parity-check (QLDPC) codes, which adapts the message gain online based on the fraction of unsatisfied stabilizers, requiring no per-code or per-noise level optimization. We show that the scaling factor required for SMS to match belief propagation decreases with the CN degree, so any fixed scaling optimized for one degree incurs into a growing penalty as the CN degree varies. SAGMS avoids this limitation by adapting the gain during decoding. Simulations on generalized bicycle QLDPC codes demonstrate that SAGMS matches or outperforms the frame error rate (FER) of an offline optimized SMS decoder. Moreover, SAGMS approaches BP performance and, under certain conditions outperforms it while retaining MS-level complexity.

Ray tracing (RT) has recently gained renewed interest in wireless communications, driven by its integration into digital twin (DT) frameworks for site specific channel modeling. Several previous studies have validated RT at the channel level, yet how these errors propagate into real 5G system level key performance indicators (KPIs) on actual hardware remains unquantified. This paper addresses this gap by comparing Sionna RT simulated channels against vector network analyzer (VNA) measured channels using an OpenAirInterface (OAI) 5G NR testbed. Channel measurements are conducted at 20 receiver positions in an indoor laboratory, with both channel types injected into a hardware in the loop channel emulator interfacing an OAIBOX MAX base station and a Quectel UE. RSRP, PUCCH SNR, and SINR are evaluated under both conditions. The results identify antenna near-field transition effects as a critical position-dependent error source, alongside material property mismatch, providing a quantitative benchmark for digital twin-based 5G and beyond network planning.

In this paper, we develop a communication-oriented complex baseband equivalent model for superheterodyne Rydberg atomic quantum receivers (RAQRs). The model explicitly captures photodetection-induced signal-dependent shot noise and its coupling with the optical operating point. By leveraging an atomic superheterodyne architecture and a strong local oscillator, we construct a complex baseband representation for both the received signal and the signal-dependent shot noise under both direct incoherent optical detection and balanced coherent optical detection. The derived model reveals that the optical operating point jointly determines the normalized effective receive gain and the equivalent noise background, thereby establishing a traceable gain-noise tradeoff governed by system design. More importantly, the proposed model shows that neglecting signal-dependent shot noise may lead to inaccurate operating-point design. Finally, by extending to the multiple-input-multiple-output (MIMO) case, we derive a lower bound on the achievable rate while considering the signal-dependent shot noise. Our analysis \textcolor{black}{reveals} that the non-zero asymptotic rate of RAQ-MIMO and its superiority over conventional RF-MIMO hinge on the normalized noise floor of the RAQ receive chain falling below that of RF MIMO. Simulation results validate our analysis and yield practical, closed-form design guidelines for RAQR front ends, revealing parameter regimes in which RAQ-MIMO outperforms conventional MIMO systems.

Accurate channel estimation remains challenging in high-mobility wireless systems because Doppler shifts induce severe inter-carrier interference (ICI) in Orthogonal Frequency Division Multiplexing (OFDM). We propose an unsupervised online channel estimation framework based on Implicit Neural Representation (INR). Unlike discrete-grid estimators, the proposed method decouples channel representation from the OFDM sampling resolution by modeling the time-varying frequency-selective channel as a continuous function of time-frequency coordinates. A Sinusoidal Representation Network (SIREN) with Gaussian Fourier feature mapping captures fine-grained channel variations and high-frequency details without offline pre-training or labeled data. For each received slot, the network parameters are updated by per-slot online fitting that minimizes a physics-aware ICI loss, while a confidence-aware decision-directed loop balances reliable pilots and dynamically harvested pseudo-pilots. Simulations in realistic Vehicle-to-Everything (V2X) environments show that the proposed method achieves near-optimal link-level reliability, significantly outperforming Least Squares (LS) and robust Linear Minimum Mean Square Error (LMMSE) estimators. Compared with supervised deep learning baselines, it also exhibits strong out-of-distribution (OOD) robustness under environmental distribution shifts, establishing an adaptable data-efficient physical-layer paradigm.

This paper introduces and analyzes Spatial Phase Manifold Communications (SPMC), a paradigm that facilitates joint communication and sensing (JCAS) over Local Oscillator (LO) free receiver. Information is embedded in, and recovered from, the relative spatial phase between antennas. In contrast to conventional coherent receivers that rely on LOs and on channel estimation/equalization, SPMC exploits antenna-domain correlation to form a baseband observable that is a function of inter-antenna phase differences. Since these phase differences are fundamentally tied to Direction-of-Arrival (DoA) and vice-versa, the formulation recasts communication and sensing as inference over the unit-circle manifold and thus naturally supports JCAS decomposition, i.e., data and spatial sensing are encoded and recovered through DoA signatures. We develop a comprehensive framework comprising: (i) a manifold-domain signal model and corresponding phase-alphabet design; (ii) an LO-free quadrature spatial-correlator receiver architecture that resolves the phase-sign ambiguity without requiring an LO; and (iii) an analysis of error probability and sensing precision, including robustness to phase noise. The proposed paradigm is particularly suited to massive Internet-of-Things (IoT) deployments, for which hardware simplicity, LO distribution cost, power consumption, and seamless sensing integration are critical, especially at millimeter-wave and higher carrier frequencies.

The applications of Digital Twins (DT) and Generative AI (GenAI) have demonstrated their capabilities in modeling and learning-based wireless communications. However, their joint potential for proactive wireless system design remains largely underexplored, particularly in extremely large-scale multiple-input multiple-output (XL-MIMO) networks, characterized by hybrid near-field (NF) and far-field (FF) propagation regimes. In this work, we propose an integrated GenAI-enhanced DT framework for proactive interference management in dynamic indoor scenarios. The DT constructs a high-resolution, site-specific virtual replica of the deployment environment, understanding where and why blockage occurs within a realistic 3D representation of the indoor space. Integration of the GenAI module further assists the framework in anticipating and proactively suppressing blockage, rather than reacting after the disruption occurs. Extensive simulation results based on Sionna ray-tracing datasets demonstrate that the proposed framework achieves significant improvements in interference suppression, signal-to-interference-plus-noise ratio (SINR), and outage probability compared to conventional reactive schemes and purely deterministic DT-based approaches.

Fingerprinting-based localization often suffers from poor cross-environment generalization, especially when only a few labeled samples are available in the target environment. Existing methods mitigate distribution shifts through domain adaptation or improved signal representations, but they usually ignore environmental geometry or use it in a deterministic manner, limiting their ability to capture diverse multipath variations in complex propagation conditions. To address this issue, we propose EnvCoLoc, an environment-conditioned diffusion meta-learning framework for few-shot fingerprinting localization. EnvCoLoc extracts structured descriptors from 3D point clouds and uses them to condition a latent diffusion generator, which produces environment-specific parameter offsets to modulate a shared meta-learned initialization. This design injects geometry-aware priors into the adaptation process and provides more informative initializations for new environments. To learn the stochastic mapping from coarse environmental descriptors to high-dimensional parameter corrections under limited data, the diffusion generator and localization network are jointly optimized within a two-loop meta-learning framework. The generated offsets capture systematic environment-dependent variations, while gradient-based inner-loop adaptation further refines the model to reduce residual task-specific mismatch. We also provide an excess-loss analysis for finite-step adaptation, theoretically supporting the benefit of geometry-aware initialization. Real-world experiments show that EnvCoLoc consistently improves localization accuracy over baseline methods, achieving up to a 20.0% reduction in mean localization error in NLOS scenarios with only 10 support samples.

Directional antenna systems are gaining substantial traction for aerial networks due to their higher gain, extended transmission range, and enhanced security. However, the requirement of beam alignment makes the task of finding and reaching neighbors challenging, particularly in a mobile setting. For wireless networks, privacy concerns play an equally critical role. However, the problem of ensuring network-wide connectivity while maintaining limited exposure when probing around is still unexplored. We address this trade-off by proposing an adaptive transceiver selection protocol based on the Deep Q-Network (DQN) framework. Each node acts as an independent DQN agent and interacts with the environment to learn how to balance the trade-off. Since the directional nodes operate only based on local observations, we adopt a weighted mechanism that guides them in prioritizing either high reachability or privacy by adaptively tuning the probing patterns. Results show that DQN framework surpasses the Random and Q-Learning baselines. Weights favoring discovery provide higher probing efficiency and reachability, while weights prioritizing privacy ensure limited exposure at the cost of low reachability, eventually attaining higher objective value.

Emergency communications increasingly rely on remote visual inference for timely hazard detection under stringent bandwidth and latency constraints. However, conventional UDP-based visual delivery typically performs inference only after the full payload has been received, even though partially received packet blocks may already contain sufficient task-relevant evidence for reliable decision making. This paper proposes a utility-aware progressive inference framework for emergency communications, which operates directly on UDP packet blocks and determines when sufficient task value has been accumulated for early hazard recognition. Specifically, the sender estimates packet-level decision utility as lightweight control metadata, while the receiver progressively updates partial observations, accumulates the utility of received packets, and triggers an early stop once the normalized utility exceeds a prescribed threshold. Experiments on a fire-scene detection dataset show that, at the main operating point, the proposed method reduces the average packet budget by 34.2% and the decision delay by 1209.17 ms while retaining 91.5% of the full-reception match rate. The method also maintains its advantage over the stability-based baseline under moderate packet loss and different packet-arrival orders. These results demonstrate that packet-level utility provides an effective basis for communication-efficient and delay-aware hazard recognition over UDP-based emergency links.

With the enlargement of antenna apertures in 6G Terahertz (THz) communications, the Rayleigh distance expands significantly, rendering near-field propagation a dominant scenario in THz links. Beyond conventional Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) conditions, quasi-LoS scenarios with partial obstructions have emerged as a critical challenge. Airy beams offer a promising solution to circumvent obstacles due to their unique curving trajectory. However, existing Airy beam training methods typically rely on parameter-based sampling or exhaustive search, leading to significant pilot overhead and low training efficiency. In this paper, an efficient Airy beam training framework is proposed to address this research gap. First, the theoretical bounds of Airy beam generation under finite apertures to prune physically invalid codewords are derived. Based on this, a two-stage Non-Uniform Polar Codebook (NUPC) design is presented, utilizing a probing mechanism to resolve the bending direction and a polar-domain spatial sampling strategy to generate Airy beams. To address ultra-low latency requirements, a Fast-Scanning 1D Codebook (FS1C) is further developed that sweeps the entire LoS region with minimal codewords. Simulation results demonstrate that NUPC achieves a higher average spectral efficiency (SE) by 13.4 bit/s/Hz while reducing training overhead by 54.2% compared to the state-of-the-art hierarchical focusing-Airy codebook (HFAC). Furthermore, FS1C reduces overhead by 92.9% with only a marginal 0.3 bit/s/Hz reduction compared with HFAC.

Performance analysis of low Earth orbit (LEO) satellite-to-ground optical links relies on composite fading models that typically evaluate scintillation and angular loss under the assumption of statistical independence. While ensuring analytical tractability, this assumption decouples fading mechanisms driven by the same atmospheric turbulence and fails to capture the distinct effects of free atmosphere (FA) and boundary layer (BL) perturbations. To model this coupling while preserving tractability, this paper develops a state-coupled joint fading model. In the proposed framework, aperture-averaged scintillation and effective angular loss are jointly characterized by a discrete slow atmospheric state, parameterized by separate FA and BL scaling factors. By replacing unconditional independence with state-conditioned independence, the model enables a closed-form derivation of the outage probability, preserving the computational simplicity of the independent baseline. Numerical results show that the independent baseline can misestimate outage under non-nominal layered turbulence states. This outage prediction bias varies with elevation because the relative roles of scintillation and angular loss change with the link geometry, resulting in different residual angular correction requirements for a given outage target.

Purpose: To develop a fast, general-purpose framework for voxelwise noise characterization in linear and nonlinear iterative MRI reconstructions, recovering the image-domain noise variance from which SNR, $g$-factor, and related image-quality metrics are derived. The framework addresses both the intractability of closed-form formulas beyond Cartesian sampling and the long runtime of Pseudo Multiple Replica (PMR) methods. Methods: We propose PICO (Probing Image-space COvariance), an estimator that operates in the image domain by probing the image-domain noise covariance operator -- or, for nonlinear compressed-sensing reconstructions, the Jacobian of the converged solution -- with random probe images. Complex random-phase probes are shown theoretically and empirically to minimize estimator variance compared with Gaussian or real-valued alternatives. PICO was validated against analytical benchmarks and high-replica PMR references using retrospective Cartesian knee data ($R=2$), prospective non-Cartesian spiral brain phantom data ($R=2,3,4$), and compressed-sensing knee reconstructions ($R=2$). Results: In Cartesian experiments, PICO accurately reproduced analytical SENSE $g$-factor maps. In non-Cartesian spiral imaging ($R=2$), it achieved 1% estimation error in 64 s compared with 462 s for PMR (approximately 7.2x speedup), with the efficiency advantage persisting at higher acceleration. For nonlinear compressed sensing, the Jacobian-based estimator produced noise maps consistent with PMR while converging faster (52 s vs. 95 s; approximately 1.8x speedup). Conclusion: PICO provides a computationally efficient alternative to PMR for voxelwise noise and $g$-factor estimation across generalized iterative MRI reconstructions. By reusing existing reconstruction primitives, it enables voxelwise noise maps to be produced as a routine by-product of the reconstruction pipeline.

This manuscript reviews theoretical results and applications related to quadratic forms in Gaussian random variables. It summarizes definitions, canonical representations, exact and approximate distributional results, numerical inversion methods, applications, and selected open problems for real and complex quadratic forms, multiforms, and ratios of quadratic forms.

This paper presents field observations of medium-wave (MW; 300 kHz-3 MHz) radio signals propagating in the subsurface rock environment of the Nanatsuo-guchi quarry, an underground Shakudani Ishi excavation site on Mt. Asuwayama in Fukui City, Japan. MW broadcast signals from a nearby local station (JOFG, 927 kHz, 5 kW), received mainly as a surface wave, and from a distant station (JOAB, 693 kHz, 500 kW), received via ionospheric reflection, were successfully received deep inside the quarry, whereas very-high-frequency frequency-modulated (FM) broadcast signals attenuated rapidly and became undetectable near the entrance. This contrasting behavior highlights the strong wavelength dependence of electromagnetic-wave propagation in subsurface environments. Two-axis rotation measurements were performed using loop antennas to analyze the arrival direction and angular dependence of the received signals. In addition to the horizontal magnetic field component (Hx), dominant near the ground surface, a vertical magnetic field component (Hz) was consistently observed inside the quarry. The relative contribution of Hz increased with depth and was accompanied by systematic variations in the apparent arrival direction. Inclination measurements further revealed a characteristic minimum in reception sensitivity near 40-50 degrees, suggesting a composite magnetic field structure involving both Hx and Hz. These observations cannot be fully explained by conventional surface-wave propagation models based on the Zenneck-Sommerfeld formulation, and instead suggest the formation of a characteristic electromagnetic field structure under subsurface boundary conditions. This study provides experimental evidence for previously unreported MW field behavior in underground spaces and offers new perspectives for subsurface communication and disaster-resilient information systems.

Addressing the increasing and diversified demands of multicast and broadcast services require highly efficient multicast and broadcast technologies. Broadcast networks, such as Advanced Television Systems Committee 3.0 (ATSC 3.0), are inherently designed to support these services and continue to evolve to meet growing performance and scalability requirements. At the same time, smartphones are increasingly used for video streaming and other high-volume services, placing growing pressure on mobile network capacity. Interworking between broadcast and mobile networks is therefore an important enabler for efficient and seamless service delivery. In this context, Broadcast-to-Everything (B2X) extends ATSC 3.0 to support enhanced interoperability with Third Generation Partnership Project (3GPP) mobile systems while maintaining low cross-correlation with ATSC 3.0 bootstrap signals, supporting reliable system identification in scenarios where multiple waveforms may be present. Bootstrap signaling, which enables initial signal detection and synchronization, is a key feature of ATSC-based waveform discovery and synchronization, and B2X further extends this capability through a scalable bootstrap framework supporting a range of bandwidth configurations. This paper investigates system discovery through bootstrap signal detection at the B2X receiver and presents key design-related findings, including parameter selection and cross-testing with ATSC 3.0. We present extensive simulations of the receiver performance under diverse propagation and mobility conditions, ranging from stationary to high-speed scenarios. The results demonstrate the robustness of the B2X bootstrap signaling design across a broad range of channel conditions relevant to multicast and broadcast operation.

We present a new mechanism for long-range entanglement (LRE) in strongly symmetric many-body mixed states that does not rely on symmetry anomalies or long-range correlations. Our primary example is the maximally mixed state in the translation-invariant subspace on a one-dimensional ring. This state is LRE because translationally symmetric short-range entangled states span a subspace whose dimension grows only polynomially with system size, whereas the full translation-invariant subspace grows exponentially. We further discuss certain unconventional properties of this state, including logarithmically growing conditional mutual information, strong-to-weak spontaneous symmetry-breaking, and Rényi-index-dependent operator-space entanglement. We also construct a geometrically non-local Lindbladian to stabilize this state as the steady state. Our results identify dimensional mismatch as a novel route to LRE that is intrinsic to many-body mixed states.

We show by a counting argument that even though translation symmetry admits symmetric short-range entangled (SRE) eigenstates, there are not enough such SRE eigenstates to span the zero momentum sector. This means that the fixed point strong-to-weak spontaneous symmetry breaking state of translation symmetry is long-range entangled: it cannot be written as a mixture of SRE states. This is a subtle form of long-range entanglement in mixed states that cannot be detected by long-range connected correlation functions.

We investigate realizations of (1+1)-dimensional fusion category symmetries on tensor-product Hilbert spaces, allowing for mixing with quantum cellular automata (QCAs). It was argued recently that any such realizable symmetry must be weakly integral. We develop a systematic analysis of QCA-refined realizations of fusion categories and prove two statements. First, we show that, under certain physical assumptions on defects, any QCA-refined realization has QCA and symmetry-operator indices determined by the categorical data, up to the freedom of redefining the symmetry operators. Second, we construct a lattice model that provides a QCA-refined realization for any weakly integral fusion category symmetry on a tensor product Hilbert space. We also compute indices of the QCAs in our lattice model and show agreement with the first result. As an application of the general construction, we give an explicit QCA-refined realization of general Tambara-Yamagami categorical symmetries.

The performance of quantum resource manipulation protocols, including key examples such as distillation of quantum entanglement, is measured in terms of the rate at which desired target states can be produced from a given noisy state. However, to achieve optimal rates, known protocols require precise tailoring to the quantum state in question, demanding a perfect knowledge of the input and allowing no errors in its preparation. Here we show that distillation of quantum resources in the framework of resource non-generating operations can be performed universally: optimal rates of distillation can be achieved with no knowledge of the input state whatsoever, certifying the robustness of quantum resource distillation. The findings apply in particular to the purification of quantum entanglement under non-entangling maps, where the optimal rates are governed by the regularised relative entropy of entanglement. Our result relies on an extension of the generalised quantum Stein's lemma in quantum hypothesis testing to a composite setting where the null hypothesis is no longer a fixed quantum state, but is rather composed of i.i.d. copies of an unknown state. The solution of this asymptotic problem is made possible through new developments in one-shot quantum information and a refinement of the blurring technique from [Lami, arXiv:2408.06410].

Using the post-Newtonian effective field theory (PN-EFT) formalism for spinning gravitating bodies, we derive the next-to-leading-order (NLO) spin-orbit potential and Hamiltonian for a system of N spinning bodies in general relativity. This extends the EFT treatment of the binary case to arbitrary N. We present two derivations: one in the generalized canonical gauge, and one based on the covariant spin supplementary condition (SSC), followed by a noncanonical transformation to canonical variables. In both approaches, the only new contributions beyond the binary case are three-body interaction diagrams. The canonical Hamiltonians obtained from the two EFT routes agree with the known ADM N-body Hamiltonian of Hartung and Steinhoff up to a canonical transformation.

We show that the low-energy states of non-Abelian topological orders possess extensive magic which is long-ranged, and cannot be eliminated by a constant-depth local unitary circuit. This refines conventional notions of complexity beyond the linear circuit depth which is required to prepare any topological phase, and provides a new resource-theoretic characterization of topological orders. A central technical result is a no-go theorem establishing that stabilizer states--even up to constant-depth local unitarie--cannot approximate low-energy states of non-Abelian string-net models which satisfy the entanglement bootstrap axioms. Moreover, we show that stabilizer-realizable Abelian string-net phases have mutual braiding phases quantized by the on-site qudit dimension, and that any violation of this condition necessarily implies extensive long-range magic. Extending to higher spatial dimensions, we argue that any state obeying an entanglement area law and hosting excitations with nontrivial fusion spaces must exhibit extensive long-range magic. This applies, in particular, to ground-states and low-energy states of higher-dimensional quantum double models.

The possibility of laser cooling and the presence of closely spaced rovibrational doublets make polyatomic molecules an attractive platform for the $\mathcal{P}$, $\mathcal{T}$-violation searches. We study the spectrum of the lowest rovibrational state of the AcOCH$_3+$ symmetric top molecule. The electronic structure full-electron computation was performed within a relativistic coupled cluster method with double and perturbative triple excitations. The rovibrational wavefunctions are obtained using a coupled channel technique, taking into account all rovibrational effects and anharmonicities of the potential. As a result, the vibrational frequencies, as well as the values of the electric dipole moments for the rovibrational states, were computed.

Independent and identically distributed (i.i.d.) states are ubiquitous in quantum information theory. However, in a practical setting, the i.i.d. assumption is too stringent, and possibly not realistic. A physically more compelling class of 'almost i.i.d.' sources was recently proposed by [Mazzola/Sutter/Renner, arXiv:2603.15792]. In this paper, we introduce two alternative definitions of almost i.i.d. states, based on the normalised quantum Wasserstein distance and on the idea of looking at the average $k$-body marginal. We explore some basic properties of these notions and prove a strict hierarchical relation among them, with Mazzola et al.'s notion being the strictest, the one based on $k$-body marginals the loosest, and the one based on the quantum Wasserstein distance in between. Strict separation is established by means of explicit examples.

Characterizing large quantum systems with minimal assumptions is a central challenge in quantum information science. Self-testing provides the strongest form of certification by identifying the underlying quantum state solely from observed measurement statistics. However, existing self-testing methods for generic $n$-partite states face a scalability barrier, requiring exponentially many samples in the system size. In this work, we overcome this barrier by introducing a protocol that robustly self-tests almost all $n$-qubit states with only polynomial sample complexity. The key ingredient is an efficient scheme for device-independently evaluating multipartite Pauli measurements, which can be implemented using only a linear number of ancillary Bell pairs together with standard projective and Bell measurements, well within the reach of current quantum technology. Beyond self-testing states, our scheme provides a general framework for implementing a wide range of learning and certification protocols in the device-independent setting, thereby opening a scalable route to device-independent quantum information processing in large-scale quantum networks.

Classifying interactions is key in the physical sciences, and bonding mechanisms in matter-antimatter systems remain particularly enigmatic. Here we focus on a paradigmatic example of positronium hydride (PsH) dimer composed of two protons, two positrons, and four electrons, whose bonding nature has been previously described as either ionic, covalent, or van der Waals-like. Accurate quantum Monte Carlo calculations show that the two positrons occupy a delocalized molecular orbital that envelopes the two hydrogen anions and responds as a collective dipole to an applied electric field. This positronic bonding stems from quantum correlations that resemble a single covalent bond formed between negatively charged pseudo-nuclei, but with a bond strength commensurate with the traditional van der Waals interaction. Our findings suggest that the ability to form delocalized proto-bonds is a more general property of quantum systems, and could be present in a broader class of particles, antiparticles, and quasi-particles interacting with matter.

The classical simulation of quantum algorithms is a crucial tool for circuit development, testing, and validation. Although acceleration using GPUs significantly reduces simulation time, most high-performance simulators rely on vendor-specific frameworks that target data-center hardware. To broaden access to quantum simulation, this work proposes a vendor-agnostic approach targeting the integrated GPUs commonly found in consumer-grade laptops. A primary challenge in state-vector simulation is its inherently poor spatial locality, which creates a memory bandwidth bottleneck. Consequently, baseline implementations experience a severe degradation in relative GPU speedup as the number of simulated qubits increases. To address this limitation, we introduce a state partitioning optimization that reorganizes the quantum state vector to maximize the last-level cache locality and minimize costly main memory fetches. We evaluate this strategy using a Quantum Phase Estimation algorithm across diverse architectures from Intel, AMD, and Apple. The experimental results demonstrate that the proposed optimization successfully mitigates performance degradation at larger qubit scales. In particular, for a 28-qubit simulation, the optimization reversed a performance deficit on an Intel Core i5, improving the GPU speedup over the CPU from 0.95x to 1.89x, and increased the Apple M1 Pro speedup from 3.71x to 5.88x. Overall, this approach yields consistent execution time improvements, demonstrating the viability of integrated GPUs for efficient quantum circuit simulation.

How much energy does a quantum computer consume? Are they more efficient than their classical counterparts? In this work, we make a step towards answering these questions. We define the energy efficiency of a quantum computer as the ratio of the number of algorithms it can perform during a given time over the energy consumed by the hardware during this time. We analyze the most representative physical platforms currently envisioned to be used as building blocks of quantum computers: superconducting qubits, silicon spin qubits, trapped ions, neutral atoms and photonic qubits. Including insights from experts in all these technologies and taking into account algorithm compilation constraints, we discuss the advantages and inconveniences of each platform from an energy standpoint. Beyond providing concrete values of the energy consumption of current quantum computers, we lay the foundation of a framework to benchmark the energy efficiency of any future quantum computing architecture.

Nondestructive detection of single-electron motion is crucial for quantum information processing with electrons trapped in Paul traps. The standard approach in Penning traps is to detect the image current induced on the trap electrodes by the electron's oscillatory motion. However, applying this approach in Paul traps for single electrons is currently hindered by motional frequency fluctuations arising from trap anharmonicities and instabilities in the rf trapping field. In this work, we propose a robust detection scheme exploiting the transient dynamics of parametric driving to overcome these limitations. Distinct from traditional steady-state approaches, our method focuses on the transient regime to break the temporal constraints imposed by steady-state assumptions, thereby enabling fast readout. We show that a controlled ramp of the parametric drive effectively locks the frequency of the electron motion in the transient regime, rendering the signal highly resilient to realistic experimental noise and inherent micromotion. This work paves the way for the experimental realization of nondestructive detection of single-electron motion in Paul traps.

Quantifying quantum resources for simulating the fundamental forces of Nature is sensitive to the mapping of gauge fields onto finite quantum computational architectures. When locally truncating lattice gauge theories in the irreducible representation basis, it has been proposed to further deform the theory via quantum groups. The purpose of this deformation is (1) to provide an infinite tower of finite-dimensional ($d = k+1$) groups systematically approximating the infinite-dimensional gauge links and (2) to restore the physical unitarity of a plaquette operator diagonalization procedure analytically derived from the field continuum by recontracting vertex pairs. For the SU(2)$_k$ Yang-Mills pure-gauge theory, we provide a constructive strategy of gauge-variant completions to extend this unitarity to the entire computational Hilbert space, leading to well-defined time evolution unitaries as targets for optimized circuit synthesis. Leveraging basic circuit decompositions and symmetries of the diagonalized plaquette operator, we report resource upper-bounds on the generalized-controlled-X two-qudit gates for arbitrary local truncation $d$, reducing estimates and scaling relative to the non-deformed theory by three polynomial powers from $O(d^8)$ to $O(d^5)$. Examining the stronger q-deformed gauge constraint, which softens the total flux at vertices, we show that the physical Hilbert space dimension of the deformed plaquette operator scales equivalently to its non-deformed counterpart with a constant factor $0.2563(5)$. Thus, despite affecting interactions at all scales as exemplified by the observed flux hierarchy inversion symmetry, q-deformation continues to pass scrutiny as a reliable truncation offering advantages in quantum circuit synthesis.

We point out that a simple late-time cosmological model where our Universe can absorb "baby universes" explains the exponential expansion of our universe without the need of a cosmological constant and leads to a z-dependence of the parameter w(z) in the equation of state. In this model w(z) is less than -1 for z sufficiently large.

We derive closed-form propagators for any $K$-qubit subsystem of a closed $N$-qubit network with a single conserved excitation. A single transition amplitude simultaneously controls excitation flow between subsystems, the positivity and complete positivity of every propagator, the entanglement entropy of every subsystem, and the quantum Fisher information for global parameters. Positivity and complete positivity coincide, determined solely by the direction of excitation flow, independently of subsystem size, coherence, or entanglement structure. A propagator is positive and completely positive if and only if it contracts the subsystem state toward its fixed point. The ensemble of propagators collectively constrains global properties inaccessible to any single subsystem. For single-qubit subsystems, we characterize the ensemble's fixed-point distribution and domain of positivity, finding a band of states that lies inside the positivity domain of every propagator yet is never visited by the physical dynamics. The quantum Fisher information decomposes into state and process contributions over any observation window $[t_1,t_2]$, with the state contribution bounded while the process contribution grows secularly. The total Fisher information is minimal when all future propagators are nonpositive and not completely positive, and near its maximum when they are positive and completely positive.

Shared multipartite entanglement defines a ``whatever channel'', i.e., a latent communication substrate that does not determine a priori which end-to-end entangled links are activated, but can be configured to support different entanglement-connectivity graphs through Local Operations and Classical Communication (LOCC). Building on this, we propose a resource-driven framework in which multipartite entanglement is treated as a programmable resource that induces a space of admissible entanglement-graph configurations. Within this framework, connectivity provisioning emerges as a particular instance of a more general resource reconfiguration process. To support this paradigm, we introduce a set of structural design parameters that characterize the operational degrees of freedom of the resource and define the admissible transformations independently of the specific mechanism used to realize them. We then formalize Entanglement Rolling as a measurement-based protocol that operates over the induced configuration space, enabling the systematic reconfiguration of the shared resource across a family of multipartite states. Finally, we analyze the proposed framework under realistic noise conditions. Leveraging the Noisy Stabilizer Formalism (NSF), we derive closed-form noise maps that characterize the effect of noise on the resource transformations and show that the proposed approach maintains reliable performance under relevant noise processes.

The Majorana stellar representation translates abstract quantum spin states into intuitive geometric constellations on the Bloch sphere, revealing symmetries, degeneracies, and correlations that traditional algebraic methods often obscure. Within quantum information science, this framework provides a powerful lens for characterizing symmetric multi-qubit and higher-spin systems. By encoding entanglement directly into spatial coordinates, the constellation geometry yields exact measures of concurrence, three-tangle, and genuine multipartite entanglement, while its dynamical evolution uncovers internal anomalous contributions to geometric phases. While interest in stellar representations has resurged, existing literature remains fragmented, lacking a unified treatment of these entanglement-specific metrics and their higher-dimensional dynamics. This review synthesizes the entanglement-centric perspective on Majorana representations, bridging discrete algebraic classifications (e.g., SLOCC orbits) with continuous geometric interpretations. Crucially, we highlight how this framework circumvents \#P-hard computational bottlenecks, leveraging polynomial-time tractability to evaluate multipartite invariants. We detail the interplay between constellation topology and higher-spin Berry/Hannay phases, explore extensions beyond pure symmetric states, and review applications in quantum metrology, state engineering, and condensed-matter physics. By foregrounding entanglement as the unifying theme, this comprehensive examination establishes Majorana stars as a fundamental geometric language, uniquely positioned to inspire new theoretical and experimental directions in quantum technologies.

We construct a five-dimensional singly rotating near-horizon solution in Einstein-Gauss-Bonnet gravity. We show that the Gauss-Bonnet term removes the local curvature singularity, yielding finite curvature invariants throughout the spacetime, provided the rotation parameter remains below a certain value set by the Gauss-Bonnet coupling. To our knowledge, this is the first analytic example of a singly rotating five-dimensional solution in this framework with finite curvature invariants over a nontrivial region of parameter space. We analyze the geometry across this space, identifying regular, singular, and marginal regimes. Finally, we study the thermodynamic properties, finding that while higher-derivative corrections regularize the local curvature behavior, they also introduce unique challenges to the standard thermodynamic description of Killing horizons.

We prove that the maximum eigenvalue of the (both signed and unsigned) Laplacian of level $k$ Kikuchi graph of any graph $G$ with $m$ edges is at most $m+k$. This confirms four recent conjectures of Apte, Parekh, and Sud. As applications, we obtain that tensor products of one and two qubit product states achieve an approximation ratio of $5/8$ for Quantum Max Cut and $5/7$ for the XY Hamiltonian. Moreover, combining our bounds with the algorithms analyzed by Apte, Parekh, and Sud, yields efficient algorithms achieving an approximation ratio of $0.614$ for Quantum Max Cut and $0.674$ for the XY Hamiltonian. Finally, we also make modest progress on Brouwer's conjecture and improve Lew's bound on the sum of the top-$k$ eigenvalues of a Graph Laplacian.

Rydberg atoms provide a powerful platform for exploring strongly interacting quantum systems, both in free space and in structured electromagnetic environments, with growing applications in quantum technology. Accurately modeling their single-atom properties and mutual interactions is essential for interpreting experiments and designing new architectures. We present a unified theoretical framework for Rydberg atoms and their interactions based on multi-channel quantum defect theory (MQDT) and static electromagnetic Green's tensors. MQDT provides a precise description of Rydberg states of divalent atoms such as strontium and ytterbium, while the Green's tensor formalism provides a general and flexible approach for calculating interactions between two Rydberg atoms in arbitrary geometries, including modifications induced by nearby surfaces. We implement this framework in an updated version of the open-source PairInteraction software [Weber et al., J.~Phys.~B~50 (2017)]. The implementation leverages high-performance libraries and achieves speedups of one order of magnitude for pair-potential calculations compared to prior software. We demonstrate the capabilities of the framework through example applications to divalent atoms and show excellent agreement with experimental data for an exemplary Stark map of $^{174}$Yb. The modular software architecture enables the community to extend it further.

By implementing the Bogoliubov-de Gennes (BdG) formalism of population-imbalanced atomic Fermi gases with pairing interactions in a thin spherical shell, we characterize the Larkin-Ovchinnikov-Fulde-Ferrell (LOFF) state in such a compact geometry. We first construct a phase diagram showing where uniform solutions of spin-polarized Fermi superfluid from the BdG equation cease to exist due to the vanishing order parameter. Near the boundary, various LOFF states with spatially modulating order parameters and density profiles can survive as convergent solutions to the BdG equation. When both uniform and LOFF solutions are present, we compare their grand potentials to determine the energetically favorable state and find that the LOFF states with multiple nodes in the order parameter become more stable at higher spin polarization. However, the LOFF state only survives close to the phase boundary where the uniform solutions vanish, indicating fragility of the LOFF state on a spherical surface. We also briefly discuss possible implications.

We investigate a scalar-vector-tensor theory in which matter is minimally coupled to a Jordan-frame metric, while a massive vector sector interacts with the baryonic current. We show that the conformal scalar coupling modifies the physical expansion rate measured by matter observers, leading to a late-time enhancement of the effective Hubble constant. By constructing a phenomenological scalar evolution that becomes relevant only at low redshifts, the model provides a purely late-time mechanism for alleviating the Hubble tension without significantly affecting early-universe cosmology. The scalar potential naturally acts as a dynamical dark-energy sector, while the vector contribution behaves effectively as a pressureless component at cosmological scales through a density-dependent vector mass. Hence, the framework connects late-time scalar dynamics, effective dark-energy evolution, and Hubble-tension alleviation within a unified setup. Finally, local gravitational constraints can be suppressed through a chameleon-type screening mechanism, allowing the theory to remain compatible with Solar-System tests while retaining nontrivial cosmological effects.

In recent years, there have been increasing challenges to the cosmological principle, based on new observations of e.g. supernovae and the cosmic bulk flow. As a result, the cosmological community is speaking their concern for the cosmological principle, and from which scales onwards it should apply. In this context, there is a desire to understand more fully the properties and signatures of cosmologies not obeying the cosmological principle. In this article, we let go of the demand of cosmic isotropy, and instead assume only spatial homogeneity in our cosmological models. We follow the results of our previous works [see citations in the list of references], and here bring these together into one unified picture, with the goal of describing the signature(s) of anisotropy in anisotropic cosmological models. We first introduce the Bianchi models -- a particular instance of spatially homogeneous cosmologies -- and show that a metric can be constructed for them when an appropriate collection of desired Killing vector fields is supplied. Then, we give the perturbations of the Friedmann equations in such Bianchi models, in the Newtonian gauge, derived using much the same methodology as applicable to the FLRW models. We show these can be combined into one characteristic partial differential equation. Finally, we use this equation in order to simulate the CMB of a toy Bianchi V example and produce its power spectrum. We close with a discussion, and suggestions for further research.

When considering how self-interaction affects an object's motion, it can be convenient to decompose the self-force into conservative and dissipative pieces. As a toy model for understanding such decompositions of the gravitational self-force, we consider objects that do not affect the spacetime, but are instead coupled to a nonlinear scalar field. There is then a standard splitting of the first-order scalar self-force into conservative and dissipative components. Multiple criteria can be used to obtain this splitting, all of which imply the same result. However, the implications of these criteria generically differ at higher orders. Demanding that any reasonable conservative sector be Hamiltonian, we identify multiple possible definitions of the conservative second-order self-force. Motivations for these possibilities and their properties are discussed and relevant Hamiltonians are obtained. We assume the existence of a three-point function with certain properties that is a generalization of the Detweiler-Whiting two-point function. These results apply to the two-body problem but are restricted to unbound scattering trajectories, due to infrared divergences that arise for bound orbits.

It has been known that gravitational waves (GWs) transfer energy to viscous matter through which they propagate, but the effect is too weak to be astrophysically significant. Using linearized perturbations about a Minkowski background, we previously showed that the interaction can become important when the distance between matter and source is smaller than the GW wavelength. Here, we review extensions to more realistic backgrounds, namely Schwarzschild spacetime and a static spherically symmetric setting. We find that GW damping and the associated heating of the viscous fluid are enhanced, and can lead to substantial attenuation or even gamma-ray bursts. We investigate astrophysical scenarios where these effects may be relevant, including core-collapse supernovae, binary neutron star mergers, and accretion onto binary black hole mergers.

We introduce a nonlocal Maxwell demon teleporting ergotropy at finite temperature via classical communication and a shared surface code. The teleported ergotropy is exponentially protected below a topological threshold. We identify a thermodynamic phase transition separating a profitable demon phase from a thermal phase. A quadratic infrastructure cost strictly enforces the second law, imposing a fundamental thermodynamic horizon on separation distance. This establishes quantum error correction as a resource for nonlocal thermodynamics beyond fault-tolerant computation.

We present a tool QSeqSim, a Qiskit-integrated symbolic backend that fills the current gap of having no Qiskit-native support for simulating while-loop quantum programs and their induced sequential quantum circuits. QSeqSim takes Qiskit QuantumCircuit objects, translates them into OpenQASM 3 code, and organises the resulting program into a combination of combinational, dynamic, and sequential circuits, thereby assigning while-loops a precise sequential circuit semantics with explicit internal and external qubits. Building on this semantics, QSeqSim adopts a Binary Decision Diagram (BDD)-based symbolic representation and integrates weighted model counting to compute measurement probabilities efficiently by exploiting sharing in structured and sparse BDDs. On top of this Boolean backbone, it introduces dedicated symbolic operators for state composition and state retention, thereby enabling efficient symbolic execution of sequential quantum circuits. Our experiments demonstrate that QSeqSim scales to substantial while-induced sequential circuits; in particular, in the quantum random walk benchmark we successfully simulate circuits with over 1000 qubits for more than 10 loop iterations. QSeqSim is available at https://github.com/Veri-Q/QSeqSim.

Motivated by the central role of the Zel'dovich approximation in the description of cosmic structure formation through gravitational collapse, we investigate Burgers-type dynamics in a spherically symmetric gravitational field. In the Newtonian setting, we derive perturbatively the catastrophe time for radial motion by imposing the loss of invertibility of the Lagrangian map. We show that the perturbative expansion is controlled by the dimensionless parameter $ α=μ/{r_0^3 v_0(r_0)'^2}, $ rather than by the local gravitational acceleration alone. Hence, the expansion remain valid even when gravity is strong. We then extend the analysis to radial geodesic motion in Schwarzschild spacetime.

Ultrafast continuous-variable quantum states offer new opportunities for advanced quantum technologies, but efficient homodyne detection of these states remains challenging. Here, we present a method for efficient ultrafast homodyne detection by exploiting temporal correlations in detector signals. By optimizing the temporal weight used to extract quadrature outcomes, we achieve a substantial increase in the signal-to-noise ratio of ultrafast homodyne detection, thereby improving the detection efficiency. We analyze the autocorrelations of shot noise and electronic noise and determine the optimal weight by solving a generalized Rayleigh quotient problem. The optimal weight enhances the squeezing and anti-squeezing levels observed experimentally. These results highlight the importance of optimized signal processing for efficient quantum measurements.

We consider an extended model of quantum computation where a scalable fault-tolerant quantum computer is coupled to one or more ancilla qubits that evolve according to a nonlinear Schrödinger equation. Following the approach of Abrams and Lloyd, an efficient quantum circuit evaluating an $n$-bit Boolean function in conjunctive normal form is used to prepare an ancilla encoding its number $s$ of satisfying assignments ($0 \le s \le 2^n$). This is followed by a nonlinear quantum state discrimination gate on the ancilla qubit that is used to learn properties of $s$. Here we consider three types of state discriminators generated by different nonlinear Hamiltonians. First, given a restricted Boolean satisfiability problem with the promise of at most one satisfying assignment ($ 0 \le s \le 1$), we show that a qubit with $\langle σ^z \rangle σ^z$ nonlinearity can be used to efficiently determine whether $s = 0$ or $s = 1$, solving the UNIQUE SAT problem. Here $\langle A \rangle := \langle ψ| A |ψ\rangle $ denotes expectation in the current state. UNIQUE SAT is NP-hard under a randomized polynomial-time reduction (of course any discussion of complexity assumes a scalable, fault-tolerant implementation). Second, for unrestricted satisfiability problems with $ 0 \le s \le 2^n$, a Hamiltonian with $ \langle σ^x \rangle σ^y - \langle σ^y \rangle σ^x$ nonlinearity can be used to efficiently determine whether $s=0$ or $s>0$, thereby solving 3SAT, which is NP-complete. Finally, we show that $ \langle σ^y \rangle \langle σ^z \rangle σ^x - \langle σ^x \rangle \langle σ^z \rangle σ^y $ nonlinearity can be used to efficiently measure $s$ and solve #SAT, which is #P-complete. The nonlinear models are of mean field type and might be simulated with ultracold atoms.

The Heisenberg-Weyl group $HW(d)$ related to a $d$-dimensional Hilbert space $H(d)$, is enlarged into the Heisenberg-Weyl-parity group $HWP(d)$ that incorporates parity transformations. It consists of $2d^3$ elements, of which $d^3$ elements belong to the $HW(d)$ subgroup, and extra $d^3$ elements which are related through a Fourier transform with the former ones. It is shown that $HWP(d)$ is a generalised version of the dihedral group. The properties of operators that combine displacements and parity, are discussed. $HWP(d)$ is shown to be a solvable group, and commutators of its elements perform displacement and parity transformations of quantum states, along loops in the discrete phase space.$2d^2$ coherent states related to the $HWP(d)$ group are introduced, which consist of $d^2$ coherent states related to the $HW(d)$ subgroup, and extra $d^2$ coherent states which are related through a Fourier transform with the former ones. In noisy cases, expansion of an arbitrary state in terms of the $2d^2$ coherent states with Bargmann coefficients, is advantageous in comparison to expansion in terms of the $d^2$ coherent states related to $HW(d)$. One of the consequences of the $HWP(d)$ group, is a natural unification of the Wigner and Weyl functions. The properties of the unified Wigner-Weyl function are discussed.

Roger Penrose introduced the concept of the trapped surface: a spacelike hypersurface where the two null normals have negative expansion. The trapped surface along with the null convergence condition leads to null geodesic incompleteness. If an event horizon forms, the trapped surface is also always behind it, providing evidence for the weak cosmic censorship conjecture. When the null convergence condition is violated, as in the case of semiclassical gravity, trapped surfaces lose these guarantees. A generalized notion, the sufficiently trapped surface, accommodates weaker energy conditions consistent with quantum fields. This concept restores key roles in singularity and area theorems and continues to support the weak cosmic censorship conjecture.

Quantum Gravity remains elusive, largely because its observable effects are suppressed by powers of the Planck scale. Direct detection of single gravitons is widely believed to be impossible. Here we propose a concrete astrophysical mechanism that may overcome this suppression. We show that superradiant axion-like-particle clouds surrounding rotating black holes can generate multimode squeezed states of gravitons containing up to $10^6$ - $10^7$ correlated quanta. Such states exhibit distinctive polarization correlations and quantum-noise signatures that could be detectable in future gravitational-wave interferometers. Observation of these signatures would constitute direct evidence for the quantum nature of gravitational radiation. Conversely, their absence can place constraints on axion-cloud lifetimes. Our approach also provides a test of General Relativity as an effective field theory.

The AMPS firewall argument relies on treating early radiation, late outgoing Hawking modes, and interior partner modes as approximately independent quantum subsystems. In diffeomorphism-invariant quantum gravity, however, gravitational dressing and asymptotic constraints obstruct such a tensor-product factorization of physical observables. In this essay, we sharpen this obstruction by formulating subsystem independence directly in operator-algebraic terms. Using modular theory, half-sided modular inclusions along null directions, and the sector-wise maximality of the dressed radiation algebra at future null infinity, we show that -- within a fixed asymptotic charge sector -- the algebra associated with the interior Hawking partner cannot form an independent commuting subalgebra, but must be contained as a (non-commuting) subalgebra of the radiation algebra itself. The subsystem-independence assumption underlying the AMPS paradox therefore fails, and the entanglement-monogamy step never becomes applicable. As a result, unitary black hole evaporation and semiclassical horizon smoothness are compatible in asymptotically flat quantum gravity, without invoking entanglement islands, replica wormholes, or modifications of semiclassical horizon physics.

We study a generic quantum Markovian master equation for a linearly displaced or driven harmonic oscillator. It was known that the displacement dynamics of Gaussian mixed states depends on the unitary part of the Liouvillian, the decay rate of the system but not on the bath temperature. Here we further show that the fast-rotating modes do not affect the system's displacement dynamics under linear driving forces. Analytical solutions of the quantum master equation are obtained for displaced Gaussian mixed states. Because the non-driven and driven Liouvillians are related by a unitary displacement operator, they are expected to share the same exceptional points structure. At the exceptional points, the displacement of critically damped oscillator displays a characteristics polynomial-in-time prefactor multiplied by an exponential decay. We discuss how external time-dependent forces affect the displacement dynamics using impulsive force and harmonic force as examples. The results obtained for constant driving remain valid in the presence of time-dependent driving.

We study the regularized vacuum stress tensor of scalar fields in maximally symmetric spacetime and assess the feasibility of driving primordial inflation or current cosmic acceleration by analyzing the existence of solutions to the Friedmann equation. We find that a conformally coupled scalar field with mass of order $10$ $M_{\text{pl}}$ can be a candidate for both the inflaton and dark energy, suggesting that these two components may have the same quantum origin. In contrast, a minimally coupled scalar field cannot serve as either the inflaton or dark energy regardless of its mass.

Continuous gravitational waves, i.e., persistent and nearly-monochromatic signals emitted by asymmetric spinning neutron stars, remain elusive. Searches for these signals from unknown binary systems are the most computationally challenging, but they are essential, given that binary accretion provides a natural mechanism for creating the required asymmetry, and around half of the known pulsars rotating above 25 Hz are part of a binary system. Here we report on a search of a large uncharted parameter-space region: for the first time we cover gravitational-wave frequencies above 520 Hz (from 50 to 1000 Hz), and, for the first time with advanced detectors, orbital periods lower than 3 days are explored. No signal is detected, and we set the most stringent constraints to date on the amplitude of signals of this kind. Our results exclude with $95\%$ confidence neutron stars within 100 pc and rotating faster than $\sim$ 495 Hz from having ellipticities above $5.2 \times 10^{-8}$. Within the same distance our results also exclude r-mode amplitudes above $1.5 \times 10^{-6}$ for stars rotating faster than $\sim$ 740 Hz.

The application of quantum computing to data management has attracted growing interest, yet remains constrained by a limited understanding of how the physical behaviour of quantum devices relates to the structure and difficulty of database problems. In particular, evaluating quantum annealing approaches for combinatorial optimisation, which is central to many data management tasks, poses significant challenges beyond the scope of conventional empirical and complexity-theoretic methods. We present a computational toolbox for the systematic numerical analysis of quantum annealing processes derived from data management problem formulations. Adopting a physics-informed perspective, the toolbox enables the study of spectral and dynamical properties -- such as energy gaps and eigenstate structure -- that are inaccessible through direct hardware measurements, yet essential for understanding computational hardness and scaling behaviour. Our approach further provides derived quantities and visualisation techniques that support the interpretation of optimisation dynamics, the identification of structural similarities to canonical physical models, and the construction of reduced effective descriptions. By bridging methodological gaps between quantum computing and database systems research, this work establishes a principled foundation for evaluating quantum approaches and guiding future co-design efforts.

Hellings-Nordtvedt theory is a vector-tensor theory in which a vector field $A_μ$ is nonminimally coupled to curvature through two independent interactions $A^2{\cal R}$ and $A^μA^ν{\cal R}_{μν}$. When supplemented by a potential whose zero-energy minimum occurs at nonzero $A^2$, the restricted $A^μA^ν{\cal R}_{μν}$ sector is known to admit black-hole and neutron-star solutions with a monopole-like asymptotic vacuum structure. We examine whether this structure is a generic consequence of the nonzero vector vacuum or instead relies on the special Ricci-tensor coupling. By analyzing the field equations near spatial infinity, we show that the asymptotic vacuum condition is incompatible with generic nonzero values of both couplings and instead selects two allowed single-coupling sectors. The $A^μA^ν{\cal R}_{μν}$ sector reproduces the known monopole-like asymptotics, whereas the $A^2{\cal R}$ sector admits an asymptotically flat Schwarzschild metric with a nontrivial radial vector field. We further compute the Noether mass in the $A^2{\cal R}$ sector, derive the corresponding Solar-System constraints, and construct neutron-star configurations. Although the weak-field deviation is constrained to be small, neutron stars can still show appreciable departures from both general relativity and the Ricci-tensor-coupling sector in their masses, radii, and moments of inertia. Our results identify that the $A^2{\cal R}$ sector of massive Hellings-Nordtvedt theory as a viable and useful framework for studying strong-field compact objects with a nonzero vector vacuum while remaining compatible with weak-field tests.

In the Kerr-Schild double copy, static and spherically symmetric black hole solutions of general relativity are mapped to purely electric solutions of Maxwell's theory in flat spacetime. We demonstrate that, for these configurations, the thermodynamic Smarr formula is structurally identical to the single-copy Gauss's law. Extending this to asymptotically anti-de Sitter spacetimes, we prove that the thermodynamic pressure-volume term ($PV$) naturally emerges from a gauge-theoretic background subtraction. This relationship establishes a novel connection between the classical double copy and black hole thermodynamics.

Nitrogen-vacancy (NV) centers in diamond are a leading platform for solid-state quantum sensing and quantum information processing. While most optical studies rely on the visible fluorescence associated with the triplet transitions, the infrared singlet transition near $1042$ nm, which is typically considered dark within the singlet manifold of the NV optical cycle, provides an alternative optical channel. Here, we report wavelength-resolved optically detected magnetic resonance (ODMR) measurements of this infrared emission. We directly observe ODMR contrast in the $1042$ nm emission and analyze its dependence on the magnetic field. The field-dependent spectral dispersion of the ODMR signal demonstrates that the spin-state information encoded in the NV center is transcribed to the infrared singlet emission through the spin-selective intersystem crossing, in close analogy to the visible fluorescence readout. These results establish infrared ODMR as a high-fidelity optical readout pathway. Crucially, by extending spin-state transcription directly into the $1300-1600$ nm range, this work demonstrates a direct, conversion-free interface between diamond spin-qubits and standard telecommunication infrastructure, bypassing the efficiency bottlenecks of active frequency conversion and benefiting from the already well-developed technologies in this range of the electromagnetic spectrum.

In this study, we explore the behavior of photon added coherent states in a deformed harmonic oscillator subjected to dissipative decoherence. We use $q-$deformation as our nonlinear function to model our system. By adjusting the deformation parameter, we show that $q-$deformed photon added coherent state (DPACS) exhibit greater nonclassicality and resilience to decoherence compared to those of a standard harmonic oscillator. Additionally, we investigate the nonclassical properties and entanglement of DPACS under decoherence induced by interaction with a dissipative photon-loss environment.

A consistent non-compact axion cosmology requires a non-periodic field, an effective field theory valid sufficiently above the inflationary scale, and a small non-QCD contribution to the potential that tilts the axionic vacuum landscape in order to trigger a timely domain-wall collapse. All conditions can be met by the dilaton -- the pseudo-Nambu-Goldstone boson of spontaneously broken approximate scale invariance.

In the shallow water approximation, the cross-sectional profiles of laboratory rivers satisfy a differential equation here shown to be formally the Friedmann equation of cosmology ruling the evolution of Anti-de Sitter universe. The ensuing cosmic analogy provides a counterintuitive Lagrangian for the transverse river profile. Extremizing the corresponding action corresponds to extremizing the friction force on the river bottom and the energy dissipation rate. Analysis of the second variation establishes that this extremum is a maximum.

We study the $α'$ corrections to self-dual gravitational instantons in the context of the four-dimensional Cano--Ruipérez action, which can be obtained by the compactification of the Bergshoeff--de Roo heterotic string effective action on $\mathbb{T}^{6}$ followed by a truncation and a field redefinition. We show that the metric of spaces of self-dual curvature does not receive any corrections, but their (initially trivial) dilaton and axion fields do, owing to their couplings to Gauss--Bonnet and Pontrjagin densities. We find the generic form of the corrections of the dilaton and axion fields for the Gibbons--Hawking multi-instanton solutions and their explicit form for the particular cases of the Euclidean Taub--NUT and Eguchi--Hanson spaces. We construct the boundary terms required to define a well-posed Dirichlet variational principle in the Euclidean Cano--Ruipérez theory, including the contributions associated with the Gauss--Bonnet and Pontrjagin terms. The boundary terms are normalized for asymptotically-locally-Euclidean solutions, and we evaluate with them the Euclidean action of the $α'$-corrected Eguchi--Hanson instanton showing that the total action receives no corrections to first order in $α'$. We also show that, at zeroth order in $α'$, one can construct Euclidean solutions similar to the string theory D-instanton with non-trivial dilaton and axion on the background of a self-dual purely gravitational instanton which remains unmodified. We also compute the $α'$ corrections to these solutions.

We study static spherically symmetric Kundt solutions to the vacuum field equations of quadratic gravity with a cosmological constant, as well as specific models of six-derivative gravity. In quadratic gravity, we identify all solutions for coupling constants satisfying ${α\neq3β}$, while the case ${α=3β}$ is studied using the Frobenius method, where we derive the recurrence relations for the power series. In contrast, in six-derivative gravity, we focus on selected models to illustrate the variety of closed-form solutions; we also analyze possible indicial families of Frobenius solutions. For all solutions, we analyze curvature singularities and their accessibility to geodesic observers. We then construct exact gravitational-wave solutions propagating on some of these backgrounds in quadratic and six-derivative gravity. It is known that in Einstein gravity, gravitational waves on the Nariai background unavoidably contain singularities, which are interpreted as physical sources generating these gravitational waves. In contrast, in addition to singular solutions, for appropriate values of the coupling constants, higher-order gravities allow for globally smooth solutions representing gravitational waves.

We investigate the imprints on the angular power spectra of cosmological perturbations of a pre-inflationary bounce phase, as described by the hybrid and dressed metric approaches to loop quantum cosmology. For this purpose, we derive a new parametrization of the primordial power spectrum at the end of the inflationary regime. Apart from slow-roll coefficients and cosmological parameters that are present in the standard cosmological scenario without quantum modifications, this parametrization additionally depends only on pre-inflationary physics. More specifically, we find a dependence on the number of e-folds during the bounce epoch and on a characteristic suppression scale which, given the e-folds accumulated during cosmic evolution, is determined by the energy density at the bounce. Recall that this density depends on the Immirzi parameter and the area gap known from LQG. This leads to a robust and accurate parametrization of the primordial power spectrum. Since in pre-inflationary scenarios there is no preferred vacuum state, we adopt the NO-AHD proposal, which selects a vacuum that is optimally adapted to the background dynamics and yields a non-oscillatory primordial power spectrum. With this choice, we show that the tensor-to-scalar ratio in both quantization approaches coincides with its expression in the standard $Λ$CDM model when the observed scales are not much smaller than the power-suppressed region. Computing also the angular power spectrum, we find that, for a total cosmic expansion of about 140 e-folds, both the hybrid and the dressed metric approaches exhibit excellent agreement with Planck data at high multipoles, while apparently improving the fit with respect to $Λ$CDM for low multipole numbers.

Current cloud-based quantum processors offer access to advanced hardware hosted on a remote server, but do not guarantee data or algorithm privacy. Blind quantum computation provides information-theoretic privacy by enabling a client to execute an algorithm without disclosing information about either the task or the final result. Here, we execute a measurement-based blind quantum computation protocol on a superconducting processor comprising two flip-chip-bonded modules, one acting as a server and the other as a client. The server generates a two-dimensional cluster state and forwards it to the client. Using this resource, the client implements a universal gate set with only adaptive single-qubit rotations and measurements. To illustrate this approach, we execute a three-qubit instance of the Deutsch-Jozsa algorithm. We analyze the server's quantum state after each rotation of a measurement-based single-qubit gate to verify that negligible information about the computation is revealed to the server, consistent with the one-way flow of information that guarantees blindness. This proof-of-principle demonstration establishes key elements of blind quantum computation in superconducting-circuit architectures, indicating that intermediate-scale implementations of blind protocols may become feasible with realistic near-term improvements in gate fidelities.

Positive maps that are not decomposable are a key resource in entanglement theory because they can detect bound entangled states, yet systematic methods for constructing them remain limited. We introduce an optimization framework based on differentiable semidefinite programming (SDP) for generating positive non-decomposable maps under flexible structural constraints on their Choi matrices. The method combines SDP-based certificates of non-decomposability and positivity with gradient-based optimization, enabling a systematic search over maps with different input and output dimensions. Within this framework, we generate previously unknown numerical examples, identify a parametrized family of maps arising from masked Choi matrices, and construct real non-decomposable maps. We further show that the same approach can be adapted to explore open questions in quantum information theory, including the PPT square conjecture and recently proposed eigenvalue bounds for 2-positive trace-preserving maps.

We study scattering for continuous-time quantum walks on finite graphs with two attached leads. We derive explicit formulae for the two-terminal scattering matrix in terms of characteristic polynomials of the finite graph and its vertex-deleted subgraphs. For real-weighted two-terminal graphs, we then introduce three real quantities, $μ_1$, $μ_2$, and $ν$, which are each additive under parallel composition of graphs. In these variables, perfect transmission at fixed momentum is characterized by the condition $μ_1=μ_2$ together with a hyperbola in the corresponding $(μ,ν)$-plane, whose points determine the transmission phase. This turns the search for graphs with prescribed transmission properties into a geometric vector-sum problem for smaller building blocks.

Real-time decoding plays a crucial role in practical fault-tolerant quantum computing. Window decoding, in which the decoding problem is divided into windows, is a promising approach. While reducing the window size is desirable for faster decoding, each window contains a buffer region whose size must typically be at least the code distance to avoid degrading the logical error rate, which limits how much the window can shrink. In this paper, we propose an adaptive decoding scheme in which window decoding is first performed with a small buffer size and a decoding confidence (soft information) is computed; if the confidence is low, the buffer size is enlarged and decoding is redone. This approach reduces the average decoding time, since most shots are decoded with a small buffer. A central challenge in realizing this scheme is that existing forms of soft information are not directly applicable to window decoding, especially with a small buffer. We address this challenge by introducing a new form of soft information, the spatiotemporal complementary gap, specifically designed for this setting. Numerical simulations demonstrate that the proposed scheme reduces the average buffer size by approximately 40% while maintaining the logical error rate.

We propose a superconducting circuit hosting $d$ low-lying states, well separated from the rest of the spectrum, that naturally realizes a qudit system protected from leakage errors. The system represents a generalization of the fluxonium and the low-energy states are constituted by fractional fluxon states, that we call {\it fraxons}, localized in the minima of a suitably designed Josephson potential. The latter is tailored through a Fourier engineering approach, that employs multi-harmonic Josephson building block elements composed by a Josephson junction and an inductance connected in series. We present the spectrum of a $d=4$ and a $d=5$ qudit system and study in detail the qutrit case. We analyze the dipole matrix elements for coupling to radiation and propose a non-Abelian, stimulated Raman adiabatic passage (STIRAP) protocol for single-qutrit gates, that is particularly suited for the present system. The proposed platform opens novel perspectives in circuit engineering and quantum computing beyond the qubit paradigm.

The parametric amplification enabled by two-photon driving constitutes a versatile platform for advanced quantum technologies. We present an optimized scheme for implementing quantum batteries (QBs) based on a superconducting circuit system, where a two-photon-driven LC resonator serves as the charger and an array of transmon qubits functions as the battery. Our results show that two-photon parametric driving exponentially enhances the effective cavity-qubit coupling, which in turn gives rise to near-degenerate energy-level structures and highly entangled quantum states. This significantly enhances the charging power and enables rapid energy transfer from the charger to the battery. Moreover, the engineered squeezed cavity mode and the associated quantum correlations effectively suppress environmentally induced decoherence, thereby delaying energy leakage and facilitating stable energy storage. The proposed scheme remains robust against practical experimental imperfections, such as parameter disorder and environmental noise, preserving its performance advantages. The work provides a feasible platform for realizing high-power, high-stability QBs and highlights the potential of parametric control in quantum energy technologies.

We study the linearized scattering of dilaton-graviton waves from a thin brane in three-dimensional spacetime. Holographically, the setup models scattering from an interface in a family of strongly coupled theories related to dimensional reductions of higher-dimensional $AdS_{d+2}$ gravity. Unlike the pure $AdS_3$ case, for $d>1$ the physical bulk mode allows incident radiation to be redistributed into reflected, transmitted, and evanescent components. For the $d=2$ background, we obtain a controlled solution in which the interface acts like a rough translucent window, producing diffuse angular scattering and absorption into surface modes. From the dual perspective, the scattering process is suggestive of dissipative flow toward the infrared. For $d=4$, the same analysis reveals a sensitivity to the infrared boundary condition, suggesting that the singular zero-temperature geometry must be regulated in order to have a well-defined scattering process. The structure of the equations nevertheless suggests that a regulated $d=4$ problem may exhibit the same qualitative redistribution of incident flux.

Recent cosmological tests have discovered a fresh new set of anomalies in the large-scale isotropy of the universe. Motivated thus by the numerous pieces of evidence for large-scale cosmic isotropy violation with the advent of the 'precision cosmology' era, we are led to explore the viability of anisotropic Thurston geometries, described in William Thurston's geometrization conjecture. In this work, we examine the coherent temperature and polarization signals generated in the CMB sky by such geometries. We begin with introducing Thurston spacetimes as our background model and the formalism we use to obtain the patterns. We then construct a set of transfer equations relative to a given background and solve them for each spacetime geometry. We finally discuss the role of spatial curvature in these FLRW limiting models along with their underlying geometry, and attempt to establish some general results on the symmetries of the patterns produced by their time evolution in terms of the Stokes parameters P, Q, U and V. We show the evolution of temperature and polarization amplitudes in terms of such Stokes parameters at different timestamps and attempt to isolate individual Thurston geometries.

In this work, we investigate the cosmological dynamics of a spatially flat Friedmann--Lemaître--Robertson--Walker Universe in the framework of generalized \( \mathcal{F}(\mathcal{R},Σ,\mathcal{T}) \) gravity by incorporating gravitationally induced particle creation together with the variable generalized Chaplygin gas scenario. The modified gravitational action depends explicitly on the Ricci scalar \( \mathcal{R} \), the matter-coupling scalar \( Σ\), and the trace of the energy--momentum tensor \( \mathcal{T} \), which collectively generate significant corrections to the standard cosmological evolution. The particle creation mechanism is introduced through an open thermodynamic description of the Universe. In addition, the dark sector is modeled using the variable generalized Chaplygin gas formalism. To examine the observational consistency of the model, the free parameters are constrained using the Pantheon\(^+\) Type Ia Supernova compilation together with the combined observational Hubble and Pantheon\(^+\) datasets through a statistical \(χ^2\)-analysis. The cosmological behavior of the model is further explored through the evolution of the cosmological parameters. Furthermore, the thermodynamic properties of the model are investigated using the apparent horizon formalism. The obtained results demonstrate that the entropy evolution remains physically consistent throughout the cosmic evolution. Hence, the present \( \mathcal{F}(\mathcal{R},Σ,\mathcal{T}) \) gravity framework with particle creation provides a viable geometrical description of the late-time accelerated Universe and remains compatible with recent cosmological observations.

Wigner's thought experiment illustrates quantum theory's measurement problem by considering an observer who measures a quantum system inside a sealed lab, modeled unitarily by an outsider. Recent extensions of this thought experiment, referred to as extended Wigner's friend arguments, question how different observers can reason consistently about each other in quantum setups, and challenge the absoluteness of the outcome value obtained by the friend under a notion of locality. In this work, we present an argument against the absoluteness of free choices under the same notion of locality, using an extended Wigner's friend scenario based on the Pusey--Barrett--Rudolph theorem. Similar arguments based on other contextuality or nonlocality models are possible.

We investigate the consistency in the thermodynamics and the approaches at the equation and action levels for the quantum-improved charged black holes with scale-dependent couplings. For the quantum-improved Reissner-Nordström black holes, we find that the thermodynamic consistency allows both the Newton and electromagnetic couplings to have arbitrary dependence on the radial coordinate. We point out a subtlety in the chemical potential with the scale-dependent electromagnetic coupling in the study of thermodynamics. We also examine the compatibility of the Einstein equations at the equation and action levels with the Bianchi identity, identifying the need for an additional quantum energy-momentum tensor. We then find that the consistency between the approaches at the equation and action levels requires that the Newton coupling satisfy certain property. Finally, we extend the analysis to cosmological solutions, suggesting that quantum-induced modifications can drive the isotropization of the early universe.

Rydberg atomic electrometry leverages the extreme sensitivity of highly excited atoms for calibration-free electric field measurements. The technique uses a non-metallic vapor cell to link properties of an RF field to a spectroscopic readout in the optical domain. Most demonstrations have so far focused on detecting linearly-polarized fields, for which the induced splitting of dressed atomic levels is rotationally invariant. Here we report on Rydberg atomic measurements of RF fields in a general state of polarization (SOP) which we map onto the Poincaré sphere through spectroscopic fingerprints. For a Stokes vector circumnavigating a Poincaré sphere meridian, we witness a continuous transformation of the atomic eigenenergy spectrum. Because the relative positions of eigenenergies are locked in place by quantization of angular momentum, the framework is universal and calibration free. We provide a specific demonstration in rubidium, which generalizes to all systems with a single valence electron.

We investigate the quasinormal modes of massless scalar and electromagnetic perturbations in charged Euler--Heisenberg black holes surrounded by perfect fluid dark matter. The quasinormal frequencies are calculated using the asymptotic iteration method and the sixth-order WKB approximation, and the relative deviation between the two methods is quantitatively analyzed to verify the reliability of results. The greybody factors for both perturbations are also evaluated within the sixth-order WKB framework. We systematically examine the effects of the black hole charge $Q$, nonlinear electrodynamic parameter $a$, dark matter parameter $λ$, and angular quantum number $l$ on the quasinormal frequencies and greybody factors. We find that these parameters significantly modify the structure of the effective potential barriers, and thus affect the oscillation frequencies, damping rates, and wave transmission and reflection properties of the perturbed fields.

Speech emotion recognition (SER) remains fragile in real-world conditions because emotional cues are subtle, speaker-dependent, and easily confounded by recording variability, while high-performing deep models typically rely on large and carefully curated training sets. Quantum machine learning offers an alternative way to introduce nonlinear correlation modeling with compact modules, yet existing quantum SER studies remain limited and the impact of circuit structure is not well understood. This paper presents HQTN-SER, a hybrid quantum-classical framework that investigates how quantum tensor network connectivity can support SER under small-qubit settings. HQTN-SER introduces (i) an MPS-inspired quantum tensor network module that enforces structured interactions to model correlations in speech representations with a small number of trainable parameters, and (ii) a fusion strategy that combines quantum measurement features with a learned classical latent embedding for end-to-end emotion classification. We evaluate HQTN-SER on three public benchmarks (RAVDESS, SAVEE, and MDER) under a unified preprocessing and training protocol. The proposed model achieves consistent performance across datasets, RAVDESS = 80.12%, SAVEE = 78.26% and MDER = 73.51% accuracy, with stable convergence and low qubit counts, showing that tensor network structure can be an effective and hardware-aware design choice for quantum-assisted SER. The results provide a reproducible baseline and clarify when structured quantum modules can add value to affective computing today.

Entanglement can hide in two fundamentally different ways. First, multi-copy correlations can carry information that no single-copy measurement on an unknown state is able to access. Second, bound entangled states possess a positive partial transpose, which makes them invisible to the Peres-Horodecki criterion and all moment inequalities that depend on it. Here we show that the moment difference between the partial transpose and purity decomposes exactly as a chirality-chirality correlator, where the relevant operator is the scalar spin chirality -- the same quantity that governs chiral spin liquids and the topological Hall effect. This decomposition identifies the specific physical structure that multi-copy entanglement detection probes. Using the same controlled-SWAP circuits, we develop a multi-channel spectral classifier for bound entanglement. The classifier combines realignment spectral features with chirality corrections and achieves 99.9% recall at zero false positives across all three known 3x3 bound entangled families, compared with ~40% for the CCNR criterion alone. We also introduce a marginal-noise construction that produces CCNR-invisible bound entangled states, which the classifier detects but which remain invisible to all single-parameter criteria. We validate our approach experimentally on three IBM Quantum processors and demonstrate negativity reconstruction with mean errors of 0.002-0.027, chirality detection for pure and mixed entangled states, and bound entanglement detection across two structurally distinct families (Horodecki and chessboard) on a single gate-based superconducting processor.

Mode-pairing quantum key distribution (MP-QKD) protocol achieves performance beyond the repeaterless rate-transmittance bound and exhibits excellent practicality by avoiding the requirement for difficult global phase locking. However, the source side of MP-QKD still relies on the assumption of continuous phase randomization, an experimentally infeasible requirement in practice. Therefore, the practical security of the protocol cannot be fully guaranteed. In this work, we propose a discrete-phase-randomized mode-pairing quantum key distribution (DPR-MP-QKD) protocol and analyze the basis-dependence of the source side. Then, we introduce a concrete discrete version of the decoy state method that ensures the security of the DPR-MP-QKD protocol. Finally, simulation results indicate that as the number of discrete phases increases, the key rate performance of DPR-MP-QKD progressively approaches that of the continuous case, with convergence achieved at approximately 14 discrete phases. Moreover, our approach drastically lowers the demand for randomness. While conventional continuous phase randomization demands an unlimited supply of random bits, we show that merely a few bits (e.g., 4) are adequate.

Motivated by recent work on consistent fluid couplings in $f(R, T)$ gravity, we study cosmology in the nontrivial model $f(R, T) = R + σR T$ using the Brown variational principle for a barotropic perfect fluid. For a flat FLRW universe, we cast the field equations into Einstein-like form and obtain explicit expressions for the effective energy density, pressure and equation of state (EOS) parameter. This allows us to rewrite the null, weak, strong and dominant energy conditions as simple polynomial inequalities. We show that radiation reproduces standard relativistic cosmology, whereas for dust and $σ>0$ the effective fluid acquires negative pressure and can drive accelerated expansion. In this dust case, there exists a finite window in the Hubble parameter during which the strong energy condition is violated, but the null, weak, and dominant energy conditions remain satisfied. Conversely, whenever the strong energy condition is imposed, the other conditions are automatically fulfilled. The additional viability requirement $1 + σT > 0$ further restricts the allowed Hubble range and yields an upper bound on $σ$ that still leaves a non-empty accelerating regime. Our analysis provides a transparent energy-condition study of a consistent $R\, T$ coupling in $f(R, T)$ cosmology, based on qualitative techniques.

We study far-field discrimination between one and two incoherent point sources in the singular regime of weak and closely spaced emitters. Under ideal alignment, spatial-mode demultiplexing (SPADE) attains the quantum-optimal large-sample Stein exponent, but the finite-photon behavior near the one-source boundary and the effect of realistic imperfections remain less understood. Using singular learning theory, we analyze both the aligned and misaligned problems. In the aligned Gaussian case, we derive the zeta-function poles for direct imaging and SPADE, show that both share the same real log canonical threshold $λ=1/2$ but differ in multiplicity, and obtain the corresponding Bayes free-energy asymptotics. This yields a universal subleading advantage of aligned SPADE in the local prior-weighted regime. In the misaligned setting, we study a physically motivated binary-SPADE reduction that retains the full leading $O(s^2)$ leakage contrast near alignment, with corrections from the detailed higher-mode redistribution entering only at $O(s^4)$. We show that misaligned binary-SPADE and direct imaging acquire nontrivial local power on different intrinsic scales, $s=O(n^{-1/4})$ and $s=O(n^{-1/2})$, respectively. However, finite-$n$ Neyman--Pearson comparisons under common physical conditions reveal that direct imaging is stronger on the plotted grids and that misaligned binary-SPADE exhibits an exact blind separation $s^\ast=2θ$, where its power collapses to $α$. These results identify model singularity as a structural organizing principle for finite-photon quantum discrimination and clarify how ideal aligned SPADE benchmarks can fail to translate into finite-$n$ advantages under misalignment.

It has recently been revealed that dyonic black-hole spacetimes of a quasitopological non-linear electrodynamic field theory may be characterized by discrete radial regions with the property $dg_{tt}(r)/dr=0$ in which spherically symmetric massive {\it test} shells (Dyson shells with negligible self-gravity) can be supported in static equilibrium states. In the present paper we prove that the dyonic spacetimes of the non-linear electrodynamic field theory may also be characterized by the presence of radial regions with the dimensionless property $d[r\cdot g_{tt}(r)]/dr\to0^+$ in which massive {\it self-gravitating} thin shells that are on the verge of becoming black holes can be supported in static equilibrium states. Intriguingly, it is proved that the discrete radii of these self-gravitating nearly-black Dyson shells are universal in the sense that they are independent of the masses of the central supporting dyonic compact objects.

We show that standard multi-path interferometry, using only pairwise visibility measurements, provides an operational route to tests of preparation noncontextuality. Under ideal symmetric conditions, interference visibility directly encodes state overlaps, without requiring tomography or SWAP tests. For three paths, any jointly diagonalizable (coherence-free) description must satisfy ${V}_{12}^2+{V}_{23}^2-{V}_{13}^2\le 1$, where ${V}_{ij}$ are two-path visibilities. Pure qubit detector states violate this bound, achieving a maximal value of $5/4$. We generalize to arbitrary $n$-path interferometers and derive the tight qubit bound $S_n^{\max}=n\cos^2(π/2n)-1$ for all $n\ge3$, achieved by coplanar pure qubit states with uniform angular separation $π/n$. A robustness analysis yields explicit experimental thresholds. Under the operational equivalences used in overlap-based generalized noncontextuality frameworks, violations of these visibility inequalities also witness preparation contextuality. For $n$-cycle inequalities, only the pairwise visibilities appearing in the cycle need to be measured.

Cavity-magnon systems, combining magnons and photons, offer a versatile platform for studying quantum entanglement and advancing quantum information science. In this work, we propose a scheme for generating nonreciprocal magnon-magnon entanglement in a hybrid system consisting of two yttrium iron garnet spheres coupled to a spinning whispering-gallery-mode cavity. By leveraging the magnon Kerr nonlinearity and the Sagnac effect arising from the cavity rotation, we show that the entanglement can be substantially enhanced, and the resulting entanglement exhibits pronounced nonreciprocal characteristics. Furthermore, our scheme demonstrates that the entanglement remains robust against thermal noise and persists at bath temperatures up to 100 mK. This work underscores the potential of spinning cavity-magnon systems as a versatile platform for realizing nonreciprocal quantum devices and facilitating the development of quantum technologies.

Recently, the technique of counterdiabatic driving, which provides an effective strategy for accelerating adiabatic quantum evolution, has been widely applied in the preparation of many-body quantum states. In this work, we propose a theoretical scheme for the efficient preparation of Dicke states in a system of non-interacting two-level atoms. Our approach leverages the one-axis twisting (OAT) interaction to generate non-classical correlations and combines it with time-dependent external fields to achieve precise control over the dynamics of the system. By employing rapid adiabatic passage (RAP), it demonstrates how the system can be steered from an initial coherent spin state to a target Dicke state with high fidelity [S. C. Carrasco, M. H. Goerz, S. A. Malinovskaya, V. Vuletić, W. P. Schleich, and V. S. Malinovsky, Phys. Rev. Lett. \textbf{132}, 153603 (2024)]. To further optimize the preparation process, we introduce counterdiabatic driving (CD), which suppresses non-adiabatic transitions. Numerical simulations confirm that our scheme can achieve high-fidelity Dicke states for a moderate number of particles. Our results provide a scalable and experimentally feasible approach to prepare Dicke states, with potential applications in quantum metrology, quantum communication, and quantum information processing.

This work investigates the mechanism of gravitational baryogenesis (GB) under the formalism of f(R, G_{μν}T^{μν}) gravity, where R denotes the Ricci scalar, G_{μν} is the Einstein tensor and T^{μν} represents the energy--momentum tensor. f(R, G_{μν}T^{μν}) model is considered to evaluate the baryon-to-entropy ratio (BnER), which is subsequently compared against the observational limits. The results obtained exhibit compatibility with the estimated matter imbalance. Moreover, the analysis is extended to generalized GB case, resulting in outcomes that closely match empirical bounds. The findings reveal that the f(R, G_{μν}T^{μν}) formulation yields a viable theoretical setting for explaining the detected matter-antimatter disparity of the universe, highlighting its relevance in early cosmic evolution. To further validate the models, a chi-square (χ^2) analysis of the Hubble parameter, H(z), and distance modulus, μ(z), is performed, confirming their consistency with current cosmological observations. A comparative assessment simultaneously with the ΛCDM paradigm demonstrates a satisfactory level of agreement between the proposed model and cosmological observations from CC and Pantheon+SH0ES datasets.

Matrix product states (MPS) are a standard tensor-network representation for ground states of one-dimensional quantum many-body systems, and they underpin widely used simulation tools such as DMRG. However, while quantum model checking has been developed mainly for quantum programs and communication protocols (with properties expressed along a time axis), there is still no comparable framework for systematically verifying \emph{spatial} and \emph{size-dependent} properties of physical many-body states, where the key parameter is the system size. This paper takes a step toward bridging the gap. We propose \emph{Linear Chain Logic} (LCL), a spatial logic designed to specify physically meaningful properties of periodic MPS families as the system size grows, such as nontriviality on rings and large-size asymptotic patterns. Our approach builds on a simple but powerful connection: every periodic MPS naturally induces a completely positive map (a quantum operation) on its virtual space, so many quantitative features of the MPS can be analysed through the repeated application of the operation. Using this perspective, we derive an effective procedure to compute the inner products of an MPS at a given size and to support richer LCL specifications, without relying on brute-force state expansion. We then develop approximate model-checking algorithms that combine sound bounding with asymptotic structural analysis, enabling scalable reasoning about large system sizes. Experiments on representative MPS families illustrate that our method can automatically verify nontriviality and detect asymptotic spatial regimes in a way that complements traditional numerical techniques.

Adaptive quantum Fisher information (QFI) estimation requires a stopping rule that distinguishes accuracy from apparent numerical stability. For Krylov-shadow QFI estimators, finite Krylov order $K$ produces truncation bias, while finite sample budget $M$ produces finite-$M$ sampling-side error. We show that a width-only empirical stopping rule, based on interval width and local Krylov stability, can declare convergence at small $(K,M)$ even when the post hoc error exceeds the requested tolerance; we call this event a \emph{false stop}. The mechanism is a narrow empirical interval centered on a biased low-$K$ estimate. We give a two-component stopping analysis that separates the Krylov and sampling terms, and we implement a guarded rule that permits a success declaration only after minimum thresholds in $K$ and $M$ and a persistence condition are satisfied. On a five-level dephasing benchmark at $n=4$ qubits, the guarded rule suppresses the false success declarations produced by the width-only empirical rule, whose false-stop rates range from $0.16$ to $0.68$ across the tested noise levels. Under the main fixed resource limit, the guarded rule refuses to make success declarations rather than accepting biased low-$K$ estimates; a separate true-relative-tolerance sampling-budget sequence then shows that, after Krylov and sampling recalibration, the same decision principle can make success declarations without observed false stops. These results show that stopping reliability is a distinct design requirement for adaptive QFI estimation: sampling precision at fixed $K$ does not by itself establish that Krylov truncation bias is controlled.

As quantum computers become available through multi-tenant cloud platforms, ensuring privacy against adversaries sharing the same quantum processing unit becomes critical. We introduce and explore \emph{covert quantum computing}, a new concept that ensures an adversary with access to all other quantum computational units (QCUs) of a quantum computer cannot detect computation on the subset that they cannot access. Analogous to covert communication, we employ information theory. However, since here the adversary controls the systems used for detection, we require a richer framework for covertness analysis that accounts for the use of quantum memories and adaptive operations. Thus, we adopt the \emph{quantum-strategy} framework used in quantum game theory and memory channel discrimination. Current quantum computers use planar graph circuit layouts and typically assume nearest-neighbor crosstalk. We derive discrete isoperimetric inequalities to show that, for an $n$-qubit circuit under this model, only $\mathcal{O}(\sqrt{n})$ border qubits provide detection information to the adversary. We then explore this scaling law on IQM's 54-qubit \emph{Emerald} processor and IBM's 156-qubit \emph{ibm\_fez} machine employing the Heron 2 architecture. We implement Ramsey experiments on qubits not used in computation, and detect nearest-neighbor crosstalk, as expected. However, we also observe long-range coupling effects beyond the border qubits, revealing a side channel that the adversary can exploit. We hypothesize that this long-range crosstalk is induced by leakage from the drive and control lines. Beyond weakening covertness, it exposes co-tenants to both adversarial and unintended crosstalk and degrades circuits that span spatially distributed qubits, motivating further work on spatial isolation and crosstalk characterization.

Complex numbers play an indispensable role in quantum mechanics and quantum information, as validated by both theoretical analysis and experimental verification. Since quantum information processing inherently relies on quantum channels, the resource theory for quantum channels is equally fundamental to that for quantum states. In this paper, we propose two frameworks for quantifying the imaginarity of Gaussian channels. The first framework regards all real superchannels as free superchannels. Within this setting, we introduce two concrete imaginarity measures for Gaussian channels: I_s^GC based on existing imaginarity measures of Gaussian states, and I_d^GC derived directly from the intrinsic parameters of Gaussian channels, which enjoys high computational simplicity. The second framework adopts only a proper subset of real superchannels as free superchannels. Under this framework, we put forward another imaginarity measure I_c^GC , which is fully determined by the inherent parameters of Gaussian channels and features continuity as well as tractable computation. As a practical application, we employ I_c^GC to investigate the dynamical behavior of Quantum Brownian Motion Gaussian channels throughout the entire evolutionary process.

Periodically driven quantum many-body systems can spontaneously break discrete time-translation symmetry, realizing discrete time crystals. To date, both experimental and theoretical efforts have largely focused on the simplest case of spontaneous period-doubling in $\mathbb{Z}_2$ discrete time crystals realized with qubits. This owes, in part, to the challenge of stabilizing eigenstate order in higher discrete symmetry ($\mathbb{Z}_n$) time crystals, due to the presence of richer domain wall physics. Here, we demonstrate the realization of a $\mathbb{Z}_3$ discrete time crystal by implementing a Floquet chiral clock model in a chain of 15 superconducting qutrits. Unlike the conventional Ising setting, our system features a tunable chiral angle that governs domain-wall dynamics, spectral degeneracies, and crucially, the stability of time-crystalline order. Using disordered nearest-neighbor chiral interactions, we observe robust subharmonic period tripling that persists across a wide range of drive strengths and is independent of initial state. Finally, we highlight the special role that chirality plays in our $\mathbb{Z}_3$ discrete time crystal -- in its absence, the system's Floquet dynamics exhibit a marked initial state dependence governed by domain wall degeneracies. Our results establish native qudit hardware as a powerful platform to access a broader landscape of non-equilibrium phases.

Atom interferometers represent a promising approach for gravitational wave detection in the decihertz frequency band, complementary to existing light-based detectors. The South Pole offers unique advantages for such experiments: exceptionally low seismic noise, established infrastructure for large scientific projects, and a location that strengthens gravitational wave source localization through global triangulation. Here we discuss the scientific case and practical considerations for deploying a long-baseline atom interferometer at the South Pole, which has the potential to expand the global network of gravitational wave detectors while enabling precision tests of fundamental physics.

We develop an open quantum theory for shot-noise dynamics in dissipative chiral transport. By mapping a system under consideration onto a quantum circuit, we show that current noise is governed by two competing factors: the average occupancy distribution and particle-number fluctuations. With energy fully relaxed, shot noise is strongly suppressed, reflecting the stacking of electrons into lower energy states due to dissipation. This process quenches the partition noise from partially occupied levels, and finally isolates the residual noise protected by strong $U(1)$ symmetry. Moreover, selectively heating the source against the bath uncovers the underlying competition between the noise contributions from the occupancy distribution and those from the particle-number fluctuations. It triggers a sign reversal in inter-channel correlation noise, a signature masked by seemingly identical single-channel thermal noises. We propose an inversion scheme to experimentally reconstruct the hidden occupancy distribution directly from measurable noise cumulants.

We study distributed inner product estimation for $n$-qubit states using local randomized measurements, for which rigorous worst-case guarantees are less understood. We first reduce the minimax kernel optimization to Hamming-distance kernels. Within this class, unbiasedness fixes a unique kernel. For this kernel under local Clifford sampling, we prove a sharp fourth-moment bound using the single-qubit Clifford commutant. This yields worst-case sample complexity $\mathcal{O}(\sqrt{4.5^n})$, attained by identical pure product stabilizer states. For the same kernel under local Haar sampling, we prove a local twirling identity that compares its fourth moment with the Clifford fourth moment. This gives the same rigorous upper bound as in the Clifford case, but the comparison is lossy. This motivates the conjectured sharper Haar scaling $\mathcal{O}(\sqrt{3.6^n})$ attained by product states, and verify it for several important classes of states. We also show that independent single-qubit Pauli shadows have worst-case scaling $\mathcal{O}(\sqrt{7.5^n})$ for large $n$.

Nitrogen-vacancy (NV) centres in diamond can be used to detect radiofrequency (RF) signals through coupling of the RF magnetic field with the NV spins, combined with optical readout of the spin state. The sensitivity of such RF detectors has so far been mainly studied in terms of magnetic field sensitivity, which is relevant when the RF signal is generated by a near-field source. However, for applications where the RF input is delivered externally, a more relevant quantity is the sensitivity in terms of the input RF power. Here we theoretically analyse the power sensitivity of NV-based RF detectors as a function of the RF-spin interface geometry. We derive scaling laws of the power sensitivity for both slope-detection and variance-detection RF sensing protocols, and for various noise regimes. We find that, in most scenarios, the power sensitivity scales inversely with the characteristic physical dimension of the RF-spin interface, for instance the width of a coplanar waveguide or the diameter of a loop antenna. In other words, the smaller the structure and the probed NV volume, the better the power sensitivity, which is contrary to the case of magnetic field sensitivity. Lastly, we numerically estimate that photon shot noise limited sensitivities of 10^{-20} W Hz^{-1} (slope) and 10^{-12} W Hz^{-1/2} (variance) are achievable. This work lays the groundwork for further optimisation of NV-based RF detectors.

We present an empirical evaluation of quantum entanglement in agent coordination within quantum multi agent reinforcement learning (QMARL). While QMARL has attracted growing interest recently, most prior work evaluates quantum policies without provable baselines, making it impossible to rigorously distinguish quantum advantage from algorithmic coincidence. We address this directly by evaluating a decentralized QMARL framework with variational quantum circuit (VQC) actors with shared entangled states. In the CHSH game, which has a mathematically proven classical performance ceiling of 0.75 win rate, we show that entangled QMARL agents approach the Tsirelson limit of 0.854, providing clear evidence of their quantum advantage. We show that unentangled quantum circuits match the classical baseline, confirming that entanglement and not the quantum circuit itself is the active coordination mechanism. We also explore the effect of specific entanglement structures, as some Bell states enable coordination gains while others actively harm performance. On cooperative navigation (CoopNav), QMARL without entanglement achieves $\sim2\times$ improvement in success rate over classical MAA2C ($\sim$0.85 versus $\sim$0.40), with the hybrid configuration, quantum actor paired with a classical centralised critic, outperforming both fully classical and fully quantum solutions. We present our experimental analysis and discuss future work.

Hybrid quantum-classical (HQC) algorithms, such as the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA), are central to near-term quantum computing but remain challenging to test. Sampling-based fuzzing can expose faulty or non-convergent configurations, but under realistic execution budgets, it may miss failure-prone regions in the joint space of classical optimizer settings and quantum circuit parameters. This paper studies failure-guided fuzzing for HQC programs. It models a hybrid input as a pair of classical optimizer hyperparameters and quantum circuit parameters, and evaluates a two-phase strategy that first searches for non-convergent seeds and then locally fuzzes circuit parameters around those seeds. To understand where the gains come from, five budgeted strategies are compared: random hybrid testing, classical enumeration without fuzzing, random-seed local fuzzing, enumeration-seed local fuzzing, and concolic-seed local fuzzing. The study is implemented on a VQE instance and a QAOA MaxCut instance in Qiskit. The results show that failure-guided local fuzzing is the main driver of improvement over random testing, while concolic seed discovery provides additional benefits on VQE but is less stable on QAOA. These findings suggest that reusing failure information is a promising direction for HQC testing, but that the value of concolic seed discovery is workload-dependent.

What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from Augustine to Galileo -- and runs each through a neutral-atom quantum processor. The bridge is graphs: each textual unit becomes an atom, and graph edges are physical blockade constraints for engineered exact unit-disk designs, or a 2D approximation to the semantic graph for natural texts. Three contributions follow. First, we introduce rigidity rho, a metric for how unique a book's structural backbone is -- distinguishing Marguerite de Navarre's Heptameron (rigid, twelve-nouvelle hard core) from Boethius (fully fungible, every chapter substitutable). Second, we invert the pipeline: rather than extracting a graph from existing prose, we pick a target graph the hardware encodes natively, and write a book whose structure matches it. The twenty-nine texts written this way, collected under the name QOuLiPo, extend the OuLiPo tradition to graph-topological constraints and, together with the eight natural texts, form a benchmark distribution against which neutral-atom hardware can be tracked as it scales. Third, we run both natural and engineered texts on Pasqal's FRESNEL processor up to one hundred atoms; engineered texts reach high approximation ratios, the cleanest instances returning the exact backbone. A cloud-accessible quantum machine plus an agentic coding environment now lets a single investigator run this pipeline end-to-end. What is reported is an application layer, not a speedup -- humanistic instances ready to load onto neutral-atom processors as they scale, already complementing classical text analysis. The Digital Humanities community has a stake in building familiarity with this hardware now: the engineered-corpus design choices made today fix the benchmark distribution future hardware will be measured against.

This work concerns scalar field theories with topologically nontrivial vacuum manifold in rotationally symmetric backgrounds of arbitrary dimension. Lagrangians with canonical and generalized kinetic terms are considered, and a Bogomol'nyi framework is developed for the symmetric restriction of the theory. Localized topological solutions are found. Their stability, which would normally be prevented in higher dimensions due to scaling instability, is made possible by the presence of an explicit radial dependence on the potential. The first-order equations give rise to an integrable orbit equation which can be used to solve the problem completely. It is shown that target space orbits - but not the solutions themselves - are shared between analogous systems defined in different backgrounds. Moreover, the first-order equations can be mapped into a one-dimensional BPS theory through a transformation encoded by a function $ξ(r)$. The internal structure, size and existence of defects follows from the properties and range of this mapping. We use these tools to evaluate the effect of geometry on confinement, existence, and structure of solitons. Exact solutions are provided in Minkowski, Schwarzschild, de Sitter, Schwarzschild de Sitter and conformally flat backgrounds.

We investigate the spectral consequences of the uniquely determined Hermitian ordering of the Dirac Hamiltonian with spatially varying mass. In contrast to the nonrelativistic case, where continuous families of admissible prescriptions exist, the relativistic Dirac operator admits a single consistent ordering compatible with probability-current conservation. This requirement generates an additional logarithmic-gradient term proportional to the spatial variation of the mass profile. We show that this contribution modifies the effective kinetic operator and induces a universal deformation of the spectral quantization condition. In compact geometry, an explicit analytic computation reveals a mode-dependent second-order spectral shift that becomes strongly enhanced near the mass-inversion threshold. These results demonstrate that the consistent relativistic ordering of the Dirac operator leads to observable modifications of discrete spectra in spatially inhomogeneous scalar backgrounds.

We investigate the superhorizon behavior of scalar hair sourced by black holes in de Sitter spacetime in the linearly coupled shift-symmetric scalar-Gauss-Bonnet theory. Working in the test-field regime, we show that this hair exhibits both temporal and spatial growth on superhorizon scales. This growth is not a special consequence of the black hole, but instead follows from the dynamics of a minimally coupled massless scalar field in expanding de Sitter spacetime. Moreover, it is not even specific to black holes, but also arises for a point scalar charge in de Sitter, indicating that a scalarized black hole acts effectively as a localized subhorizon source of scalar perturbations. Backreaction, when important, first arises on subhorizon scales and does not by itself eliminate the superhorizon profile. The time-dependent scalar hair also carries a steady outward energy flux, which frames the test-field regime as a transient, and helps explain the difficulties encountered in attempts to construct self-consistent static solutions.

We propose an adiabatic-elimination formalism in the dispersive regime based on a transition-centric perturbation theory. The perturbative expansion is recast into a diagrammatic framework, while adiabatic elimination is implemented through controlled projections onto transition subspaces. Our approach applies systematically at arbitrary perturbation order, and is suited to multilevel systems and multiple qubits in both cavity and waveguide quantum electrodynamics. It ultimately enables the explicit construction of effective higher-order Hamiltonians while bypassing important limitations of existing techniques, thereby providing a practical toolbox for multiphoton processes in the dispersive regime.

We introduce a framework where light-matter transitions, rather than states, are the primary dynamical objects. Successive compositions of elementary transitions yield multiphoton processes with compact diagrammatic bookkeeping of resonant and off-resonant pathways. This approach enables transparent derivations of effective high-order Hamiltonians in the dispersive regime, foundational to quantum-information applications. Applied to the paradigmatic Jaynes-Cummings model, our framework reveals a photon-number-independent intrinsic Rabi frequency and persistent polaritonic hybridization in the dispersive regime, unifying resonant and dispersive limits.

In this work, we perform Markov Chain Monte Carlo (MCMC) analyses using the Planck 2018 cosmic microwave background (CMB) datasets, including temperature, polarization, and lensing, in order to compare matter bounce models with observational data. The particular model we considered contains a scalar field with an exponential potential, which behaves as dust in the asymptotic past of the contracting phase, it realizes a quantum bounce, and then behaves as a transient dark energy field at large scales in the expanding phase. The parameter $λ$ appearing in the exponential potential is directly related to the model's scalar spectral index, $n_s$, which is set free in the MCMC analyses, as well as the deepness of the bounce, which controls the amplitude of the power spectrum. We provide constraints on the cosmological parameters and compare the model's performance against the standard inflationary $Λ$CDM scenario. Our results indicate that Planck data alone cannot favor one model with respect to the other, showing that the model we investigate can be a viable alternative to inflation.

We propose a superconducting circuit based on the Bloch transistor, a quantum device consisting of two small-capacitance Josephson junctions connected in series and having a small island in between. This device is driven by two dc electrical sources controlling Josephson oscillations of frequency $f_J = 2e\overline{V_J}/h$, related to the average voltage $\overline{V_J}$ on the transistor, and Bloch oscillations of frequency $f_B = \overline{I_B}/2e$, related to the average current $\overline{I_B}$ injected into the transistor island. Due to the Bloch transistor properties, these two types of oscillations can mutually phase lock, i.e., $f_J = f_B$. This leads to formation of current steps on the current-voltage curve at $\overline{I}_B = 2ef_J$, which are similar to the dual Shapiro steps appearing at current $\overline{I}=2ef$ under microwave irradiation of frequency $f$. Moreover, transconductance $\overline{I_B}/\overline{V_J}$ takes the fundamental value of $1/R_Q$, where $R_Q = h/4e^2$ is the resistance quantum. The obtained results pave the way to the alternative quantum standard of resistance, based on the superconducting circuit and operating without applying strong magnetic field.

The quasi-normal modes of black holes play various important roles in gravitational wave theory, signal modeling, and data analysis; however, there remain open questions about their mathematical properties. Aspects of classical polynomial theory have been proposed as a framework to investigate quasinormal mode orthogonality and completeness. We have recently presented a class of polynomials that are "natural" to quasi-normal modes in that they are restricted by the quasi-normal mode boundary conditions, and exactly tridiagonalize Teukolsky's radial equation. In turn, these polynomials may be useful for better understanding the vector space properties of quasi-normal mode solutions to that equation. Here, we provide an overview of these polynomials' analytic properties: their 3-term recurrence relation, ladder operators and governing differential equation. We demonstrate that the natural polynomials for Schwarzschild and Kerr black holes are Pollaczek-Jacobi polynomials with complex valued parameters. Along the way, we observe a novel property that is particular to Schwarzschild: the polynomials' 3-term recurrence relation always peaks at the physical overtone index. This work supports the broader application of these polynomials, as well as their extension to black hole spacetimes beyond Schwarzschild and Kerr.

Graviton lasers have been considered in the past, \cite{gl}, but practical terrestrial implementations appear infeasible. The absence of any known mechanism to reflect gravitons means that it remains unclear how a graviton beam could be directed repeatedly through a putative lasing medium. Astrophysical graviton lasing is still a possibilty as circular graviton orbits around blackholes afford the possibility of an arbitrarily long path length through the lasing medium of ultra-light dark matter \cite{bhgl,nhaxs}. In this essay, we consider the possibility of a graviton laser that could be constructed in a laboratory setting. The graviton lasing medium could be one of many possible gravitating systems, of which we give three possible examples. We calculate the possibility of reflecting the gravitons by using the conversion of gravitons into photons in an external magnetic field, the Gertsenshtein effect, \cite{Gertsenshtein1962}. We may convert the gravitons to photons, then reflect the photons, then reconvert the photons into gravitons via the same effect, and then pass them through the graviton lasing medium. With an identical apparatus on the other side, we can essentially extend the path length of the gravitons through the lasing medium as arbitrarily long as desired.

Achieving practical quantum advantage on fault-tolerant quantum computers (FTQC) is fundamentally constrained by the substantial spatial and temporal overheads required to map logical operations onto physical hardware. Existing compilation approaches typically adopt coarse-grained, slice-based abstractions that overlook fine-grained microarchitectural effects, such as routing contention, leading to inefficient resource utilization and limited alignment between algorithm structure and hardware capabilities. This work presents a microarchitecture-aware compilation approach that integrates algorithmic structure directly with lattice surgery (LS) execution. By leveraging the commutativity of C-Phase operations, the method transforms inherently sequential gate sequences into concurrent multi-target interactions, effectively removing artificial dependencies and exposing significant instruction-level parallelism. To enable this, we design a dynamic, event-driven scheduling strategy that accurately models spatial layout and routing constraints, allowing operations to overlap in time while minimizing contention. Through improved coordination of computation and communication, this approach substantially reduces idle resources and achieves up to a 59.7$\times$ reduction in execution time compared to standard baselines.

Traversable topological bridges traditionally require exotic matter, violating the Null Energy Condition (NEC). This essay investigates whether matter-vacuum coupling can circumvent this necessity. Focusing on zero-tidal-force solutions, we establish a rigorous no-go theorem for static configurations, proving that such coupling cannot bypass the requirement for NEC violation. We demonstrate that the geometric flare-out condition is incompatible with NEC-compliant sources, regardless of the coupling $Q$ or equation of state. Crucially, the vacuum fails to shield the throat; instead, interaction gradients mathematically obstruct the required geometry. This result suggests that causality protection is inherent in the field equations, rendering the vacuum's evolution a regulator rather than a facilitator of topological shortcuts, thereby reinforcing the robustness of classical energy conditions.

Quantum computing has demonstrated its potential to solve various optimization problems, including drone scheduling, which is important not only for drone delivery but also for logistics in general. However, one of the main obstacles is that practical drone scheduling settings typically require quantum resources that current hardware cannot provide. Therefore, in this work, we introduce a new Quantum Optimization via Coordinate Descent (QUACOD) approach to address this problem under the constraint of a limited number of available qubits. By leveraging coordinate descent, QUACOD decomposes the original high-complexity problem into multiple subproblems, which are then solved using quantum optimization. In our experiments, QUACOD outperforms the state-of-the-art (SOTA) quantum-based drone scheduling method not only in optimized drone completion times but also in scalability, handling up to 5 times more drones and 35 times more routes. In addition, QUACOD demonstrates that hardware-efficient circuits are effective for optimization problems. Together, these contributions advance quantum computing toward practical applications in the noisy intermediate-scale quantum (NISQ) era.

We introduce Graphical Algebraic Geometry (GAG), a family of diagrammatic languages extending the Graphical Linear Algebra programme. We construct several languages within this family and prove that they are universal and complete for the corresponding (co)span semantics of commutative algebras and affine varieties. This framework provides clear graphical representations of algebraic structures -- such as polynomials, ideals, and varieties -- enabling intuitive yet rigorous diagrammatic reasoning. We showcase two practical viewpoints on GAG. First, we show that instances of counting constraint satisfaction problem (#CSP) are recast as rewrite problems of closed diagrams in GAG. This means that deciding rewritability in GAG is #P-hard, and GAG can be viewed as a complete and compositional rewrite system for networks of polynomial constraints. Second, we characterize the qudit ZH calculus, a diagrammatic language for quantum computation, as an extension of Graphical Algebraic Geometry. This establishes the correspondence that Graphical Algebraic Geometry is to the ZH calculus what Graphical Linear Algebra is to the ZX calculus. Using this construction, we show that computing amplitudes in qudit ZH requires only a constant number of queries to a GAG oracle.

Inverse problems in scientific sensing are often solved with either hand-designed regularizers or supervised networks trained on simulated labels, yet both can fail when the forward model is nonlinear, spectrally coupled, and physically delicate. We study this issue for noise sensing based on nitrogen-vacancy (NV) centers in diamond, where a quantum sensor measures magnetic-noise spectra generated by sparse spin sources. We show that replacing a common scalar/coherent forward approximation with a tensor power-summed dipolar operator changes the inverse landscape and exposes a center-collapse failure mode in free-density optimization. We propose NeTMY, an amortization-free coordinate neural field coupled to the differentiable NV forward model, with annealed positional encoding, multiscale optimization, sparsity/gating, and spectrum-fidelity losses. Across sparse synthetic reconstructions generated by the corrected operator, NeTMY achieves the best localization and distributional metrics in the tested benchmark. Mechanism experiments show that NeTMY does not directly execute the raw density-space gradient; its parameterization smooths and redistributes updates, mitigating the center-collapse pathology. These results position NV quantum sensing as a useful testbed for physics-faithful neural inverse problems.

Solving non-linear Diophantine systems lies at the mathematical core of integer optimization and cryptography. While the general unbounded problem is undecidable, even over bounded integer domains it remains classically intractable in the worst case. In this work, we introduce a fully reversible quantum algorithmic framework tailored to solve arbitrary polynomial Diophantine equations over bounded integer domains. The core of our approach is the explicit, gate-level synthesis of an evaluation oracle for amplitude amplification. By coherently evaluating polynomial constraints via in-place two's complement arithmetic and routing operations into a single recycled accumulator, this garbage-free strategy achieves a compact and scalable synthesis of the underlying non-linear arithmetic. Through analytical derivations and empirical circuit simulations, we prove that the overall spatial complexity is bounded by $q = \mathcal{O}((n + d^2)\log_2 N)$ logical qubits for $n$ variables, maximum degree $d$, and interval length $N$. The non-Clifford Toffoli depth is upper-bounded by $\mathcal{O}(q^2)$. This structural scaling exponent remains invariant to the variable count, modulated linearly only by the coefficients' Hamming weights. By moving beyond abstract black-box assumptions, this explicit architectural synthesis guarantees that the necessary quantum arithmetic acts as a bounded polynomial overhead. This ensures a quadratic speedup over classical exhaustive search, whether retrieving a unique assignment or dynamically enumerating an unknown number of solutions.

Quantum machine learning (QML) aims to accelerate machine learning tasks by exploiting quantum computation. Previous work studied a QML algorithm for selecting sparse subnetworks from large shallow neural networks. Instead of directly solving an optimization problem over a large-scale network, this algorithm constructs a sparse subnetwork by sampling hidden nodes from an optimized probability distribution defined using the ridgelet transform. The quantum algorithm performs this sampling in time $O(D)$ in the data dimension $D$, whereas a naive classical implementation relies on handling exponentially many candidate nodes and hence takes $\exp[O(D)]$ time. In this work, we construct and analyze a quantum-inspired fully classical algorithm for the same sampling task. We show that our algorithm runs in time $O(\operatorname{poly}(D))$, thereby removing the exponential dependence on $D$ from the previous classical approach. Numerical simulations show that the proposed sampler achieves empirical risk comparable to exact sampling from the optimized distribution and substantially lower than sampling from the non-optimized uniform distribution, while also exhibiting exponentially improved runtime scaling compared with the conventional classical implementation. These successful dequantization results show that sparse subnetwork selection via optimized sampling can be achieved classically with polynomial data-dimension scaling on conventional computers without quantum hardware, providing an alternative to the existing quantum algorithm.

Semiconductor hole-spin qubits offer a promising route to quantum computation due to their weak hyperfine interaction, and strong intrinsic spin-orbit coupling enabling electric control of qubits. Scalable architectures, however, require coherent long-distance quantum state transfer, which is hindered in these systems by spin-orbit induced anisotropic exchange. Here we show that this limitation can be overcome by using an all-electric control protocol. By tuning the electric field strength, we identify discrete spin-orbit phase-matching conditions that restore near-perfect state transfer, independent of the rotation axis. Complementarily, controlling the electric field direction aligns the spin-orbit axis, suppressing excitation non-conserving processes and enabling robust transfer without fine tuning. Our results establish that electrical control of spin-orbit phases through either magnitude tuning or axis alignment as a practical route for robust quantum information transport in hole-spin quantum dot arrays.

We study quantum mechanics of bosonic multi-matrix Lagragians in the collective field framework, with particular emphasis on three matrix models. We derive the effective Hamiltonian of the collective field and study the vacuum solution and its stability.

Recent work has identified a dynamical squeezing phase transition in power-law interacting bilayer XXZ spin models, separating a fully collective phase with Heisenberg-limited squeezing from a partially-collective phase with universal critical scaling. Here we test and establish the universality of this transition along two qualitatively different microscopic axes: lattice geometry, by studying square, triangular, and honeycomb $2\mathrm{D}$ bilayers as well as $1\mathrm{D}$ ladders, and a symmetry-preserving rescaling $λ$ of the interlayer couplings relative to the intralayer ones. Combining a Bogoliubov instability analysis with discrete truncated Wigner simulations, we find that the transition persists across all four lattice geometries and over a wide range of $λ$ with critical exponents consistent within error, providing strong evidence for a genuine non-equilibrium universality class. The Bogoliubov theory recovers the previously identified scaling $a_Z^* \propto L$ in the long-range interacting regime $α< d+2$, and yields an analytical scaling $a_Z^* \propto L^{2/(α-d)}$ for the critical aspect ratio with system size for $α>d+2$, with $α$ the power-law exponent in dimension $d$. This uncovers a previously unrecognized sub-linear regime for short-range interactions. By tuning $λ$ we vary the interlayer coupling strength at fixed layer spacing, demonstrating that the dynamical transition can be driven purely through interaction engineering without modifying the underlying geometry. These findings provide a versatile route toward controlling entanglement generation in Rydberg-array, polar molecule, and trapped-ion platforms with applications in quantum sensing and simulation.

We revisit the Hartle-Hawking wave function in AdS spacetime, where natural spatial slices are open and require an additional spacetime boundary. This leads to two constructions: a fully gravitational wave function, in which the boundary configuration is integrated over, and a partially frozen one, in which it is fixed, as in AdS/CFT. To illustrate the fully gravitational construction, we explicitly analyze it in AdS$_3$ Einstein gravity and AdS$_2$ Jackiw-Teitelboim gravity. We then evaluate the one-loop correction to the hyperbolic-ball partition function in $D$-dimensional AdS Einstein gravity, expected to give the leading contribution to the wave-function norm. We demonstrate that the fully gravitational hyperbolic ball partition function, where the boundary fluctuates, develops a nontrivial one-loop phase of $(\mp i)^{D+1}$, analogous to that of the sphere partition function in dS gravity. By contrast, the partially frozen partition function, where the boundary is fixed, remains real and positive. Motivated by this AdS comparison, we conversely investigate a partially frozen dS sphere partition function where the metric on an equator is fixed, finding that its one-loop phase cancels nontrivially. Our results suggest that the phase problem is controlled by whether the gravitational path integral is fully dynamical or partially frozen.

We construct new families of everywhere regular, asymptotically flat solitons in the Einstein--Proca model, obtained as self-gravitating continuations of flat-spacetime (singular) Proca multipoles. First we consider static and axially symmetric solutions, organized by a multipole number $\ell$. Two distinct classes arise: electric-type configurations, which include the spherical Proca stars as the $\ell=0$ case, and magnetic-type configurations, which have no spherical counterpart and start at $\ell=1$. Then we construct hybrid solutions as nonlinear superpositions of electric and magnetic multipoles. These have non-vanishing local angular momentum density but vanishing total angular momentum, and in some cases have no north-south $\mathbb{Z}_2$-symmetry. By performing dynamical evolutions of Proca stars in the new magnetic and hybrid sectors, we show they are unstable, decaying to the (static) prolate Proca stars or the (stationary) spinning Proca stars, previously identified as dynamically robust, electric sector configurations. In some cases, they can also collapse into a black hole.

We construct charged black hole solutions in bumblebee gravity coupled to a general class of nonlinear electrodynamics (NLED) using an auxiliary Maxwell-scalar formalism. The norm-fixed radial configuration of the bumblebee vector makes the solutions asymptotic to a conical Lorentz-violating vacuum and requires stringent nonminimal bumblebee-NLED couplings. The general black hole solutions contain independent mass and charge parameters. There are two sources of singular behavior at the center: one is due to the Schwarzschild-type pole and the other is the residual conical singularity of the Lorentz-violating vacuum. By fine-tuning the mass-charge relation, one can generally remove the pole singularity, giving rise to marginally regular black holes. For a suitable NLED theory such as Born-Infeld theory, both singularity sources can be removed at the cost of requiring both the mass and the charge to be fine-tuned to specific functions of the coupling constants. The resulting solutions describe regular horizonless spacetimes interpolating from AdS or dS cores to Lorentz-violating vacua.

The recent success of gravitational-wave (GW) astronomy together with renewed plans for lunar geophysical instrumentation has revived interest in using the Moon as a resonant detector for mid-frequency (mHz-Hz) GWs. In realistic observational scenarios, the GW strain amplitude is expected to be constrained independently by networks of GW detectors, which motivates an inverse, \emph{tomographic} question: to what extent can measurements of the Moon's seismic response to known GWs be used to infer its internal structure? In this work, we develop a first-principles, perturbative framework that maps spherically symmetric perturbations of the elastic and density structure to measurable changes in observables, especially GW-driven modal amplitudes of the Moon. The formalism combines (i) a normal-mode representation of the elastic response, (ii) first-order perturbation theory for eigenvalues and eigenfunctions, and (iii) a linearized observation model that links frequency and amplitude observables to model parameters (bulk and shear moduli, density, and interface locations) and their perturbations. We show that the estimation errors of the Moon's elastic parameters can be reduced by about an order of magnitude with observations of calibrated GWs.

We construct families of deformations of the double-scaled SYK (DSSYK) model and investigate their bulk interpretation. We introduce microscopic deformations of the SYK model which, after ensemble averaging and in the double-scaling limit, are described by a transfer matrix encoding the recurrence relations of basic orthogonal polynomials in the q-Askey scheme. For certain families of deformations in the semiclassical limit at finite temperature, the chord number (encoding Krylov complexity) corresponds to the length of an Einstein-Rosen bridge connecting an End-Of-The-World brane to an anti-de Sitter asymptotic boundary. By increasing one of the deformation parameters, the models eventually exhibit discrete energy levels, signaling a new geometric transition in sine dilaton gravity. Via the SYK-Schur duality, Krylov complexity also admits a representation-theoretic interpretation as the spread of the SU(2) spin in the index of an $\mathcal{N}=2$ SU(2) gauge theory. We study the operator algebras of the deformed theories. The algebras can be type II$_1$ or type I$_\infty$ factors, depending on the operators that are included. The entanglement entropy between the type II$_1$ algebras for a pure state manifests as an extremal surface through the Ryu-Takayanagi formula. We discuss connections between our results and the emergence of baby universes in the bulk.

We construct a new Ricci-flat metric by demagnetizing the recently reported Kerr-Bertotti-Robinson (KBR) solution. The metric is a deformation of the Kerr metric characterized by a parameter $B$, so that the asymptotic Kerr becomes a regular dome of spindle shape with north and south poles. Despite lacking an asymptotically-flat region, we find that the first law of black hole thermodynamics can be established. Some thermodynamic relations are identical to those of the Kerr black hole, as if the constant $B$ is absent. Our Ricci-flat rotating metric serves a neutral seed for a variety of inequivalent schemes of magnetizing the Schwarzschild and Kerr black holes.

For three-dimensional non-interacting multi-band metals, we show that important information about the shape and the quantum geometry of Fermi surfaces is encoded in the subleading logarithmic term of bipartite charge fluctuations. This logarithmic term is related to the dimensionless $|\mathbf{q}|^3$-coefficient of the structure factor in momentum space, and both quantities can be expressed as Fermi surface integrals of the Fermi surface curvature tensor and the quantum metric tensor. When the real-space partition surface is a quadric (i.e., sphere or ellipsoid), the logarithmic coefficient satisfies a topological bound depending only on the Euler characteristic and the Chern number of the Fermi surface, illustrating a non-trivial interplay between topology and quantum topology in multi-band metals.

We present an analytic method for computing gravitational-wave fluxes from bound Schwarzschild geodesics with arbitrary eccentricity. Our approach systematically expands the Fourier coefficients of the emitted radiation in a Chebyshev basis, allowing them to be reduced to sums of Keplerian-like Fourier coefficients previously derived in the Quantum Spectral Method. Because the construction does not rely on a small-eccentricity expansion, it applies to a broad range of bound eccentric orbits. As an illustration, we implement the method using a $15$PN-expanded input and find that it reproduces the total flux for the case $(p,e)=(12.5,0.5)$ to relative accuracy $10^{-5}$, while for the stronger-field case $(p,e)=(10,0.8)$ it yields weighted mode-by-mode errors below $10^{-6}$ for the selected dominant modes analyzed. These results provide an analytic route to frequency-domain flux calculations relevant to EMRI modeling.

While the interplay of correlations and geometric frustration in doped Mott insulators provides a fertile ground for exotic quantum phases, the nature of the metallic state emerging upon particle doping remains poorly understood. In this work, we investigate the triangular-lattice Hubbard model with particle doping and provide compelling evidence for an intrinsic, interaction-driven quantum state, which we term the Nagaoka supermetal. This state is characterized by a sublinear temperature dependence in the DC resistivity, along with singular behaviors in the charge compressibility and zero-frequency spectral weight. To understand the origin of these singular properties, we derive an effective low-energy model and demonstrate that a higher-order Van Hove singularity emerges from the reconstructed dispersion. This singularity gives rise to a power-law divergence in the density of states, capturing the anomalous properties observed in the supermetallic regime. Our findings offer a new perspective on non-Fermi liquid states in geometrically frustrated systems and are directly accessible in current ultracold atom experiments.

We solve an open problem in entanglement theory posed by Yu et al., {\it Nature Communications 12, 1012 (2021)}. The problem is to show, via an entanglement witness, that the $14$-qubit state $Φ_{\text{E8}}$ is entangled. Inspired by a method from quantum codes, we combine symmetric extension with moment matrices to prove that $Φ_{\text{E8}}$ is entangled. The proof has the form of a rational infeasibility certificate for a semidefinite program, yielding an explicit entanglement witness. Our approach unifies and extends several earlier methods that involve the Lovász theta number of the Pauli anti-commutativity graph, promising scalability and flexibility in further applications.

We develop a rigorous evaluation of Dirac brackets for classical observables on the phase space of radiative gravitational modes at null infinity that naturally incorporates memory effects. Considering the Ashtekar-Streubel phase space, with boundary conditions in time given by vanishing {\it news} and purely electric {\it shear}, and taking into account the infinite dimensionality of the phase space, we identify the algebra of proper observables (understood as functions on phase space that can be associated with smooth symplectic flows). We show that the action of supertranslation charges generate the correct transformations on the shear. We also show that the conventional definition of the ``Goldstone mode'' adopted in the literature cannot be associated with a proper observable, but nevertheless there exists an infinite family of proper observables, which we call {\it Goldstone probes}, that are capable of measuring the Goldstone mode. We notice that there are no Goldstone probes constructed only out of the shear {\it or} the news, providing a possible explanation for why attempts to construct a (separable) Hilbert space with different memory states have failed so far. Finally, we derive formulas for distributional Dirac brackets between local shear and news, and show that they contain non-local corrections.

We investigate the structure and emission properties of a thin accretion disk around a rotating charged black hole described by an effective higher-curvature-inspired spacetime, constructed as a phenomenological deformation of the Kerr Newman geometry. In this framework, the deformation is introduced through a modification of the metric function $Δ$ by an effective Gauss-Bonnet-like parameter $α$, such that the spacetime reduces to the standard Kerr Newman solution in the limit $α\to 0$. Adopting a kinematical approach, we use test-particle motion to derive the specific energy, specific angular momentum, and angular velocity of circular orbits, and analyze the effects of the parameters $α$ and charge $Q$ on the innermost stable circular orbit (ISCO), radiative efficiency, radiation flux, temperature, and differential luminosity of the disk. We find that increasing $α$ shifts the ISCO inward and enhances the disk's radiation flux and temperature, while the presence of charge suppresses these quantities due to electrostatic effects. Our results demonstrate that effective higher curvature deformations of rotating black hole spacetimes can lead to observable deviations from the Kerr case, highlighting accretion disks as sensitive probes of strong-gravity effects without relying on a specific underlying gravitational theory.

Variational quantum algorithms (VQAs) are a central paradigm for noisy intermediate-scale (NISQ) quantum computing, yet their reliance on predesigned and pretrained variational quantum circuits (VQCs) introduces critical security vulnerabilities, particularly backdoor attacks. These attacks embed hidden malicious behaviors that remain dormant under normal conditions but are activated by specific triggers, leading to adversarial outcomes such as incorrect predictions or manipulated objective values. This paper presents a survey of backdoor attacks in VQCs, covering data-poisoning, compiler-level, and quantum-native mechanisms. We formalize key terminology and threat models, and review existing attack strategies along with their empirical characteristics. We also analyze current detection and defense approaches, highlighting their limitations, especially against quantum-specific threats. By synthesizing recent advances, this survey outlines the evolving security landscape of VQCs and identifies key challenges and future directions for developing robust, quantum-aware defenses in hybrid quantum-classical systems.

This essay discusses recent progress on Euclidean wormholes as candidate contributions to the Universe's initial quantum state. The comparison with the Hartle-Hawking no-boundary proposal highlights both a conceptual affinity and genuine advance: wormholes retain the relevance of Euclidean-saddles as encoders of properties of cosmological wavefunctions, while they broaden the class of regular saddles that are physically relevant for inflating universes and are capable of resolving issues that plague the no-boundary proposal. The principal achievement of the wormhole program is to enlarge the semiclassical initial-condition land-scape in a way that is physically rich, conforms with Holographic expectations and as such becomes increasingly relevant for early-universe model building, within UV complete theories of quantum gravity.

Using techniques from the theory of von Neumann algebras, we propose a framework for addressing questions of controllability of bilinear systems on infinite dimensional Hilbert spaces. In the setup, we assume only that the drift and control terms arising in a bilinear control system are affiliated with a von Neumann algebra of finite type acting on the same Hilbert space. When the control terms satisfy basic norm bound conditions, we prove existence of time-optimal controls. In the more general setting where all operators may be unbounded, we show how the dynamical Lie algebra for the system is still well-defined and may be used to check approximate controllability of the system in question. We discuss how this approach can be applied to classical dynamical systems through the Koopman operator formalism, and investigate potential candidates for the von Neumann algebra which may guide the choice of controls. We illustrate how an affiliation relation naturally arises in both classical and quantum control systems with a few examples.

We study the fully generalized Grover's algorithm to find the optimal phase changes for each step of the iteration to maximize gain in probability of observation of the target, and when phase matching is required. We find that classical Grover's algorithm and phase matching remains to be optimal till the target probability gets close 1. However, as the probability of observation approaches 1, the optimal phase changes differ from $π$ and no longer observe phase matching. We provide the optimization statement to find the optimal phase changes given the current amplitude vector and the size of the set. To analyze this formula, we approach it from a numerical and analytical perspective, with the analytical perspective focusing on special cases that simplify the optimization and allow for general statements about its behavior. Finally, we provide an example of a 5 qubit system and show that for the final iteration the optimal phase changes differ from traditional Grover's algorithm and do not observe phase matching, but lead to an increase in the probability of the target.

In this article, we introduce a new form of quantum selective measurement in which the von Neumann projection postulate is replaced by quasilinear evolution, governed by a nonlinear generalization of the von Neumann equation. We demonstrate that this equation preserves the equivalence of quantum ensembles and, consequently, satisfies the no-signalling principle, ensuring consistency with both quantum mechanics and Einstein causality. Our approach eliminates the need for instantaneous, discontinuous state collapse and provides a unified description of the postmeasurement quantum state reduction as a form of quantum state evolution. Notably, it does not require invoking concepts such as the quantum state assigned to a classical apparatus. At the same time, the stochastic character of selective measurement and the Born rule remain unchanged. We present several numerical solutions of the evolution equation for quasilinear selective measurement in two-level quantum systems and compare them with the standard von Neumann projection. The results demonstrate agreement between the two measurement schemes in their fundamental properties. Furthermore, we investigate phenomena associated with the structural instability of the evolution equation and identify very narrow parameter regions in which the outcomes deviate from those predicted by the von Neumann projection. These regions may offer opportunities to test the proposed approach experimentally. Finally, using specific analytical solutions, we discuss the Stern-Gerlach experiment within the framework of quasilinear measurement.

Enhancing quantum illumination with highly entangled probes remains an active area of research. In this context, non-Gaussian operations provide an effective route for engineering probe states that can surpass the standard two-mode squeezed state (TMSS). In this work, we investigate a specific nonlocal non-Gaussian operation protocol and show that the engineered state using this protocol outperforms previously considered local non-Gaussian scenarios, engineered based on photon catalysis, addition, and subtraction under realistic conditions, including photon loss. Furthermore, by employing a $50{:}50$ beam splitter with photon-number difference detection, we demonstrate a significant enhancement in the signal-to-noise ratio (SNR) for target detection relative to the TMSS. Thus, our protocol exhibits improved performance, highlighting a resource-efficient and experimentally feasible probe for enhanced quantum illumination.

We propose replacing the instantaneous state reduction in von Neumann selective measurement with continuous nonlinear evolution. Despite its nonlinearity, this evolution preserves the equivalence of quantum ensembles and hence obeys the no-signaling principle. Its final states coincide with those produced by the von Neumann projection. The defining features of rank-one projective measurement are retained: convergence to the eigenstate of the observable associated with the selected outcome, independence of this final state from the initial state, and consistent action on entangled states.

A key science target of the Large Interferometer Space Antenna (LISA) is to carry out multi-messenger observations of massive black hole binaries, observing the merger simultaneously in gravitational waves and with electromagnetic observatories. Identifying that a merger is happening and providing an updating estimate of the sky location in the hours, days and weeks before the merger is critical to enable electromagnetic observations of the merger event. In this work we demonstrate and compare two methods for premerger identification of massive black hole binaries; a zero-latency filter approach and, for the first time, an approach using an ``inpainting'' technique. We apply these methods to the LISA Data Challenge dataset 2a--Sangria-HM--and demonstrate the successful recovery of the 14 signals in the dataset that we expected to be identifiable at least half a day before merger. We show that the inpainting method can identify premerger signals even when gaps are present in the data, demonstrating the recovery of a signal even when 3 day-long data gaps are added to the 14 days preceding merger. Finally, we explore the challenge of overlapping signals, using a region of overlapping signals in the Sangria-HM dataset, all of which merge within a 10-day window, and show how removing signals that have been confidently identified from the data allows us to identify quieter signals in the same period.

We consider perturbations in the isotropic and homogeneous cosmological model with the spatially flat Friedmann-Lemaitre-Robertson-Walker metric in the framework of the theory of gravity with non-minimal derivative coupling. The Lagrangian of the theory contains the coupling term $ηG^{μν}\nabla_μφ\nabla_νφ$ and represents the particular example of a general Horndeski Lagrangian, which results in second-order field equations. It is known that the non-minimal derivative coupling crucially changes scenarios of the Universe evolution on early times. In particular, the $η$-term is dominating on early times and leads to a primary quasi-de Sitter (inflationary) stage which needs no fine-tuned potential. On late times the influence of non-minimal derivative coupling on the Universe evolution completely disappears, and this naturally leads to the transition to the standard cosmological evolution (post-inflationary stage). We have derived a complete set of equations which describe an evolution of scalar, vector and tensor modes of perturbations. All modes are analyzed analytically in two asymptotic cases, and then we construct exact numerical solutions which describe an entire evolution of the modes. We show that all modes, including vector ones, are amplified in the quasi-de Sitter (inflationary) stage, and such the behavior is cardinally distinct from that in Friedmann cosmology.

In a recent series of papers we developed a first-principle and gauge invariant approach to black hole perturbation theory valid to any order. We included back reaction effects to tackle the situation of evaporating black holes and obtained an explicit expression for the dynamics of the reduced phase space to second order. The physics of evaporating black holes is in particular encoded by apparent horizons, an observer dependent generalisation of the event horizon. We determine the shape of the apparent horizon to second order in the perturbations. The area of the apparent horizon is an interesting observable which is expected to decrease in the quantum theory due to Hawking evaporation. We show how the full four dimensional metric can be reconstructed in terms of the reduced phase space variables. In the quantum theory, taking expectation values of this metric, we obtain an effective classical metric, whose causal structure can then be visualised in a quantum corrected Penrose diagram. We conclude with an outlook into the quantisation procedure in the reduced phase space formalism and the implications on the area of the apparent horizon.

Quantum computers promise exponential speedups for problems in cryptography, chemistry, and optimization. Realizing this promise requires fault tolerance: physical qubits are noisy, so logical qubits must be encoded redundantly across many physical ones using quantum error-correcting codes. In most practical fault-tolerance schemes, T gates cannot be implemented transversally and instead require costly magic-state distillation protocols involving a complex set of operations. As a result, T-gate count can dominate the resource budget of large-scale quantum computations, making T-count minimization a central bottleneck on the path to quantum advantage. Existing T-count optimization tools, however, do not scale to the circuits that quantum advantage demands. We present theoretical and practical results on T-gate optimization. On the theoretical side, we give a linear-time randomized algorithm for phase folding, based on a novel randomized static analysis. Our static analysis soundly approximates the set of reachable quantum states with an arbitrarily high probability. Our key insight is a static analysis that does not track symbolic expressions, but propagates constant-width bitstrings down the circuit. On the practical side, our implementation, TZAP, is multiple orders of magnitude faster than state-of-the-art tools -- such as PyZX, VOQC, and Feynman -- closely matches their T-count reductions on standard benchmarks, and within seconds on a laptop computer can optimize circuits with millions of gates.

In quantum many-body dynamics, locally encoded information typically scrambles across the entire system, becoming inaccessible to local probes. The upper bound of accessible information of local probes can be characterized by the Holevo information via optimal measurement. In this work, we investigate the information dynamics of quantum scrambling utilizing local randomized probes, quantified by the averaged accessible information (AAI). We derive an analytical expression for the AAI under Haar-random measurements and demonstrate that it is a function of purity of local reduced density matrix. Operationally, we employ the classical shadow protocol, using only single-qubit randomized Pauli measurements, to efficiently extract the AAI across extended subsystems. Through numerical simulations across diverse many-body paradigms, we show that the AAI can reveal distinct scrambling behaviors, resolving phenomena that range from dynamical confinement and ballistic transport to persistent scar revivals and many-body localization. This work highlights a pragmatic paradigm shift--from relying on optimal measurements to utilizing randomized local probes--for the characterization of complex quantum information dynamics.

High-purity germanium (Ge) has re-emerged as a versatile semiconductor platform for spin-based quantum information processing because it combines mature materials processing, access to spin-free isotopes, high mobilities, small effective masses, and strong but engineerable spin--orbit coupling. However, ``Ge qubits'' are not a single technology. Donor spin qubits, acceptor spin qubits, gate-defined hole spin qubits, and gate-defined electron spin qubits exploit different parts of the Ge band structure and therefore make distinct trade-offs among coherence, controllability, fabrication complexity, and scalability. Here we compare these four Ge-based spin-qubit modalities on a common physical and architectural footing. We review the shared Ge materials physics, including isotopic purification, the multivalley \(L\)-point conduction band, the spin-\(3/2\) valence band, heavy-hole/light-hole mixing, strain, interfaces, disorder, and phonons. We also introduce a common framework for estimating phononic-crystal-modified \(T_1\) using a calibrated reference relaxation rate, a geometry-dependent strain-density-of-states suppression factor, and parasitic relaxation channels. The comparison shows that gate-defined Ge hole-spin qubits currently offer the strongest combination of all-electrical control, demonstrated multiqubit operation, and scalability. Donor, acceptor, and gate-defined electron qubits remain important complementary directions for memory, hybrid, and exploratory architectures. Overall, Ge supports a diverse qubit ecosystem, with gate-defined hole-spin qubits presently providing the clearest path toward scalable Ge-based quantum processors.

We analyze the decoherence of a particle's spatial superposition moving along a stationary worldline through the Minkowski vacuum. The particle is modeled via an internal degree of freedom that couples to a scalar field, and an external degree of freedom, i.e., its quantized center-of-mass motion around the stationary worldline. Assuming a separation of time scales between the particle's internal and external dynamics, we first obtain an effective red-shifted polarizability of the particle, characterizing the trajectory-dependent linear response of the internal oscillator to the field. We then derive a quantum Brownian motion master equation for the particle's center of mass, under the Born-Markov approximation, which describes its decoherence in the position basis, as well as, Hamiltonian modifications corresponding to a dispersive potential. The resulting decoherence has two components: (1) arising from a modified field spectrum observed by the particle; and (2) due to a differential time-dilation over the particle's extended spatial wavefunction. For stationary trajectories, both contributions take an effectively thermal form. We evaluate the decoherence rates for two specific cases of hyperbolic and uniform circular motion.

A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum computer. One extremely important subproblem in quantum compilation is the generation of a logical to physical qubit mapping. Typically in quantum compilers this step is either implemented as a random or a heuristic based assignment that aims to minimize additional (SWAP) gate overhead in the quantum circuit. In this paper, we present an alternative approach to solving the qubit mapping problem. Specifically, we formulate the qubit mapping problem with a combinatorial optimization (CO) objective. We then present a method to find a solution to the CO problem by training a reinforcement learning (RL) policy. We also propose a local search based post-processing algorithm to further reduce the overhead. Our results show a dramatic improvement over conventional techniques in reducing the number of SWAPs. On different real world datasets like MQTBench and Queko circuits, our trained policy achieves a \textbf{65-85\%} reduction in SWAP overhead when compared to existing quantum compilers.

It is often stated that a phase of standard, decelerated cosmological expansion is characterised by the absence of global event horizons, while a phase of accelerated expansion is associated with the absence of particle horizons. This is not necessarily true because such horizons, being non-local properties of the spacetime geometry, depend on the full (past and future) history of the given cosmological background. We provide examples of various different scenarios for the case in which the final asymptotic phase of standard expansion and decreasing curvature is connected, through a regular bounce, with an initial (and possibly infinitely extended in time) regime of growing curvature.

In this work, we address the unresolved type III cases of the algebraic reconstruction theorem by integrating crossed product algebras and semiclassical approximations. We first derive that the relative entropy in crossed product algebras factorizes into contributions from the original algebra and observer wavefunctions. By constructing ``holographic'' crossed product algebras for ``bulk'' and ``boundary'' type III factors, we extend the algebraic reconstruction theorem to include the algebraic Ryu-Takayanagi (RT) formula semiclassically, which provides a complete algebraic description of the reconstruction theorem, as an intrinsic framework for the algebraic version of bulk-boundary correspondences in holographic duality.

The Eisenhart-Duval lift (ED) geometrizes classical dynamics by embedding their trajectories into null geodesics of a higher-dimensional Lorentzian spacetime. However, such a construction requires a natural Hamiltonian, that is, quadratic in the canonical momenta. As a consequence, mini-superspace cosmological models governed by non-natural Hamiltonians cannot admit an ED lift. Effective models in Loop Quantum Cosmology provide a concrete example: polymer-modified Hamiltonians become non-polynomial in the momenta and therefore fall outside the metric framework of the ED lift. We thus establish a kinematical no-go theorem: non-quadratic cosmological dynamics cannot be geometrized via ED constructions. Quantum-corrected bounce models therefore illustrate a structural limitation of metric geometrization within the ED framework.

Periodically driven systems host topological phases without static analogs, such as the anomalous Floquet phase characterized by trivial bulk bands yet robust boundary modes. In this work, we investigate the scattering problem of a Floquet Chern insulator and reveal the non-Hermitian skin effect (NHSE) of reflected waves. Using a discrete-time scattering formalism, we demonstrate how the non-Hermitian winding number of the reflection matrix is linked to the bulk Floquet invariant via boundary resonances. This reflected-wave NHSE relies on which quasienergy gap the incident wave resides in, leading to a gap-dependent Goos-Hänchen (GH) shift. We further show that the momentum-integrated GH shift quantitatively yields the Floquet topological invariant of the corresponding gap. Our work highlights a frequency-dependent NHSE of reflected waves in driven systems and provides a real-space scattering approach to identify non-equilibrium topology.

Post-Newtonian theory is considered a reliable effective expansion of General Relativity in the weak-field and slow-motion limit. We argue that such a belief is misplaced. In generic many-body relativistic dynamics, the absence of globally conserved charges in the region of interest and non-integrability can drive strong sensitivity to angular-momentum exchange across inhomogeneous curvature, invalidating naive power counting in an effective theory expansion. Building on general lessons from effective field theory, we derive an explicit breakdown criterion that delineates when post-Newtonian truncations become unreliable despite small local potentials and velocities. This supplies a controlled systematic for weak-field mass inference, relevant to the dark matter puzzle in astrophysics and cosmology.

Generalized vector-tensor theories of gravity have drawn attention for admitting hairy black hole solutions, thereby circumventing the standard no-hair theorems. It remains an open question, however, how such black holes may form starting from reasonable initial conditions. It has been suggested that vector hair may grow spontaneously as a result of the field developing a negative effective mass squared $-$ the so-called spontaneous vectorization mechanism. We demonstrate that this is not possible if the initial state is a hairless black hole, a result that applies to essentially all stationary and axisymmetric solutions of interest in general relativity. More precisely, we prove that the appearance of a negative effective mass squared for the vector field must necessarily be accompanied by ghost- or gradient-type instabilities. Demanding the absence of such instabilities translates into interesting bounds on the coupling constants of the theory as functions of the black hole parameters. In particular, we discover that a Kerr black hole may become unstable when the spin increases above a certain critical value.

Recent cosmological data have been interpreted as indicating deviations from $Λ$CDM within the standard $w_0w_a$ parametrization, including hints of phantom crossing and dynamical dark energy. However, such inferences can be parametrization-dependent and need not imply a statistically robust detection. We test these claims by comparing $Λ$CDM, $w_0w_a$, and thawing quintessence models, using the Deviance Information Criterion (DIC) and the Bayesian evidence $\ln \mathcal{Z}$. We find that $w_0w_a$ can provide a slightly improved local fit, but this improvement is confined to a limited region of parameter space. The global Bayesian evidence does not support it once the full prior volume is taken into account. In particular, cases with $Δ{\rm DIC}<0$ but $Δ\ln \mathcal{Z}<0$ indicate that these improvements are not statistically significant. We show that all models are statistically indistinguishable, and that there is no statistically consistent evidence across different datasets for either dynamical dark energy or phantom crossing.

We revisit the Schwarzschild singularity in a semiclassical setting where the background geometry is classical and quantum effects enter through Bohmian (quantal) trajectories associated with a Klein Gordon wave packet. Using the Madelung-Bohm decomposition of the Klein Gordon wavefunction, we show that the quantum-modified motion is equivalent to geodesic motion in an effective metric conformally related to Schwarzschild, with a conformal factor fixed by the wavefunction amplitude. Solving the wavefunction equation near $r\to 0$ determines this factor and yields finite curvature invariants, in suitable coordinates the interior extends smoothly and the effective spacetime is geodesically complete. This suggests that quantum dynamics on a fixed classical background can regularize the Schwarzschild singularity without a full theory of quantum gravity.

Violations of the Leggett-Garg inequality (LGI) up to its algebraic bound under non-Hermitian dynamics are well established theoretically. Here, we demonstrate that such extreme violations are intrinsically fragile when realistic measurement processes are taken into account. We consider an open two-level system described by a time-local hybrid Liouvillian, with a continuous parameter $q \in [0,1]$, representing detector efficiency, i.e., the fraction of quantum jump trajectories that are retained in the ensemble. This parameter interpolates between trace-preserving Lindblad dynamics ($q=1$) and non-Hermitian ``no-jump" evolution ($q=0$). While $K_3$ approaches its algebraic maximum of 3 in the null-efficiency limit, even an infinitesimal increase in detector efficiency induces a rapid, highly nonlinear suppression toward the classical bound. This logarithmic sensitivity reveals that maximal LGI violations are not robust physical features but rather singular limits of idealized measurement conditions. Our results have direct experimental implications: achieving algebraic LGI violations in systems undergoing continuous time evolution requires near-perfect suppression of detected quantum jumps (i.e., effective post-selection), placing stringent constraints on detector performance. In contrast to discrete protocols based on time-non-divisible dynamics, our framework shows that extreme violations arising within continuous, divisible quantum trajectory evolution constitute a fundamentally fragile regime.

We argue that if de Sitter space is indeed represented by a finite dimensional quantum system, then semi-classical considerations, combined with the fundamental principles of quantum measurement theory, imply that any theoretical model of it is ambiguous. If our own universe asymptotes to such a de Sitter state, and if a model of it as a finite system can be embedded in a sequence of models that converges to a non-perturbative completion of a unique superstring model in asymptotically flat space, then one might be able to find a very precise mathematical model of our universe. However, even the most comprehensive experiments possible to local detectors in the universe cannot measure more than a tiny fraction of the total number of q-bits in the system.

We propose and experimentally demonstrate a method to strongly increase the sensitivity of spin measurements on nitrogen-vacancy (NV) centers in diamond, which can be readily implemented in existing quantum sensing experiments. While charge state transitions of this defect are generally considered a parasitic effect to be avoided, we show here that these can be used to significantly increase the NV center's spin contrast, a key quantity for high sensitivity magnetometry and high fidelity state readout. The protocol consists of a two-step procedure, in which the charge state of the defect is first purified by a strong laser pulse, followed by weak illumination to obtain high spin polarization. We observe a relative improvement of the readout contrast by 17 %, and infer a reduction of the initialization error of more than 50 %. The contrast enhancement is accompanied by a beneficial increase of the readout signal. For long sequence durations, typically encountered in high-resolution magnetometry, a measurement speedup by a factor of >1.5 is extracted, and we find that the technique is beneficial for sequences of any duration. Additionally, our findings give detailed insight into the charge and spin polarization dynamics of the NV center, and provide actionable insights for direct optical, spin-to-charge, and electrical readout of solid-state spin centres.

We investigate the observational signatures of an idealized double-ring and double-torus system orbiting a Schwarzschild black hole, allowing the two emitting components to have mutually inclined symmetry axes. Using general-relativistic ray tracing, we construct frequency-shift maps, bolometric flux maps on the observer's screen, and the corresponding spectral line profiles of the emitted radiation. The single equatorial torus is used as a reference configuration in order to isolate the effect of the second emitting component and of the mutual misalignment of the two structures. We show that the presence of two non-coplanar emitting structures produces characteristic multi-peak spectral profiles and asymmetric bolometric-flux distributions. These signatures are imprinted both in the line-profile morphology and in the $α$-profiles of the bolometric flux, providing simple diagnostic features of non-coplanar multi-component accretion structures.

The geodesic structure and thermal properties of Gaussian Black Holes (\textbf{GBH})s in modified and Einstein gravities are studied and compared. In the geodesic part, motion of a test particle (massive and massless) are discussed, specially properties of the circular motion are considered. In the thermodynamic part, the mass, entropy and temperature functions are considered and discussed. The local and global stability is also analyzed through the Heat Capacity (\textbf{HC}) and Gibbs Energy (\textbf{GE}). The results show the thermodynamic differences are more than geodesic ones in the two theories of gravity with the note that the modified gravity is more consistent with the physical world.

The self-duality of the transverse-field Ising model is an archetype for dualities that, alongside symmetry and topology, are used as an organizing principle throughout modern physics. This duality, however, is not exact. The original and dual models have different symmetries and numbers of ground states, and the duality is implemented by a non-invertible operator giving rise to a non-invertible symmetry at the quantum critical point. Here, we show that by adjusting the model to accommodate open rather than periodic boundary conditions, it allows for an exact duality implemented by a unique invertible operator. In the model with exact duality, the symmetry at the quantum critical point is also exact, and hence invertible. Moreover, we find that the exact duality necessitates the presence of an anomalous edge degree of freedom, thus realizing a duality rather than topology based bulk-boundary correspondence. Finally, the exactness of the duality implies that the spontaneous breakdown of a global symmetry in terms of the original model can equivalently be described as spontaneously breaking a local symmetry in the dual system. We show that this seeming contradiction of Elitzur's theorem can be explained by the original and dual models obtaining different sensitivities to spatially local perturbations in any physical implementation of the Hamiltonian. Although the dual partners are mathematically equivalent, their physical implementations therefore are not. In analogy to the spontaneous breakdown of symmetries, we term this emergent distinction due to arbitrarily small environmental influences spontaneous duality breaking.

Efficient generation and high-quality distribution of entanglement is becoming increasingly more relevant in the field of quantum technologies, with important applications such as multiparty computation as well as quantum key distribution (QKD) on the rise. Quantum communication protocols based on entanglement offer an inherent quantum based randomness for key generation and provide in general higher security compared to prepare and measure implementations. Moreover, the future quantum internet will also be based on the distribution of entanglement for securely connecting quantum computers in a network. In this work we show the feasibility of using sequential time-bin entangled states for quantum key distribution in metropolitan networks using off-the-shelf components. The time-bin encoding ensures high fidelity distribution robust against random polarisation fluctuations occuring in optical fibers. Modulated laser pulses in the GHz frequency range are used to generate time-bin entangled photon pairs. The entangled photons are then sent over an about 30km long (9.5dB loss) fiber link within the Vienna fiber network, showing high degree of distributed entanglement with a measured 93\% quantum visibility.

The quantum enhancement of success probability in the Random Access Code (RAC) protocols remains unexplored from two important perspectives. First, the use of entanglement between two co-measurable degrees of freedom of a single particle (intraparticle entanglement) in achieving such quantum enhancement has not been investigated. Second, no explicit quantitative correspondence has been established between the predicted/observed quantum advantage and the underlying quantum resource responsible for it. In this work, we address both these aspects simultaneously by harnessing a single-particle resource. For this purpose, the RAC protocol is formulated in terms of intraparticle entanglement between, for instance, spin/polarization and path degrees of freedom of a single particle. Within this framework, a relevant Bell-type inequality, derived from the assumption of noncontextuality for single particle path-spin measurements, is used. Based on these ingredients, the formulated analysis reveals that the magnitude of quantum-mechanical violation of such Bell-type inequality, signifying a form of quantum contextuality, is quantitatively commensurate with the quantum enhancement of success probability in any intraparticle entanglement-assisted $n$-bit RAC protocol. In particular, the maximal success probability of a quantum $n \mapsto 1$ RAC protocol corresponds to the maximal quantum violation of the relevant Bell-type inequality. This correspondence is empirically testable using a readily implementable single-particle interferometric setup requiring coherence preservation only for a single particle.

Evaluating quantum loop corrections to curvature perturbations in non-attractor inflation presents theoretical ambiguities. A crucial aspect of this challenge lies in the unconstrained finite contributions in renormalization counterterms and regularization scheme dependence. In this work, we derive exact Ward identities via the path integral formalism based on the large gauge symmetry of the background-perturbation split. These identities are shown to impose strict, model-independent constraints on the renormalization procedure. Provided the ultraviolet completion respects this symmetry, the Ward identities non-perturbatively govern the infrared evolution of the power spectrum. This symmetry-based framework offers a systematic resolution to recent theoretical discrepancies concerning one-loop corrections in ultra-slow-roll inflation.

Photon loss and dephasing rapidly degrade the sensitivity of quantum sensors, yet systematic methods for designing error-correcting codes whose geometry is simultaneously adapted to the sensing task and the noise channel do not exist. Here we establish that orbital-angular-momentum (OAM) encoding and Gottesman-Kitaev-Preskill (GKP) lattice geometry are structurally coupled: an OAM mode of topological charge $\ell$ induces a phase-space rotation $θ_\ell=\ellπ/\ell_{\max}$, corresponding to a family of twisted GKP stabilizer lattices. Using an end-to-end differentiable Strawberry Fields--TensorFlow circuit, we jointly optimise $\ell$, the lattice aspect ratio $r$, and the finite-energy envelope $ε$ to maximise quantum Fisher information subject to $P_{\rm err}\leq10^{-3}$. The optimum occurs at the fractional charge $\ell=1.5$ ($θ=67.5^\circ$), implementable with a half-integer spiral phase plate, which reduces $P_{\rm err}$ by $23.9\times$ relative to the square-lattice baseline while leaving $\mathcal{F}_Q$ unchanged to within $0.2\%$. This surpasses the best integer value ($\ell=2$, $15.7\times$) and arises from an exact $180^\circ$ periodicity of the $P_{\rm err}(θ)$ landscape, confirmed analytically and numerically. We derive a transcendental balance equation for the optimal angle $θ^*(η,γ,r)$ and prove that it decreases with both $γ$ and $η$. A Shannon-inspired metrological capacity $\mathcal{C}=\mathcal{F}_Q\cdot(-\ln P_{\rm err})$, maximised at $\ell=1.5$ with a $41\%$ gain over the square lattice, quantifies the joint sensitivity--fault-tolerance resource. These results establish a geometric design principle for noise-adaptive quantum sensors and a fully open-source differentiable template extensible to other bosonic code families.

The homogeneity of the microwave magnetic field is essential in controlling a large volume of ensemble spins, for example, in the case of sensitive magnetometry with nitrogen-vacancy (NV) centers in diamond. This is particularly important for pulsed measurement, where the fidelity of control pulses plays a crucial role in its sensitivity. So far, several magnetic field-forming systems have been proposed, but no detailed comparison has been made. Here, we numerically study the homogeneity of five different systems, including a planar antenna, a dielectric resonator, a cylindrical inductor, a barrel-shaped coil, and a nested barrel-shaped coil. The results of the simulation allowed us to optimize the design parameters of the barrel-shaped field-forming system, which led to significantly improved magnetic field uniformity. To measure this effect, we experimentally compared the homogeneity of a field-forming system having a barrel shape with that of a planar field-forming system by measuring Rabi oscillations of an ensemble of NV centers with them. Significant improvements in inhomogeneity were confirmed in the barrel-shaped coil.

We prove that any background-inert perturbative coupling $ λ$ in coincident $ f(Q) $ gravity exhibits a degeneracy with the clustering amplitude $ σ_{80} $, when using compressed CMB distance priors. This degeneracy is, in fact, a direct materialization of a more deeper $ A_s-D_0(λ) $ degeneracy between the primordial amplitude $ A_s $ and the present day growth factor $ D_0(λ) $. We outline a consistency check scheme, applicable to models even outside the $ f(Q) $ class, by computing $ A_s $ needed to reproduce the $ σ_{80} $ predicted by the sampler. We perform our analysis with two dataset pipelines, based on the coupled/decoupled $ fσ_8(z) $ data. To ensure theoretical diversity, we include $ Λ$CDM and the Hybrid model in the $ f(Q) $ framework. Our results illustrate that adding the $ λ_0\sqrt{QQ_0} $ correction to the models inflates $ σ_{80} $ to unphysical values, while showing moderate evidence in favor of the said models. However, this results in an increase of $ 20\%-30\% $ in $ A_s $ in $ 1.7σ-2.2σ$ tension with Planck values. We utilize the $ 1σ$ $ \ln(A_s) $ constraints from Planck as priors in order to fix the artificial increase in $ σ_{80} $ and find that all the constrained parameters return to their baseline values. Each model is penalized by around $ 2 $ units per extra parameter. Interestingly, the $ Λ$CDM$ +λ_0+\ln(A_s) $ + SDSS DR16 combination shows a weak preference over the vanilla $ Λ$CDM model, validated by the values of $ \log\mathcal{Z},\;AIC,\;DIC, $ and BIC.

The traversable wormhole protocol in coupled Sachdev-Ye-Kitaev (SYK) systems produces a transmission signal C(t) widely interpreted as evidence of holographic dynamics. Recent work has questioned this interpretation, showing that similar signals arise in generic thermalizing systems. We address what the signal actually probes by systematically destroying quantum chaos in the SYK model via random coupling deletion, while monitoring the transmission signal across the chaos-to-integrable transition. Using exact diagonalization of the doubled SYK model at N=10 with 50 disorder realizations per sparsity, supplemented by Krylov-subspace extensions to N=20, we find that the ensemble-averaged peak height varies by less than 1.1% across a 50-fold sparsification range, even as the underlying spectrum transitions from Gaussian-unitary-ensemble to sub-Poisson statistics. A 1,200-instance sweep over the inter-system coupling mu confirms that the signal is controlled by mu alone, with no dependence on internal chaos. We further verify that the thermofield double state retains its thermal structure under sparsification despite substantial changes to the state vector, providing a structural explanation for the invariance. These results indicate that the transmission signal diagnoses inter-system coupling fidelity rather than holographic dynamics, and that future quantum-simulation experiments require independent chaos diagnostics to substantiate gravitational claims. As a practical consequence, the invariance implies that 98% of the Hamiltonian's coupling terms can be discarded (with variance rescaling of the survivors), reducing the gate count per Trotter step by approximately 50x at N=10 and bringing larger traversable-wormhole simulations within experimental reach.

Bell's theorem states that no description of a Bell experiment can be simultaneously local, realistic in the sense of counterfactual definiteness, and free of conspiracy between settings and hidden state. The recent generation of experiments has confirmed the predicted violation of the CHSH inequality, so one of the assumptions must be abandoned. Which one, and how one reconstructs a coherent worldview after doing so, is a question on which many authors disagree. This paper is written by three such authors. All three reject both counterfactual definiteness and conspiratorial violation of statistical independence of setting choices and state. After a joint exposition of the classical half of Bell's theorem in the language of Pearl-style causal graphs, a joint summary of the loophole-free experiments, and a joint survey of the recent literature, each author states where they have presently arrived. Gill accepts irreducible and non-local quantum randomness and finds the choice between locality and realism a false dichotomy. In his later works, Bell derives counterfactual definiteness from classical local causality, and that is what has to go. The metaphysical concepts "realism", "locality", "causality" need to be reconsidered. Helland reconstructs the Hilbert-space formalism from a theory of accessible variables, and from this theory he concludes that every observer must be limited in a specific sense. Jongejan proposes a geometric hidden-variable construction in which the degree of violation of the CHSH inequality depends on the number of dimensions of space, Tsirelson's bound corresponding to three dimensions. The authors conclude with a discussion.

Hybrid quantum--classical pipelines increasingly support applications such as drug discovery, fraud detection, and cloud quantum processing unit (QPU) auditing, yet existing integrity-verification methods remain largely classical and fail to capture quantum-stage behaviour. We propose QCIVET, a contract-based integrity-verification framework that models a hybrid pipeline as a sequence of stages with explicit specifications and audits it at both syntactic and semantic levels. Syntactic integrity is enforced through a hash-chained audit trail with optional external anchoring, while semantic integrity at quantum stages is verified using a calibrated observable-deviation test grounded in the behavioural-subtyping discipline of Liskov and Wing. We prove soundness under the diamond-norm distance between quantum channels, conditional completeness for informationally complete observable families, and compositionality under inheritance chains. We further identify a class of Z-only-sneaky overrides that evade weak single-Pauli contracts but are exposed by multi-Pauli contracts. The framework is evaluated under calibration-derived noise models from IBM Quantum Eagle r3 and Heron r2 processors, and the subtype-separation protocol is validated end-to-end on a real ibm_fez (Heron r2) processor. QCIVET is instantiated on three representative applications: variational quantum eigensolver (VQE) for drug discovery, quantum-assisted fraud detection, and customer-side auditing of cloud QPU services. The reference implementation, including a real-time verification engine with sub-millisecond per-stage commit latency, is released as open source.

Feedback-based quantum optimization is a quantum approach to combinatorial optimization. In this paper, we introduce the classical counterpart of feedback-based quantum optimization by using the quantum-classical correspondence of spin systems to discuss the possibility of quantum advantage. It also enables us to develop higher-order theory of a previously proposed classical approach to feedback-based quantum optimization. First, we compare the feedback-based algorithm for quantum optimization (FALQON) and its variant with their classical counterparts. Then, we perform benchmark tests of various quantum and classical algorithms with small-scale instances, and of classical algorithms with large-scale instances. Main findings are that (i) quantum algorithms can be advantageous to classical algorithms in terms of the quality of solutions, while classical algorithms tend to show faster convergence than quantum ones, and (ii) one of the classical algorithms discussed in this paper shows significant scalability for higher-order unconstrained binary optimization problems. These findings highlight the importance of quantumness and the usefulness of classical approaches.

We consider the multi-qubit fixed-excitation state transfer along the spin chain with dipole-dipole interaction subjected to the interaction with environment governed by the Lindblad equation preserving the excitation number during spin-evolution. The state transfer algorithm includes the state restoring via Kraus operators and ancilla measurement. As a result, the transferred state appears in superposition with completely mixed state, the latter disappears with vanishing interaction with environment. In that case we deal with probabilistic perfect state transfer. Example of an arbitrary multi-qubit one-excitation state transfer is present and its robustness with respect to perturbation of the Kraus operators is studied.

We propose a novel gravitational signature to detect Primordial Black Hole (PBH) dark matter by treating interstellar hydrogen as a quantum sensor for spacetime curvature. Focusing on H II regions, we demonstrate that the Riemann tidal tensor of an \emph{asteroid-mass} PBH induces a symmetric splitting of the $2P_{3/2}$ state in bound hydrogen atoms. This relativistic effect redistributes $9.9\,\mathrm{GHz}$ absorption line into a gravitational spectral radio forest with a bandwidth $\sim 2\,\mathrm{GHz}$. By accounting for active accretion of Hydrogen atoms and the resulting density-squared emission measure within the Bondi radius, we find a relatively enhanced absorption spectrum. This feature presents a concrete, high-contrast target for upcoming radio-surveys to constrain PBH populations in the dark matter sector.

We investigate gravitational waveforms from compact binary systems in Einstein-scalar-Maxwell (ESM) theories, where a scalar field $φ$ couples to a $U(1)$ gauge field $A_μ$ through a field-dependent function $μ(φ)$. In this framework, compact objects -- black holes (BHs), neutron stars (NSs), and exotic compact objects (ECOs) -- can carry both vector and scalar charges, with the latter arising as secondary hair induced by the former. Modeling the binary as electrically charged point particles with scalar-field-dependent masses, we derive the conservative dynamics in the near zone and compute the radiative fields in the far zone. The tensor waveform is modified through the effective dynamics and radiation-reaction-driven phase evolution, while scalar and vector modes introduce additional energy-loss channels. From the energy fluxes of tensor, scalar, and vector radiation, we construct the frequency-domain waveform using the stationary phase approximation. Dipole radiation sourced by differences in scalar and vector charge-to-mass ratios yields a leading $-1$ post-Newtonian correction. The deviation from general relativity is characterized by a single parameter $b$, which controls both amplitude and phase modifications. We further examine constraints from the orbital-period decay of binary pulsars, showing that current observations already place stringent bounds on $b$ for neutron star binaries. In addition, we evaluate $b$ for representative BH-BH, NS-NS, ECO-ECO binaries realized in ESM theories. Our results provide a unified framework for gravitational-wave signatures of charged compact binaries and offer a means of testing dark-sectorscalar and vector charges with current and future observations.

Quantum information platforms enable analog quantum simulations, such as quantum annealing, offering a promising route to solving complex combinatorial optimization problems. Here, we propose a quantum information architecture based on networks of interacting parity-time (PT)-symmetric non-Hermitian qubits. While the dynamics of individual PT-symmetric qubits have been experimentally demonstrated across multiple platforms including NV centers, superconducting circuits, and trapped-ion systems yet coherent dynamics in interacting systems remain largely unexplored. To address this issue we theoretically investigate stationary and time-dependent Hamiltonians relevant to quantum annealing using a minimal model of two interacting XX-coupled PT-symmetric non-Hermitian qubits. We analyze both symmetry-preserving and symmetry-broken regimes and demonstrate that adding even tiny PT-symmetric non-Hermitian terms in the qubits Hamiltonian allows to greatly enhance the probability of reaching the ground state after annealing.

In this work, we derive an exact black hole solution in higher-order curvature gravity by coupling an electromagnetic sector formulated within the ModMax framework to a quintessence dark energy component. Focusing on purely electrically charged configurations, we analyze the thermodynamic and geothermodynamic properties of the solution to investigate its stability and phase structure. Within this sector, the ModMax theory effectively reduces Maxwell electrodynamics up to a rescaling of the electric charge, and thus the obtained solution corresponds to a consistent subset of the broader nonlinear theory. Using thermodynamic geometry, we examine microscopic interactions and phase transitions, showing that divergences in the thermodynamic curvature coincide with the vanishing of the heat capacity, confirming the consistency of the phase structure. We further explore the optical properties of the black hole by studying null geodesics and determining the photon sphere and the corresponding shadow radius for different values of the quintessence state parameter $ω$. Exact analytical expressions for the photon-sphere radius are derived, revealing that higher-order curvature corrections and quintessence significantly enhance the shadow size, whereas the electric charge has the opposite effect. Notably, quintessence is found to have a more pronounced impact on the shadow than the charge. These results highlight that dark energy and higher-order curvature corrections can yield potentially observable signatures in black hole shadows.

Quantum key distribution (QKD) promises information-theoretic security based on quantum mechanics and idealized device models. Practical implementations, however, deviate from these models due to unavoidable device imperfections, and existing security proofs fall short of capturing the complexity of real-world systems. Here we introduce a versatile numerical finite-key security framework valid against general coherent attacks and applicable to a broad class of practical QKD setups. It accommodates most relevant imperfections at both transmitter and receiver, including non-independent-and-identically-distributed (non-IID) signals arising in high-speed QKD systems due to the limited bandwidth of optical modulators, while requiring only partial characterization of the apparatuses. We demonstrate the power of our framework by proving the security of a realistic decoy-state QKD implementation with laser sources, providing a practical route towards rigorous security certification of real-world QKD setups.

Some collapse models proposed that gravitational effects cause the instability of mass distribution superpositions, leading to wave function collapse. In this paper, we utilize the quantum Boltzmann equation (QBE) to analyze the behavior of a fermion in a spatial superposition under graviton emission. We introduce a quantitative measure that links the stability of the superposition to the spatial separation, particle mass, and gravitational coupling. By examining the collision term in the QBE, we derive the decoherence rate and show how it depends on these parameters. Our results provide a detailed framework for understanding gravity induced decoherence, bridging the gap between quantum field theory and collapse models. We also discuss the implications of these findings for experimental tests of gravitationally induced wave function collapse and the broader class of collapse models known as dissipative continuous spontaneous localization (CSL) model.

We investigate five-dimensional rotating primordial black holes (PBHs) as dark matter candidates within the Dark Dimension (DD) scenario motivated by the Swampland Program. In this framework, a micron-scale extra dimension suppresses Hawking evaporation, allowing PBHs with initial masses \(M \gtrsim 10^{10}\,\mathrm{g}\) to survive to the present epoch. Moreover, the memory burden effect, a quantum-gravitational suppression of the evaporation rate by \(S^{-p}\), significantly prolongs PBH lifetimes and enlarges the allowed parameter space. We compute the evaporation dynamics for rotating 5D PBHs, derive the enhanced lifetime for \(p=2\), and establish the dark matter window \(10^{10}\,\mathrm{g} \lesssim M \lesssim 10^{21}\,\mathrm{g}\). The curvature perturbations responsible for PBH formation also generate a stochastic gravitational wave background through second-order scalar-induced effects. Assuming a log-normal primordial power spectrum with \(σ=1\) and \(f_{\mathrm{PBH}}=1\), we calculate the present-day energy density \(Ω_{\mathrm{GW}}h^2\) across the Dark Dimension window. The predicted signals peak at frequencies from nHz to Hz, within the sensitivity ranges of LISA and DECIGO/BBO, while remaining consistent with current CMB spectral distortion bounds. Fisher forecasts show that future observatories can constrain the PBH mass, dark matter fraction, spectral width, and memory burden exponent with percent-level precision. A detection of the predicted gravitational wave background would provide simultaneous evidence for a micron-sized extra dimension, PBH dark matter, and the memory burden effect, offering a decisive test of quantum gravity and extra-dimensional physics.

The origin of the large-scale poloidal magnetic field required to power relativistic jets in collapsars remains uncertain. While such a field may be inherited during PNS collapse, the efficiency of this process is unclear, motivating an in situ mechanism to generate poloidal fields out of the predominantly toroidal fields produced by stellar differential rotation. We present the first 3D general-relativistic magnetohydrodynamic collapsar simulations initialized with toroidal magnetic field profiles that closely follows those of pre-collapse stellar models. As the toroidal field in the disk becomes dynamically important, it seeds the dynamo, producing coherent poloidal magnetic loops that appear at $\sim \mathcal{O}(100)$ gravitational radii and are then advected inward along paths that may deviate from the disk midplane. The resulting poloidal fields thread the black hole (BH) and launch highly variable, wobbling relativistic jets on timescales of order seconds, with the onset depending on the initial magnetic field and the plasma circularization radius. Although the jets are highly variable and misaligned with the BH spin axis, they sustain $\gtrsim 10^{50}$ erg s$^{-1}$, comparable to that inferred for long gamma-ray bursts (LGRB). We identify magnetic-flux inversions driven by the stochastic dynamo, leading to the formation of striped jets that could be imprinted in LGRB light curves. These results demonstrate that the accretion0disk dynamo provides a robust pathway for jet production in collapsars across a broad range of progenitors.

Quantum batteries, which use quantum systems to store and deliver energy, are promising for next-generation energy storage. However, optimizing charging strategies and understanding the interplay between dissipation and quantum coherence remain open challenges. Here, we investigate steady-state charging in an open quantum battery and demonstrate that the charging timescale depends on the spectral gap of the Liouvillian operator governing dissipative dynamics. As a minimal example, we examine a three-level quantum battery realized in a single trapped ${}^{40}\mathrm{Ca}^{+}$ ion, where energy from an engineered thermal photon reservoir is coherently transferred to a long-lived metastable storage state. We find that long-term dynamics are confined to a low-dimensional manifold of slow Liouvillian modes, with their spectral structure determining the relaxation rate to the charged steady state. By adjusting experimentally accessible parameters, such as reservoir occupation and coherent coupling strength, the non-Hermitian Liouvillian spectrum can approach an exceptional point. This increases the spectral gap and accelerates the approach to steady state. As a result, this mechanism significantly enhances asymptotic charging power without relying on many-body collectivity or steady coherence. Our findings offer fundamental insights into open quantum thermodynamics and provide a path to efficient energy storage and fast-charging solutions in emerging quantum technologies.

We investigate the quantum computing of the vibrational dynamics of CO$_2$ and H$_2$O by constructing the vibrational Hamiltonian in qubit and qudit form by two types of qubit encodings (binary and direct) and a qudit encoding. We simulate the time-dependent vibrational population transfer using the three different encodings, including the effect of noise and find that the qudit encoding leads to the most accurate results both for CO$_2$ and H$_2$O because of the small number of terms in the qudit Hamiltonian as long as the same values of the entangling gate error rates are adopted.

We perform an exhaustive semidefinite-programming search over all 11{,}117 connected non-isomorphic simple graphs on eight vertices to maximize the quantum contextuality gap $Δ(G)=\vartheta(G)-α(G)$, where $\vartheta(G)$ is the Lovász theta function and $α(G)$ is the independence number of the exclusion graph $G$ within the Cabello--Severini--Winter framework for projective measurements. A previously uncharacterized graph on $n=8$ vertices and $m=10$ edges, which we name the Quad-$C_5$ graph (graph6 code: \texttt{GCQb`o}), achieves $Δ=0.46784$, surpassing the Wagner graph $W$ ($Δ\approx0.414$, $m=12$) with two fewer edges. We determine numerically, via the PSLQ integer-relation algorithm at 50-digit precision, that Quad-$C_5$ is a \emph{qutrit} contextuality witness with $η_3=1+\sqrt{5}$ (minimal polynomial $x^2-2x-4=0$), while numerical evidence indicates the Wagner graph requires a four-dimensional (two-qubit) Hilbert space. The graph contains four mutually overlapping induced five-cycles, and its adjacency spectrum is dominated by golden-ratio eigenvalues, tracing the contextuality advantage algebraically to the KCBS pentagon. Under depolarizing noise, Quad-$C_5$ at $d=3$ shares the critical visibility $v^*=1/(3\sqrt{5}-5)\approx0.585$ of the KCBS witness -- an analytically provable coincidence arising from a uniform shift of the graph parameters -- while at $d=4$ it strictly surpasses the Wagner graph in noise robustness.

We introduce a new family of CSS codes obtained from rate-1 precoded polar codes, which harnesses the precoding benefits obtained for classical short blocklength polar codes. We optimize the rate profile and precoder of these codes with a genetic algorithm, and present codes of dimension $ [\![256, 2 ]\!] $ and $ [\![512, 2]\!] $ that have logical error rates similar to the $ [\![1201, 1, 25 ]\!] $ surface code over the depolarizing channel.

Closed-form expressions for all matrix elements required for variational calculation of the electronic structure of periodic solids have been derived using a basis of explicitly correlated Gaussians (ECGs). Periodic basis functions are constructed by summing shifted correlated Gaussians over all composite lattice translations, where a generalized unfolding theorem reduces the resulting double lattice sum to a single sum through a unified computational framework for overlap, kinetic energy, and Coulomb potential operators. The formalism has been validated through application to an infinite one-dimensional hydrogen chain, where the ground-state energy per atom computed in the thermodynamic limit is shown to agree with finite-chain results extrapolated by other many-body methods.

Nonreciprocal quantum batteries offer superior charging performance compared to reciprocal quantum batteries. We consider a charger-battery system comprising two optical cavities that interact independently with a third auxiliary cavity. We show that the nonzero dissipation of the auxiliary cavity induces a nonreciprocal exchange of excitations among the charger-battery system. Therefore, by engineering the loss in the auxiliary cavity, we induce a directional energy flow that enhances the charging efficiency. Using numerical and analytical calculations, we show that the steady-state energy stored in the battery significantly exceeds that in the charger. We compare our results with those of the reciprocal cases and demonstrate that our nonreciprocal quantum battery model exhibits a significant charging advantage. We believe that our proposed scheme represents a step forward in cavity-loss engineering, making it a viable approach for nonreciprocal quantum batteries with existing experimental techniques.

Quantum computation is frequently mischaracterized as the simultaneous execution of exponentially many classical computations. This article offers a conceptual clarification of why this "branchwise parallelism" picture is misleading, demonstrating that the components of a quantum superposition cannot be treated as independently readable classical branches. Quantum speedups arise instead from reversible embeddings of algebraic structure made accessible through engineered interference patterns. We review this mechanism through several constraints: unitary garbage erasure is impossible, copying and deletion are context-dependent, and contextuality obstructs a single global classical history. We also distinguish circuit or unitary universality from Turing universality: dense generation of unitaries is not the same as symbolic computation over unbounded inputs with recursion, uniformity, and self-reference. In closed unitary dynamics there is no nontrivial absorbing halting state of the classical many-to-one kind; operational termination requires clocks, flags, measurements, open-system records, or external control. Exponential Hilbert-space dimension supplies a geometry for interference and high-dimensional embedding, not unlimited classical readout.

The influence-matrix formalism provides an alternative route to the classical simulation of quantum dynamics. Because influence matrices retain information only about the effective bath seen by local observables, they are expected to be easier to simulate than the full wavefunction. Recent work, however, has shown that they carry strong temporal correlations even in maximally chaotic systems, making them difficult to represent efficiently. Here we show that the reduced transition matrix, a suitable combination of influence matrices that directly determines local expectation values, can nevertheless be efficiently approximated. We first show that the truncation error is controlled by its singular-value spectrum, which naturally motivates a low-rank approximation. We then prove that, for chaotic dual-unitary circuits, the associated entropy grows at most logarithmically in time. Our conclusions follow from exact results for random dual-unitary circuits and are further supported by numerical results for fixed instances of both dual-unitary and random circuits.

The spatiotemporal content of a black-hole movie is set jointly by source variability and by the distribution of light-travel times across the image. In the slow-light prescription, an image evaluated at fixed observer time contains photons emitted at different source times, whereas in fast light all rays sample a single source emission time. In this work we compare these light-propagation prescriptions through the lensing-band structure of Kerr geodesic delays in a controlled semi-analytic setting. For a given emitting geometry, black-hole spin, and observer inclination, we show how the coordinate-time delay distributions of Kerr null geodesics, decomposed by image order across lensing bands, can be compared with the source correlation time to quantify differences between light-propagation prescriptions. We find that when the intrinsic variability timescale is comparable to, or shorter than, the relevant delay spread, the high-inclination mismatch between fast- and slow-light curves can reach several tens of percent. Motivated by this geometric structure, we introduce brisk light, an intermediate prescription that compresses each lensing-band delay map to its dominant temporal interval rather than collapsing the full image to a single source time. The proposed methodology provides both a practical criterion for when slow light matters and an efficient route to black-hole movies that retain the leading temporal imprint of strong lensing, a regime of direct relevance for future space-based VLBI targeting photon-ring observables.

Multivariate quantum signal processing (M-QSP) has recently been shown to be applicable for non-Hermitian Hamiltonian simulation, opening several problems regarding the optimization landscape, angle-finding, and constant-factor analysis. We resolve several of these problems here. We find the anti-Hermitian query complexity $d_I = Θ(\betaI T + \log(1/\varepsilon)/\log\log(1/\varepsilon))$ to be tight, established via Chebyshev coefficient bounds, modified Bessel function asymptotics, and Lambert~$W$ inversion. Fast-forwarding to $d_I = \mathcal{O}(\sqrt{\betaI T})$ is impossible in the bivariate polynomial model, though a linear state-dependent improvement to $d_I = \mathcal{O} β_{\mathrm{eff}} T + \log(1/\varepsilon)/\log\log(1/\varepsilon))$ is achievable. The optimization landscape of M-QSP admits spurious local minima, but a warm-start basin guarantee ensures the two-stage algorithm converges. CRC-exploiting block peeling reduces angle-finding from $\mathcal{O}(d^3)$ to $\mathcal{O}(d^2)$ classical operations, and optimized error allocation yields a leading constant of approximately~$2$ relative to the information-theoretic lower bound. A constant-ratio condition extends to non-identical signal operators, enabling time-dependent non-Hermitian simulation with query complexity $\mathcal{O}(\int_0^T(\alphaR(s) + \betaI(s))\,ds + \log(1/\varepsilon)/\log\log(1/\varepsilon))$. Block-encoding overhead $e^{-2\betaI T}$ holds across all function classes within the walk-operator oracle model, and dilational methods (Schrödingerization) achieve the walk-operator barrier. A precisely characterized direct-access construction achieves the intrinsic barrier $e^{-2ωT}$ (with $ω< \betaI$ for non-commuting Hamiltonians) on a restricted domain, though extension to the full bitorus remains open.

General relativity has achieved remarkable experimental and observational success. Critically, recent data from the LIGO-Virgo-KAGRA, Event Horizon Telescope, and GRAVITY collaborations are often credited with \textit{demonstrating} the existence of black holes, but in fact they only provide evidence for objects that should be regarded as black hole candidates. While current data are in striking agreement with the predictions for Kerr black holes, they can only rule out specific alternative models of compact objects rather than provide conclusive proof of black holes. More fundamentally, and independent of whether or not black holes exist, general relativity itself imposes limits on what can be observationally established. Essentially, no observational data is sufficient to confirm the existence of black holes.

We investigate the dissipative dynamics of linear and nonlinear waves in harmonic traps by means of engineered complex non-Hermitian potentials. By combining an analytical mapping between real and complex Schrödinger equations with direct numerical simulations, we show that while in the linear case the damped motion leads to the formation of a stationary state at the trap center, in the nonlinear case a static potential design alone is insufficient to ensure long-term stability. Instead, the system relaxes toward a long-lived metastable configuration that eventually undergoes decay or collapse. To overcome this limitation, we introduce a time-dependent modulation of the nonlinearity that effectively converts these metastable states into robust non-equilibrium stationary states. This approach establishes a general strategy for controlling nonlinear waves in non-Hermitian systems, with potential applications in photonics and Bose--Einstein condensates.

In this work, we investigate the thermodynamic geometry of Reissner-Nordstrom Anti-de Sitter (RN-AdS) black holes with quintessence in the grand canonical ensemble. The analysis employs the Ruppeiner curvature scalar to elucidate the microscopic interactions and critical phenomena in the extended phase space. Divergence of the scalar curvature signal phase transitions, while its sign characterizes the nature of the underlying interactions; negative for attractive and positive for repulsive type interactions. The analysis reveals that attractive interactions dominate at low electric potentials, whereas repulsive interactions prevail at higher potentials unlike the usual charged black holes. Finally, the interaction strength is fairly constant during the phase transition, providing a greater understanding of the quintessence influenced microscopic attributes of RN-AdS black holes.

We study the computational complexity of quantum state isomorphism problems under group actions: given two quantum circuits that prepare pure or mixed states, decide whether the two states are related by a group action. This can be seen as a quantum state version of the Hidden Shift Problem, in much the same way that the State Hidden Subgroup Problem is a quantum version of the ordinary Hidden Subgroup Problem. We prove several results for this computational problem: - For the pure-state version, we show that the problem is BQP-hard for all nontrivial groups, and contained in QCMA $\cap$ QCSZK. We further obtain refined results for specific groups of interest: for abelian groups we show that the problem reduces to the state hidden subgroup problem over the generalized dihedral group; for the Clifford group, the problem is at least as hard as Graph Isomorphism under polynomial-time reductions; for the Pauli group it is BQP-complete. - For the mixed-state version, for nontrivial, finite and efficiently representable groups, the problem is QSZK-complete. - We also study a variant of this problem over an infinite group, in particular, the bosonic linear optical unitaries. We show that in the setting where the classical description of the quantum state is given in a suitable wave function representation known as the stellar representation, the problem is at least as hard as Graph Isomorphism, and is contained in NP $\cap$ SZK. Prior to our work, state isomorphism problems had only been studied for the symmetric group [LG17]. As a consequence of our results, we resolve an open question posed in [HEC25] about the existence of a quantum algorithm for the abelian state hidden subgroup problem on mixed states. We show that this problem is QSZK-hard in the worst case, thereby ruling out an efficient quantum algorithm unless QSZK = BQP.

In the context of quantum computing, efficient resource management is crucial for optimizing throughput on cloud-based platforms and maximizing hardware utilization. In the present work, we propose an approach to tackle quantum chemistry problems via quantum multi-programming of the Local Unitary Cluster Jastrow (LUCJ) ansätze. The ground-state energy of the molecular system is obtained via Sample-based quantum diagonalization (SQD), further refined by its extended version (ext-SQD). Building upon the Qiskit Experiments package, which already supports parallel execution functionality for general tasks, we developed a novel parallel experiment class tailored for quantum chemistry problems. Cross-talk is a known issue in the multi-programming frameworks and can corrupt the ground-energy estimation of the simulated systems. To assess its impact within our approach, we simulated two conformations of the ethanol molecule: one at the equilibrium state (EtOH$_{Eq}$), and one with the O-H bond stretched to 1.2 ${Å}$ (EtOH$_{1.2}$). We defined three different layouts that we executed in a randomized fashion, alternating serial and parallel execution within 10 independent replicates. The single modality of each circuit was kept as a baseline to evaluate the effect of cross-talk induced by quantum multi-programming. The energies obtained at the first-, last- and ext-SQD iteration were compared to the classical Heat-bath Configuration Interaction (HCI) reference. Our findings highlight the viability of a quantum multi-programming workflow for quantum chemistry as the robust post-processing protocol effectively mitigates possible cross-talk induced noise. At the final step of the configuration recovery process, the energy difference relative to the HCI reference is negligible, within 0.001 kcal/mol.

Local interactions among electrons underlie many complex properties of correlated materials. While the Jordan-Wigner transformation can preserve this locality along one spatial dimension, interactions along the remaining dimensions typically incur substantial overhead. We show how to simulate all geometrically local interactions on an $N$-site two-dimensional fermion lattice with no asymptotic overhead in the number of interactions and no space overhead. The primary overhead of our method is circuit depth, which on a qubit lattice matches that of fermionic swap networks, scaling as $\mathcal{O}(\sqrt{N})$, but reduces to $\mathcal{O}(\log N)$ on reconfigurable qubit arrays and to $\mathcal{O}(1)$ in lattice-surgery-based surface-code architectures. This is enabled by dynamically reorienting the Jordan-Wigner transformation to switch the lattice dimension along which locality is preserved. Furthermore, we study fermion routing, as required for the simulation of non-local interactions. When using qubit lattices, we reach resource scaling that asymptotically matches that of qubit routing, whilst on fully connected qubit devices, a depth scaling arbitrarily close to $\mathcal{O}(\log N)$ is reached. This allows the fermionic fast Fourier transform to be implemented on qubit lattices with asymptotically optimal resource scaling under these locality constraints. Notably, all of our constructions naturally extend to $d$-dimensional lattices. Beyond scaling improvements, we show explicit examples of our method, including Fermi-Hubbard-model simulations of the square-, Lieb- and kagome lattice and the fermionic fast Fourier transform.

Strong gravitational lensing is a key probe to trace dark matter. It assumes that mass curves spacetime so that light from a background source is deflected on its way to the observer. If dark matter contributes the major part to a massive cosmic structure, reconstructing the latter from strong-lensing observables allows us to infer characteristics of dark matter. Standard reconstructions fit a pre-defined mass-density model to the data. In this essay, I show how these mass models over-estimate the dark-matter contents of light-deflecting masses. Eliminating these models from the reconstruction reveals that observations directly constrain local properties of light-deflecting masses. How much dark matter is really needed in strong-gravitational-lensing effects and how much do we make up by our model choices?

Measurement-based quantum computing uses measurement patterns on predefined quantum resource states to execute quantum logic. Quantum simulation offers an important use case on near-term devices. However, pattern optimization depends on the multivariable interplay between hardware and software constraints and is therefore use-dependent and highly non-trivial. Optimization of large-scale patterns under realistic assumptions remains a barrier. We announce the release of the quantum measurement pattern library QPatLib, a dataset that, in v1.0, presents patterns for use in measurement-based quantum simulation. We present the workflow for generating patterns that execute Pauli-string unitaries needed for many quantum algorithms. We provide benchmark patterns for measurement-based quantum unitary evolution. The measurement patterns are defined with different conventions for commuting Pauli-string subsets to allow scaling of pattern size and complexity. The purpose of the library is to (i) serve as a standardized testbed for pattern-optimization protocols for measurement-based quantum simulation routines, (ii) offer a suite of patterns for direct use on hardware, (iii) provide data to empirically justify pattern design principles, and (iv) provide a flexible resource for future storage and use of measurement-based patterns beyond quantum simulation.

Cosmic voids provide a low-density environment where the scalar fifth force predicted by $\fR$ modified gravity (MG) is least screened. We present a semi-analytical calculation of the monopole, dipole, and quadrupole of the void-galaxy cross-correlation function $ξ^{s}(s,μ)$ in redshift space for the Hu-Sawicki $\fR$ model ($n=1$), combining the scale-dependent growth factor from the scalaron degree of freedom with nonlinear spherical shell dynamics. The framework applies to any metric $\fR$ theory for which $\Geff(k,a)/G$ can be specified in the quasi-static limit. Our key results are: (1)~the monopole deviation from $\lcdm$ grows from $+2.8\%$ for large voids ($r_v = 30\;\Mpc$) to $+29.7\%$ for small voids ($r_v = 11.7\;\Mpc$) at $\fRz = 10^{-5}$ -- a distinctive size-dependent signature of the Compton-scale scalaron response associated with chameleon screening, with $λ_C \approx 8\;\Mpc$; (2)~nonlinear evolution amplifies the modified-gravity signal by $\mathcal{A}_0 \approx 4$, bringing it within reach of ongoing and upcoming wide-field spectroscopic surveys, such as DESI, Subaru PFS, Euclid, and the Roman Space Telescope; (3) the gravitational potential contains a finite-range Yukawa component, producing a radially dependent dipole signature that is complementary to the density and velocity multipoles; (4) the signal weakens with redshift as the scalaron Compton wavelength shrinks, but remains potentially detectable at Stage-IV spectroscopic void samples. We show that the void-scale transition in the modified-gravity response, the joint sensitivity to density, velocity, and fifth-force contributions, and the nonlinear amplification around void shells make redshift-space void-galaxy multipoles a powerful semi-analytical probe of f(R) gravity and related inhomogeneous dark energy scenarios.

Color centers in silicon are emerging as promising platforms for quantum technologies. Among them, the G center has attracted considerable interest owing to its bright telecom O-band single-photon emission and its optically addressable metastable electron-spin triplet state. Here we investigate the spin properties of ensembles of G centers under above-band-gap excitation. We elucidate the spin photo-dynamics giving rise to the optical detected magnetic resonance (ODMR) response of G centers. The optimal pulsed sequence for measuring the ODMR spectrum of the G defects is identified, along with the temperature and optical-power regimes maximizing the spin readout contrast. Through magneto-optical measurements, we detect a level-anticrossing of the G center electron spin states. At last, we demonstrate coherent spin control of the defects, and characterize their spin-coherence properties. Unveiling the spin degree of freedom of the G center opens new avenues for the realization of quantum memories and quantum registers based on silicon color centers.

It was recently proven that, in contrast to their matrix analogues, the moments of a real Gaussian tensor of size N do not in general factorize over their connected components in the asymptotic large N limit. While the original proof of this rather surprising result was not constructive, explicit examples of non-factorizing moments, which are expectation values of trace-invariants, have since then been discovered. We explore further aspects of this problem, with a focus on Haar-distributed (or Gaussian) complex random tensors, which are more directly relevant to quantum information. We start out by exhibiting an explicit example of non-factorizing trace-invariant, thereby filling a gap in the recent literature. We then turn to the opposite question: that of finding interesting families of trace-invariants that do in fact factorize at large N. We establish three main theorems in this regard. The first one provides a sufficient combinatorial bound ensuring large N factorization, that is also simple enough to be applicable to various cases of practical relevance. Our second main result shows that the expectation value of any compatible trace-invariant is dominated by certain tree-like combinatorial structures at large N, which we refer to as tree-like dominant pairings. Our third main theorem establishes that any trace-invariant admitting tree-like dominant pairings does actually factorize at large N. In this way, we are able to prove that various families of trace-invariants that have been previously studied in the literature do factorize at large N. We apply our findings to the theory of multipartite quantum entanglement: to any trace-invariant is associated a multipartite generalization of Rényi entanglement entropy, whose typical expectation value in the uniform random quantum state can be explicitly computed assuming large N factorization.

We achieve query-optimal quantum simulations of non-Hermitian Hamiltonians $H_{\mathrm{eff}} = H_R + iH_I$, where $H_R$ is Hermitian and $H_I \succeq 0$, using a bivariate extension of quantum signal processing (QSP) with non-commuting signal operators. The algorithm encodes the interaction-picture Dyson series as a polynomial on the bitorus, implemented through a structured multivariable QSP (M-QSP) circuit. A constant-ratio condition guarantees scalar angle-finding for M-QSP circuits with arbitrary non-commuting signal operators. A degree-preserving sum-of-squares spectral factorization permits scalar complementary polynomials in two variables. Angles are deterministically calculated in a classical precomputation step, running in $\mathcal{O}(d_R \cdot d_I)$ classical operations. Operator norms $α_R\,,β_I$ contribute additively with query complexity $\mathcal{O}((α_R + β_I)T + \log(1/\varepsilon)/\log\log(1/\varepsilon))$ matching an information-theoretic lower bound in the separate-oracle model, where $H_R$ and $H_I$ are accessed through independent block encodings. The postselection success probability is $e^{-2β_I T}\|e^{-iH_{\mathrm{eff}}T}|ψ_0\rangle\|^2\cdot (1 - \mathcal{O}(\varepsilon))$, decomposing into a state-dependent factor $\|e^{-iH_{\mathrm{eff}}T}|ψ_0\rangle\|^2$ from the intrinsic barrier and an $e^{-2β_I T}$ overhead from polynomial block-encoding.

The Galactic Centre gamma-ray excess (GCE) - an anomalous ~ 2-5 GeV Fermi-LAT signal around SgrA$^{\star}$ - has remained without a consensus interpretation for more than fifteen years. Dark-matter annihilation and unresolved millisecond-pulsar populations remain the leading candidates, yet neither incorporates the past activity of SgrA$^{\star}$ recorded by the Fermi and eROSITA bubbles (FEB). We propose a unified scenario in which both the GCE and the FEB are fossil imprints of a single past episode of SgrA$^{\star}$ activity: a precessing parabolic Blandford-Znajek jet launched from a tilted, magnetically arrested disc during a ~7.5 Myr active phase ending ~ 2.6 Myr ago. The jet both inflated the kpc-scale FEB and injected hadronic cosmic rays contributing to the GCE flux. The model rests on three independently motivated inputs: the EHT-proposed ~ $35^{\circ}$ tilt of the SgrA$^{\star}$ spin axis from the Galactic rotation axis, Lense-Thirring precession of the disc through ~5 azimuthal cycles during the active phase, and a two-zone cosmic-ray transport prescription through the CMZ and bulge with standard inner-Galaxy diffusion coefficients. Internal consistency is verified by checking that the proton Larmor radius confines cosmic rays to the jet column and that the gamma-ray optical depth toward the Galactic Centre is negligible. Comparison with current GCE observations yields a spin-dependent hadronic contribution: for the EHT-favoured SgrA$^{\star}$ spin a$^{\star}$ = 0.9, we find an irreducible hadronic floor of ~ 3-14% of the observed GCE surface brightness across the inner ten degrees, highlighting a previously unexplored component relevant for comprehensive models of the GCE.

Curvature expansion for the heat kernel trace and the one-loop effective action is built for the wave operator of the theory in the quasi-thermal setup of a nonvacuum quantum state. This setup implies a non-static and non-stationary Euclidean gravitational background with periodic boundary conditions of the period $β=1/T$, where $T$ plays the role of effective global temperature to be locally rescaled by the metric gravitational potential. The results are obtained in the approximation quadratic in metric perturbations on top of flat Euclidean space and covariantized in terms of spacetime curvature. Covariantization includes a special vector field $ξ^μ(x)$ which generalizes the Killing vector of static geometries with time translation isometry to the case of a generic arbitrarily inhomogeneous metric subject to timelike periodicity condition. This vector field is obtained as a covariant metric functional to quadratic order in metric perturbations and gives rise to the local function $T/\sqrt{ξ^2(x)}$, $ξ^2(x)=g_{μν}(x)ξ^μ(x)ξ^ν(x)$, reducing to Tolman temperature $T/\sqrt{g_{00}(x)}$ on stationary manifolds with Killing symmetry. High ``temperature'' asymptotic behavior of the nonlocal formfactors -- operator coefficients of the curvature tensor structures in the heat kernel and effective action -- are obtained and possible cosmological applications of these results are discussed.

When multiple quantum emitters couple to a common electromagnetic environment, interference in their collective radiative dynamics gives rise to superradiance and subradiance. In regimes where coherent interactions and collective dissipation compete, the microscopic many-body dynamics and quantum correlations among the emitters that underlie superradiance and subradiance are theoretically challenging and remain experimentally elusive, even though collective emission has been observed in many physical systems. Here, we realize a superconducting qubit array coupled to a common microwave waveguide that mediates collective dissipation, with simultaneous access to coherent interactions and microscopic measurements of many-body dynamics. Engineered qubit-waveguide couplings with tunable amplitude and phase enable control of collective interference and the resulting super- and subradiant states. Leveraging site-resolved control and readout, we directly observe the microscopic decay dynamics of multi-qubit states across different excitation manifolds and track the evolution of populations and tunable quantum correlations. We reveal collective decay in regimes beyond the ideal Dicke model, where strong qubit-qubit interactions stabilize superradiance and subradiance against local dephasing and reshape decay pathways through spatially and spectrally structured many-body eigenstates. Our results establish a flexible platform for exploring collective phenomena in many-body quantum optics and driven-dissipative approaches to robust quantum information processing.

Engineered dissipation provides a powerful route to controlling and stabilizing quantum states in open systems. Superconducting circuits are particularly suited to this approach due to their tunable coupling to dissipative environments. Here we realize programmable local reservoirs for superconducting qubits through parametrically driven coupling to readout resonators, creating energy-selective incoherent pump and loss. Using coupled superconducting qubits, we autonomously stabilize entangled single-excitation states with fidelity up to 90.8%. We probe the stabilization dynamics under varying initial conditions and bath parameters, and implement robust classical shadow estimation for accurate and scalable state characterization. Finally, we numerically study a configuration where the engineered pump and loss share a common dissipative mode, leading to reservoir-mediated interference and classically correlated steady states. Our results demonstrate a scalable and hardware-efficient framework for dissipative preparation and control of correlated many-body states in superconducting circuits.

Modular quantum processors require a compiler to reason about two resources at the same time: local device connectivity and communication across QPUs. A mapping that is acceptable on a single coupling graph may be unsuitable for a modular machine if it creates excessive cross-QPU traffic, concentrates that traffic on a small number of interconnect links, or assigns many boundary qubits to a QPU with few communication ports. This paper presents QuPort, a Python and Qiskit-based compilation framework that studies this setting through an explicit three-level model: a weighted logical interaction graph, a directed physical coupling map, and an undirected QPU-level interconnect graph. The main partitioning method, TPCCAP, optimizes the implemented objective formed by weighted cut distance, communication-port overflow, and routed link-load congestion. The framework also includes heavy-edge clustering, balanced greedy partitioning, simulated-annealing refinement, communication-port-aware layout, extraction of remote two-qubit operations, local-only routing of per-QPU circuits, and topology-aware schedule estimation. The model is a compiler-level abstraction. It does not claim a calibrated hardware runtime or an implementation of a physical remote-gate protocol.

We present a non-parametric, model-independent reconstruction of the cosmological background and perturbation dynamics in non-minimally coupled theories of gravity. Within the Effective Field Theory of dark energy framework, we reconstruct the time-dependent cosmological constant, $Λ(t)$, and the non-minimal coupling function, $Ω(t)$, from cosmological data. To ensure stability, we apply a correlated smoothness prior that restricts the reconstruction to the space of sufficiently smooth functions. Using CMB, DESI BAO, Type Ia supernovae, CMB-ISW lensing cross-correlations, and large-scale 3x2pt DES Year 3 data, we find a $2.8σ$ hint for a non-minimal coupling. For the dark energy equation of state, our results indicate a preference for the existence of crossing of the phantom divide, $w_{DE}=-1$, at $z<0.8$. The non-minimal coupling effect stabilizes dark energy perturbations, providing a viable physical interpretation of the phantom crossing scenario. Our work paves the way for model-agnostic searches for signatures of modified gravity in cosmological data.

Shot noise sets a fundamental limit on the sensitivity of classical optical measurements, with coherent emitters achieving the lowest possible shot-noise level. Emission from sub-Poissonian light provides a pathway to surpass this limit, and single-photon sources provide a natural platform for generating such light. However, it is commonly assumed that continuously excited single-photon sources exhibit Poissonian statistics. In this work, a theoretical model of a continuously driven two-level single-photon source is developed, treating both excitation and radiative decay as stochastic processes. The analysis demonstrates that photon emission can display sub-Poissonian statistics when excitation and decay rates are comparable, showing that continuous excitation does not inherently preclude nonclassical emission. The model is further extended to include finite detection efficiency and detector dead time, illustrating how these practical non-idealities can affect the experimental observation of sub-Poissonian statistics.

We analyze the geometry of the field equations of Cotton gravity (for a quite general energy-momentum tensor) on a static space-time. In particular, we describe the local structure of the spatial Riemannian factor. This structure, that we call Cotton-$\varphi$-perfect fluid (C-$\varphi$-PF, for short) is a generalization to the regime of Cotton Gravity of the recently introduced notion of $\varphi$-static perfect fluid space-time ($\varphi$-SPFST). After discussing the variational origin of this system, we provide sufficient conditions for a C-$\varphi$-PF to reduce to a $\varphi$-SPFST. We also study the geometry of the level sets of the lapse function $f$ and we provide a rigidity result for C-$\varphi$-PFs under some curvature conditions. The role that Codazzi tensors hold in this theory is highlighted.

Quantum computation holds the promise of solving certain complex problems exponentially faster than classical computers. However, the high prevalent noise in current quantum devices impedes the accurate execution of even basic algorithms. This can be remedied by protecting quantum information with a quantum error-correcting code, where the logical information of an algorithmic qubit is spread across multiple physical qubits. Individual quantum errors are then located and corrected by the fault-tolerant measurement of multi-qubit stabilizer operators (parity checks). Unfortunately, error correction and fault tolerance both impose large demands on the qubit overhead: hundreds to thousands of physical qubits per logical qubit. We reduce the spacetime cost of fault tolerance by redesigning key building blocks of an error-corrected quantum computer. First, we develop a combinatorial proof with flag fault tolerance that exponentially reduces the extra qubits needed to measure a stabilizer of any size, while tolerating one fault. We leverage these proofs to then design state preparation circuits for the Steane and Golay codes with 100% yield. Next, we improve error correction on a planar layout by showing that a distance-four code encoding six logical qubits protects information as well as the distance-five surface code, using one-tenth as many physical qubits. Finally, we optimize the time overhead of logical gates in surface code quantum computers by protecting measurement results with a classical code, cutting computation time by a factor of two to six. Our hardware-agnostic optimizations of fault tolerance overheads thus suggest new routes to advance the timeline of error-free quantum computing.

We establish sharp lower bounds for the mass of asymptotically locally Euclidean (ALE) and asymptotically locally flat (ALF) toric 4-manifolds, in terms of equilibrium geometries consisting of gravitational instantons. More precisely, the mass of a complete ALE or ALF toric 4-manifold with nonnegative scalar curvature is bounded below by a sum comprised of the following quantities: the mass of the corresponding toric gravitational instanton having the same orbit space (rod) structure as the original ALE/ALF manifold, and an expression determined by the conical angle defects of totally geodesic 2-spheres within the instanton that serve as generators for its second homology. The inequality may be generalized to the situation in which the ALE/ALF manifold also possesses conical singularities as well as orbifold singularities, and it suggests a refined notion of `total mass' in which the result simply states that the total mass of the ALE/ALF manifold is not less than that of the corresponding gravitational instanton. Furthermore, we prove rigidity for these statements, namely the inequality is saturated only when the ALE/ALF manifold is Ricci flat and in fact agrees with the corresponding instanton. These results may be viewed in the context of positive mass theorems, providing an explanation of how positivity can fail in the ALE/ALF setting. Moreover, the main theorem may be interpreted as yielding a variational characterization of the relevant toric gravitational instantons.

While nonclassical light sources are fundamental to quantum communication and computing, solid-state platforms like color centers and quantum dots require cryogenic temperatures to reach the performance levels necessary for practical applications. Over the past decade, low-temperature engineering has transitioned from manual handling of liquid cryogens to automated closed-cycle cryostats. This review details the principles behind modern cooling hardware ranging from flow cryostats to mechanical cryocoolers and dilution refrigerators, with a specific focus on the requirements of optical quantum devices. Aimed at the practicing scientist, this overview provides the technical insights and historical context needed to navigate the current cryogenic landscape and evaluate its role in the future of quantum technology deployment.

The current network of gravitational wave detectors has already revealed hundreds of compact binary coalescences (CBCs), including binary neutron stars, binary black holes, and black hole-neutron star systems. As detector sensitivity improves, the superposition of these signals is expected to form an astrophysical background that becomes increasingly relevant for future observatories. In third generation detectors, such as the Einstein Telescope (ET), this background will be most prominent at low frequencies, potentially affecting the search for continuous gravitational waves (CWs) from spinning neutron stars. In this work, we evaluate the impact of the CBC background on CW detection using the Frequency-Hough pipeline, with a focus on the low-frequency performance in ET sensitivity conditions. Through realistic simulations of the unresolved CBC background, we find that it acts as an additional noise source, most strongly affecting the detection of CW signals around 7 Hz, worsening the FH sensitivity by about 7-10%.

The inflationary Lyth bound relates the primordial tensor amplitude to the inflaton field excursion. There is no analogous universal relationship in the case of ekpyrotic, bouncing, and cyclic models because scalar and tensor perturbations depend on entropy conversion, matching through the bounce and the specific mechanism that violates or evades the null energy condition. Nevertheless, the background kinematics fulfills a useful non-inflationary analogue: a field-space distance budget. In this study, we propose a phase-resolved distance criterion for a non-inflationary smoothing process and decompose the invariant scalar distance into ekpyrotic smoothing, entropy-to-curvature conversion, bounce, and post-bounce contributions. Then, we impose BKL anisotropy suppression as an additional constraint on the ekpyrotic phase. In the canonical phase of the ekpyrotic contraction, we recover the known small-field scaling and generalize it to total budget inequality. We impose three requirements: a BKL (Belinski-Khalatnikov-Lifshitz) anisotropy suppression that is parameterized separately, a phenomenological cutoff-corrected distance budget inspired by tower of states logic, and observational conversion windows from residual isocurvature and non-Gaussianity. Furthermore, we propose a new master condition that provides a lower bound on the value of the parameter $ε_{\rm ek}$ that depends on the remaining distance available after conversion and the cosmological bounce. We also derive a curvature constraint for scale-invariant entropy perturbations in curved field space which shows that the small total distance and the observed red tilt seem to indicate ultra-fast-roll ekpyrosis, sharp turns, short or strongly modified bounces, and/or significant negative sectional curvature of the scalar manifold. Finally, we demonstrate methods for testing the distance budget against observational data.

We extend the worldline quantum field theory formalism to include a direct diagrammatic method of computing the total flux of angular momentum from a black hole scattering event in the post-Minkowskian regime. Remarkably, except for subtle zero-frequency gravitons, the diagrammatic and integrational challenge is in a one-to-one correspondence with the analogous calculation of the black hole impulses -- and the well-developed WQFT methodologies for the impulse may thus be directly imported to this problem. Zero-frequency gravitons appear in this calculation as a "static" integration region in addition to the "dynamical" region usually encountered for the impulse. We show that a large class of static contributions can be organized systematically by introducing $n$-point functions referred to as "static correlators". They reduce to a simple one-loop integral family which we compute explicitly using integration-by-parts relations and the method of differential equations. In passing, our analysis shows that static contributions disappear in space-time dimensions $D>4$. As a concrete application of our new method, we compute explicitly the $\mathcal{O}(G^3)$ total flux of angular momentum reproducing known results. Further, we apply the same method to electromagnetism where we compute the analogous $\mathcal{O}(α^3)$ result.

We prove that the ground state of the AKLT models on the hexagonal lattice and the Lieb lattice satisfy the local topological quantum order (LTQO) condition. This will be a consequence of proving that the finite volume ground states are indistinguishable from a unique infinite volume ground state. Concretely, we identify a sequence of increasing and absorbing finite volumes for which any finite volume ground state expectation is well approximated by the infinite volume state with error decaying at a uniform exponential rate in the distance between the support of the observable and boundary of the finite volume. As a corollary to the LTQO property, we obtain that the spectral gap above the ground state in these models is stable under general small perturbations of sufficient decay. We prove these results by a detailed analysis of the polymer representation of the ground states state derived by Kennedy, Lieb and Tasaki (1988) with the necessary modifications required for proving the strong form of ground state indistinguishability needed for LTQO.

We study the dynamics of the Bianchi~IX (Mixmaster) universe under classical polymerization and generalized uncertainty principle (GUP) deformation of the Poisson brackets. Starting from the Misner Hamiltonian, we derive the effective equations of motion with both modifications and analyze the duration of Kasner epochs as a probe of dynamical behavior. Our results show that GUP corrections typically shorten the epochs, leading to more frequent wall collisions, whereas polymer corrections prolong them and suppress successive bounces. At leading order, the combined deformation produces an additive shift that interpolates between these two trends. While the billiard picture remains robust, the strength of Mixmaster chaos becomes sensitive to the deformation parameters. These results illustrate how Planck-scale corrections may either enhance or suppress cosmological chaos, offering a controlled framework for exploring early-universe dynamics.

We introduce a general gravity-related collapse mechanism based on linearized gravity. Starting from the weak-field limit of general relativity, gravitoelectromagnetism suggests an effective coupling between the gravitoelectric potential and the mass density distribution. At the same time, it provides a similar relation for the gravitomagnetic vector potential and the mass current. Following a hybrid (classical-quantum) dynamics approach, these couplings lead to a master equation whose non-unitary part is determined by the underlying mass distribution and currents. When the gravitoelectric potential coupling is considered, the well-known Diósi-Penrose collapse model acting on positional degrees of freedom is recovered. However, upon including the gravitomagnetic vector potential, additional collapse mechanisms emerge for rotational degrees of freedom as well as for mixed mass-rotation contributions.

We present an optimal control-based strategy to enhance the estimation of impulse-like disturbances in continuously monitored linear classical and quantum systems by exploiting non-equilibrium states. Using optimal estimation techniques for linear Gaussian systems to collect information from the temporal vicinity of the disturbance, we cast the minimization of disturbance estimation uncertainty as a nonlinear optimal control problem over time-dependent system parameters. The resulting method dynamically shapes the estimation covariances through parametric modulation, maximizing information gain at a known impulse time. This differs fundamentally from conventional squeezing protocols using periodic modulation that effectively degrade inference of impulse-like disturbances. Applied to nanomechanical resonators and levitated nanoparticles, optimal parametric driving reduces estimation variance by up to a factor of two relative to steady-state operation

Probabilistic error cancellation (PEC) is unbiased but suffers exponential sampling overhead set by noise-weighted circuit volume, whereas quantum error-detecting codes (QEDCs) remove many physical faults by stabilizer post-selection but leave an undetectable logical residue. We exploit this complementarity by using post-selection to map physical noise to a weaker accepted logical channel, and then applying PEC only to the residual channel. The resulting feedback-free QED+PEC scheme interleaves Clifford logical blocks, stabilizer measurements, post-selection, and probabilistic cancellation on accepted trajectories, without real-time decoding or active recovery. A key complication is that post-selection correlates accepted fault branches through stabilizer-commutation constraints, so the sparse Pauli-Lindblad factorization underlying bare PEC no longer applies directly. We therefore construct the inverse channel perturbatively: for fixed order $K$, only accepted fault branches up to order $K$ are retained, reducing preprocessing from $2^m$ branches to $O(m^K)$ per block. The order-$K$ protocol cancels the normalized post-selected channel through degree $K$, leaving a per-block error $O(W^{K+1})$ that accumulates at most linearly. For logical GHZ-state preparation with the $[[n,n-2,2]]$ Iceberg code under circuit-level depolarizing noise and ideal stabilizer measurements, first-order QED+PEC reaches $n=200$ physical qubits and lowers sampling overhead by three to four orders of magnitude relative to standard PEC while maintaining $F\simeq0.956$. Syndrome-noise tests show that readout-only flips mainly increase post-selection cost, whereas noisy GHZ-assisted global stabilizer extraction can remove the advantage. This identifies a discrete-Zeno trade-off: cheap detection reshapes the effective channel PEC must invert, rather than simply adding overhead.

Achieving uniform and scalable control of semiconductor spin qubits remains a key challenge for large scale quantum computing. In this work, we investigate how gate oxide thickness influences uniformity in dense two dimensional silicon quantum dot arrays. Using a 7 x 7 array fabricated in a 300 mm CMOS-process patterned by EUV lithography, we statistically characterize 392 quantum dots across four different oxide thicknesses. The threshold voltages, capacitances, lever arms, and charging energies are extracted using parallel row based measurements and we identify an optimal SiO2 thickness of 17 nm that minimizes threshold voltage variability below 63 mV standard deviation. Our observations illustrate how multiple sources of disorder can introduce competing oxide-thickness dependencies, resulting in non-monotonic trends. These results provide key design guidelines for dense, scalable silicon spin qubit architectures.

Quantum teleportation is a fundamental protocol in quantum information science, whose performance is conventionally evaluated under the assumption of ideal Bell-state measurements. In realistic implementations, however, joint measurements are often imperfect and can deviate from maximally entangled bases due to coherent errors in entangling operations. In this work, we analytically show how the entanglement of joint measurements determines teleportation performance and propose a strategy to overcome the limitations imposed by partially entangled joint measurements to recover the unit teleportation fidelity. We then derive an exact equation revealing a quantitative relation between measurement entanglement, channel entanglement, and the success probability to realize the unit-fidelity teleportation. We illustrate our results using elegant joint measurements and realistic coherent error models arising from imperfect entangling operations in quantum systems. Our work provides fundamental insight into the role of measurement entanglement in quantum teleportation and establishes a practical framework for achieving faithful teleportation without requiring substantial modifications to existing hardware.

We propose an experimental programme to test Leggett--Garg-type temporal correlations in single-neuron dynamics. The goal is to distinguish between diffusive (Wiener/cable-equation) models and non-diffusive persistent stochastic models based on Kac-type finite-velocity processes leading to the Telegrapher's equation. We show that while purely diffusive dynamics satisfies Leggett--Garg inequalities, persistent stochastic dynamics can produce oscillatory temporal correlations capable of violating these inequalities. The Leggett--Garg inequality may be viewed as a temporal analogue of Bell-type constraints. In the present context, however, violation is interpreted conservatively not as evidence of microscopic quantum coherence, but as evidence against a simple trajectory-based diffusive description. The resulting temporal correlations indicate persistence, memory, and contextual temporal structure mathematically analogous to that encountered in quantum systems. Using the analytic continuation connecting Kac processes to Dirac-like envelope equations, we argue that finite-velocity persistent stochastic transport provides a natural mechanism for such non-diffusive temporal correlations. These tests therefore offer a possible experimental probe of contextual and non-Markovian structure in neural dynamics without requiring claims of microscopic quantum coherence in the brain.

We study massless scalar, electromagnetic, and Dirac perturbations of asymptotically de Sitter black holes in generalized Proca theory. These geometries are especially interesting because the Proca sector generates both a primary-hair parameter and an effective cosmological term $Λ_{\rm eff}$, thereby reshaping the horizon structure and the size of the static patch. Working on this common hairy background, we derive the master equations for the three spin sectors and analyze their quasinormal spectra by means of Padé-improved WKB calculations supplemented by characteristic time-domain integration. We show that the scalar sector, especially the $\ell=0$ mode, is the most sensitive to metric deformations; increasing the Proca-hair parameter $Q$ weakens the damping as the charged three-horizon regime is approached; $β$ hardens the spectrum in the $(α,β)$ scan; and increasing $λ$ and $c_1$ produces the strongest overall softening. For the neutral scalar $\ell=1$ mode, the time-domain Prony extraction agrees excellently with the WKB results and resolves both the Schwarzschild-like black-hole branch and the de Sitter branch. We also discuss the implications of the exact empty-de Sitter limit for strong cosmic censorship and note that the resulting quasinormal frequencies provide useful input for grey-body factors.

In this paper, we consider some causality violating solutions in the curvature-squared gravity in order to examine whether closed timelike curves (CTCs) are allowed in these models. These aspects are studied in terms of the Gödel, Gödel-type and axially symmetric cosmological solutions. We observe that the Gödel and Gödel-type metrics are causal solutions of the model so that CTCs are now allowed and, surprisingly, every contribution involving the Weyl tensor is removed from the solutions. Hence, in order to study the effect (if any) of the Weyl tensor (an conformal symmetry) into CTCs a third metric is considered. In this case, we obtain contributions due to the Weyl tensor to the energy density and led to modifications of the weak energy condition.

Quantum Hamiltonian Descent (QHD) is a continuous optimization algorithm based on simulating a time-dependent quantum Hamiltonian whose potential energy encodes the objective function and whose kinetic energy promotes exploration through quantum interference and tunneling. While QHD is formulated for unconstrained optimization, many real-world optimization problems are constrained and highly nonconvex. In this paper, we benchmark AL-QHD, a hybrid framework that embeds QHD within the Augmented Lagrangian Method (ALM), thereby solving a sequence of unconstrained subproblems while using ALM to enforce constraints. We evaluate AL-QHD on standard nonconvex test functions and use iterative refinement to improve solution accuracy at fixed per-run qubit cost. We also perform a gate-based resource analysis on ACOPF-derived power system subproblems constructed from power-network data to estimate the quantum-computer scale required for practical applications. Resource estimates on Texas7k-derived ACOPF instances show steep hard-gate scaling, reaching $\sim 4.46 \times 10^7$ entangling gates in a NISQ-oriented model and $\sim 9.42 \times 10^8$ T gates in a fault-tolerant model at $\sim 5.3 \times 10^2$ active variables. These results suggest that AL-QHD is a useful framework for studying constrained nonconvex optimization with QHD, but that practical ACOPF-scale applications would likely require large-scale fault-tolerant quantum hardware.

We study the thermodynamic value of side-information channels induced by Bell-type correlations through a CHSH prediction task embedded into a Szilard-type feedback engine. A thermal two-level system supplies a uniformly random physical microstate $X$, and a trusted referee encoding together with a nonsignalling correlation resource induces a controller bit $G$ that acts as side information about $X$. We show that the maximal average feedback work satisfies $\langle W_{\max}\rangle \le k_B T \ln 2 , I(X:G)$, with equality achievable in the ideal quasistatic limit. For the CHSH embedding considered here, the induced channel $X \to G$ is binary symmetric with success probability $p_{\rm win}=1/2+S(P)/8$, where $S(P)$ is the CHSH value. The corresponding reversible feedback work is $k_B T \ln 2 ,[1-h_2(p_{\rm win})]$, yielding a strict ordering of the optimal classical, quantum, and nonsignalling cases. The result should be interpreted as a thermodynamic valuation of CHSH-induced side information available to the controller, not as evidence that Bell nonlocality itself is a source of free energy. The analysis assumes that the controller receives only the compressed bit $G$ and does not include the thermodynamic cost of implementing the referee, the correlation resource, or the auxiliary preprocessing. A full-cycle analysis including controller-memory reset gives non-positive net work, consistent with the second law.

Achieving quantum state transfer in passive ways can become a powerful asset for scalable quantum networks. Here, we demonstrate how giant atoms coupled to 1D waveguides provide a platform for such a passive, deterministic transfer. Engineering the position and strength of coupling points, we show that the nonlocal interaction can be utilized for the emission of time-reversal-symmetric single-photon wavepackets by spontaneous decay. We first derive general analytical conditions under which arbitrary qubit decays can be mapped to wavevector-dependent couplings that guarantee perfect state transfer in the continuum limit of infinitely many coupling points. Then, for experimentally relevant configurations with a finite number of coupling points, we demonstrate that high transfer fidelities can still be achieved by optimization, reaching 87% with only two coupling points and exceeding 99% with ten or more. We further analyze the robustness of the protocol against disorder in leg positioning and extend the formalism to environments with nonlinear dispersion, showing that dispersion-induced distortions can be fully compensated by judiciously chosen setups. Our results establish giant atoms as a powerful platform for realizing high-fidelity quantum state transfer in a setting without time-dependent control, opening new avenues for scalable quantum networks and engineered light-matter interfaces.

We investigate the cosmological implications of generalized mass-to-horizon entropy, a two-parameter extension of the standard Bekenstein entropy based on the mass-to-horizon relation. Assuming the entropy balance relation, we derive the change in the generalized mass-to-horizon entropy, which entirely accounts for the heat exchange across the horizon as measured by an observer near the apparent horizon. We have then derived the Friedmann equation, using the Clausius relation, and also using modified law of thermodynamics. The thermodynamic consistency of the entropy, is examined through entropy evolution and entropy maximization conditions, where the generalized entropy and its higher-order derivatives indicate that the universe evolves toward a stable maximum entropy configuration consistent with the generalized second law of thermodynamics. In addition, fluctuations in horizon energy are investigated to probe the thermal stability and thermodynamic behavior of the cosmic horizon. The fluctuation analysis reveals finite and physically stable behavior throughout cosmic evolution, supporting the thermodynamic viability of the proposed model. The present work therefore establishes the generalized mass-to-horizon entropy as a viable thermodynamic framework for describing modified cosmological dynamics and also the accelerated expansion of the universe as well.

Dynamical systems techniques are a powerful tool to analyse systems of ordinary differential equations, written in an appropriate form. For a given theory of gravity, the cosmological field equations typically lead to a system of ordinary differential equations. Casting these cosmological equations into the form of a dynamical system requires a careful choice of the dynamical variables. Despite this being a critical step, relatively little is said about this process in the literature. We discuss how different variable choices affect the information that can be extracted from the Friedmann equations. We begin by reviewing the standard cosmological model with dark matter, radiation, and dark energy, and include quintessence models. We revisit well-known models with an exponential potential using new variables. This discussion is then extended to models with scalar fields and more intricate coupling terms.

We show that the dissipation of small-scale perturbations through diffusion damping after neutrino decoupling lowers the present-day neutrino temperature compared to the expected value of $1.96\,{\text{K}}$. This reduces the relic neutrino abundance by an amount controlled by the integral of the primordial curvature power spectrum $Δ_{\cal R}^2(k)$. We find that a relic neutrino detection by PTOLEMY can set limits $Δ_{\cal R}^2(k) \lesssim {\cal O}(0.1)$ on scales $k \lesssim 3 \times 10^5\,{\text{Mpc}^{-1}}$, complementary to limits from Big Bang Nucleosynthesis, spectral distortions, pulsar timing arrays, and future dark ages 21-cm observations.

Dynamical capture in dense stellar environments is a promising channel for producing eccentric compact binary mergers. Although there have been no confident detections of eccentric mergers to date, a few candidates show indications of non-negligible in-band eccentricity upon re-analysis of the data. By assuming an observed eccentric event originates from a dynamical gravitational wave (GW) capture, we show that it is possible to identify the host environment using the eccentricity and mass posteriors. In particular, the eccentricity posterior can be mapped to posteriors on key capture parameters, such as the relative velocity at infinity and the impact parameter. By comparing these with the expected velocity distributions of different astrophysical environments, we can place constraints on the likely host. Assuming that it originated from a GW capture, we applied this framework to the neutron star-black hole merger GW200105. By comparing with the velocity dispersion distributions of neutron stars in the cores of globular clusters (GCs) and nuclear star clusters (NSCs), we find the probability that GW200105 merged in a GC (NSC) to be 29% (71%). As we anticipate detecting several eccentric mergers in the future, this method can provide a valuable astrophysical diagnostic of their host environments on a single-event basis; this can be straightforwardly generalized to a population of eccentric binaries. The formalism we develop is also applied to GW190521, but is less constraining for that event. Lastly, we infer a GW decay time from capture to merger of 11-156 days for GW200105.

We investigate a probe state preparation protocol based on two non-selective generalized quantum measurements to enhance parameter estimation in single-qubit systems. By fine-tuning the measurement strengths, we demonstrate the ability to design a broad class of probe states, initially prepared in a thermal state, which can be optimized for specific estimation tasks. We apply this framework to characterize the decay rate and the temperature of a generalized amplitude damping channel. Our results show that the preparation protocol significantly modulates the quantum Fisher information for both parameters. Furthermore, we derive a general analytical relationship between the quantum Fisher information, thermodynamic susceptibilities, and Hamiltonian variance, valid even in the transient regime. This connection highlights the role of energy fluctuations and kinetic response in determining metrological precision. Finally, we briefly discuss a quantum circuit for experimental implementation using nuclear magnetic resonance techniques.

Incompatible quantum channels cannot be jointly and exactly realized, meaning that any approximate joint realization inevitably entails a tradeoff in implementation accuracy. While this notion of channel incompatibility unifies fundamental limitations such as measurement uncertainty, the no information without disturbance principle, and the no-cloning and no-broadcasting theorems, connecting these traditional relations directly to the resource-theoretic strength of incompatibility has remained elusive. In this Letter, we show that generalized robustness, a typical resource quantifier of channel incompatibility, lower bounds the total error of any approximate joint realization. Applying this result to measurement channels provides a unified, model-independent framework encompassing error-error and information-error-disturbance tradeoffs. Furthermore, our robustness-based evaluation of disturbance outperforms an algebraic bound for all POVMs in dimensions up to six.

Predicting universal transport coefficients in far-from-equilibrium quantum systems remains a fundamental challenge. A paradigmatic example is the non-thermal fixed point (NTFP) of isolated Bose gases, where coherence spreads as $\ell^2(t) = C\hbar t/m$ with a universal constant $C$. While the scaling exponent $z=2$ is well established, the amplitude $C$ has remained elusive because the underlying particle cascade $n(k)\sim k^{-4}$ leads to a divergent kinetic energy, threatening the very existence of a constant speed limit. Here we resolve this paradox and present the first analytical, parameter-free prediction of a universal amplitude $C$. A deep interplay between symmetry and dissipation is uncovered. The emergent weak U(1) symmetry at the NTFP enforces a conserved total current, forcing the low-energy phase dynamics to obey a diffusive Langevin equation with noise entering as the divergence of a stochastic current. This structure, combined with dynamical decoherence of high-momentum modes, yields a universal power-law momentum distribution $\tilde{f}(v)\sim(1+v^2)^{-3}$ (with $v=k\ell$) that naturally regularizes the ultraviolet divergence. From this, a parameter-free geometric baseline $C=3$ is obtained, independent of microscopic details. The experimental value $C=3.4(3)$ [Martirosyan et al., Nature 647, 608 (2025)] is then shown to be quantitatively consistent with universal logarithmic corrections arising from a marginally irrelevant coupling at the fixed point. A new paradigm is thus established for predicting transport coefficients in strongly correlated non-equilibrium systems: symmetry constraints determine the low-energy effective theory, dynamical decoherence provides a natural ultraviolet completion, and scaling analysis delivers testable predictions moving beyond scaling exponents to quantitative amplitude prediction.

We construct an effective-field-theory bridge from late-time scalar-tensor cosmology to black-hole ringdown observables. Starting from a cosmology-conditioned EFT posterior, we lift Jordan-frame FLRW data through a finite covariant jet, transport the result to the arbitrary-background EFT for black-hole perturbations with a timelike scalar, and project it onto parity-resolved quasinormal-mode response kernels. The cosmological layer is a deterministic compressed likelihood built from BAO-like distances, growth summaries, low-redshift tensor-speed information, stability filters, and posterior samples for the ringdown pushforward. The detector layer uses Bayesian time-domain injections, one-, two-, and three-mode recovery models, analytic marginalization over linear sine/cosine amplitudes, remnant-calibration covariance products, and start-time variations. The transported posterior shows that FLRW tensor-speed deformations inherited from cosmology are driven far below ringdown detectability, whereas operators that vanish on homogeneous FLRW backgrounds can remain active in the anisotropic near zone of a black hole. For a literature-calibrated Hayward branch, we specify the prior measure, separate directly admissible points from a proxy continuation, and propagate both to detector-whitened consistency modes. The resulting framework turns cosmological viability into black-hole spectroscopy priors while keeping the strong-field completion explicit rather than assumed.

The steady incompressible Navier--Stokes equations pose significant computational challenges due to their nonlinear convective terms and pressure--velocity coupling. Physics-informed neural networks (PINNs) provide a mesh-free framework for approximating such systems, but classical PINNs can experience optimization difficulties in nonlinear flow regimes. In this work, we propose a quantum physics-informed neural network (QPINN) framework with a quantum neural network (QNN)-based trainable embedding for the lid-driven cavity problem. The proposed approach uses a QNN to learn data-adaptive quantum feature maps that encode spatial coordinates before they are processed by a variational quantum circuit within a physics-informed loss formulation. Numerical experiments show that the proposed QNN-TE-QPINN exhibits stable training behavior and competitive solution accuracy compared with classical PINNs and hybrid quantum models using classical embeddings, while requiring significantly fewer trainable parameters. Rather than claiming computational speedup, these results highlight the potential of trainable quantum embeddings for parameter-efficient physics-informed learning. The findings suggest that embedding design plays an important role in quantum-assisted PDE solvers and support further investigation of QNN-based trainable embeddings for nonlinear fluid dynamics benchmarks.

Barren plateaus in variational quantum circuits are commonly attributed to strong mixing dynamics that cause gradient variance to vanish exponentially with system size. Passive photonic circuits, central to linear optical quantum computing, challenge this picture: although their Hilbert space can be exponentially large, their dynamics are constrained to a Lie algebra whose dimension scales as the square of the number of modes. In photonic systems, postselection also plays a central role, with gradient concentration governed not by the Hilbert-space dimension but by how it reshapes the effective observable. Through exact statevector simulations, we compare allow-bunching evolution, collision-free filtering, and dual-rail postselection. In the allow-bunching and collision-free regimes, gradient variance remains consistent with polynomial rather than exponential decay over the tested system sizes. By contrast, dual-rail postselection induces exponential concentration beyond moderate system sizes, robustly across three initialization ensembles. These results indicate that photonic barren plateaus are governed by the interplay between passive linear-optical dynamics, postselection geometry, and task observables, offering practical guidance for designing near-term photonic variational architectures.

Uncertainty relations are usually stated as bounds on selected combinations of variances, but the full covariance matrix contains substantially richer information about the geometry of quantum state space and about the operational capabilities of quantum systems. Here we characterize the covariance matrices attainable by a finite-dimensional canonical pair of observables related by the discrete Fourier transform, the natural analogue of position and momentum in a finite Hilbert space. We combine analytic arguments with convex-geometric and semidefinite-programming methods based on joint numerical ranges to describe the admissible region through unitary invariants, in particular the trace and determinant of the covariance matrix. This provides a systematic way to identify extremal states, generalizing the notion of minimum-uncertainty states, and to quantify how the discrete uncertainty geometry approaches its continuous counterpart with increasing dimension. We further show that the resulting covariance-matrix characterization has direct consequences for applications: it yields accuracy bounds for multi parameter estimation protocols and separability criteria for finite-dimensional bipartite systems, including discrete analogues of continuous-variable EPR-type witnesses. Our results establish a systematic and versatile platform for connecting uncertainty relations, convex quantum geometry, metrology, and entanglement detection in finite-dimensional systems.

We develop an adiabatic quantum simulation framework on gate-based quantum computers to probe topological signatures of the one-dimensional fermionic Su--Schrieffer--Heeger--Hubbard (SSHH) model. We present explicit quantum-circuit constructions for initial-state preparation and time evolution, together with a practical measurement protocol and classical post-processing procedure for extracting the many-body Berry phase and the spatial profile of the sublattice polarization. Using classical simulations of the proposed circuits, we demonstrate -- for the first time within a genuine many-body framework -- that the topological characteristics of the SSH model remain robust against weak Hubbard interactions but eventually break down as the chiral-symmetry-breaking component of the interaction exceeds a threshold. The required qubit number, gate complexity, measurement shots, and classical pre- and post-processing costs all scale polynomially with system size. Our results provide a proof-of-concept framework for probing topological properties of interacting many-body systems via adiabatic quantum simulation on future large-scale quantum computers.

We develop a thermodynamic formulation of Cotton gravity in the Codazzi parametrization, providing a general framework in which the gravitational dynamics can be interpreted in terms of horizon thermodynamics. As paradigmatic examples, we apply the formalism to FriedmannRobertson-Walker (FRW) and static spherically symmetric spacetimes. By implementing the first law of thermodynamics on the apparent cosmological and event horizons, we derive a modified holographic entropy consisting of the standard Bekenstein-Hawking term supplemented by a correction induced by the Codazzi tensor. In the cosmological setting, this correction is governed by the temporal component of the Codazzi tensor, while in static configurations it is controlled by its anisotropic sector. Remarkably, the sign of this contribution provides a potential diagnostic of the underlying matter content, allowing one to distinguish between ordinary matter, a cosmological constant and phantom-like components. These results establish horizon thermodynamics as a sensitive probe of Cotton gravity, offering a complementary perspective beyond background kinematics and enabling a characterization of the statistical and thermodynamic properties of spacetime within the Codazzi formulation.

We investigate the renormalization group flow of a gravity--matter system in which a scalar field is minimally coupled to Einstein gravity and its kinetic term is given by a scale-dependent form factor $f_Λ(-\Box)$. Employing the Wilsonian proper-time flow equation, we derive a closed integro-differential equation that encodes the dependence of the form factor on the UV cutoff $Λ$. We solve the resulting fixed-point problem with a pseudospectral discretization and find a non-trivial fixed point for which $f_\ast(-\Box)$ departs from the canonical $-\Box$ behavior. Linearizing the flow about this solution yields a discrete spectrum of perturbations and a corresponding set of critical exponents, indicating a non-trivial scaling structure in this non-local sector compatible with asymptotic safety. We also observe that the form factor becomes local once the UV cutoff is removed, suggesting that the bare action associated with this fixed point is local in the scalar two-point sector.

We report the first experimental realization of backward retrieval in a spin-wave quantum memory based on a Stark-echo-modulated protocol in Eu3+:Y2SiO5. By using Stark control, we preserve the full optical depth of the ensemble while suppressing coherent noise, enabling conditional storage fidelities above 97%. Our analysis shows that the present backward-retrieval efficiency is mainly limited by technical imperfections rather than by fundamental constraints. With realistic engineering improvements, backward retrieval in this protocol could move beyond the reabsorption-limited forward-emission regime. The protocol is also compatible with cavity-enhanced operation, offering an additional route toward higher efficiencies. These findings establish Stark-echo modulation as a practical and scalable route to high-efficiency, long-lived solid-state quantum memories.

Practical quantum key distribution (QKD) modulators inevitably introduce correlations, causing the state emitted in a given round to depend on the setting choices made in previous rounds. These correlations break the round-by-round independence structure on which many widely used security proof techniques rely, leaving a significant gap between available theoretical guarantees and the reality of practical implementations. In this work, we develop a finite-key security proof for decoy-state BB84 against general coherent attacks that rigorously incorporates correlations introduced by Alice's bit-and-basis encoder, while requiring only partial characterization of such correlations.

We investigate the spectral structure of reset-driven Floquet quantum channels generated by the Hamiltonian evolution of a many-body system followed by periodic resetting of a bath. By tuning a chaos-controlling parameter in the underlying Hamiltonian, we uncover an exceptional-point-induced spectral transition from a symmetry-constrained ergodic regime to a fully chaotic regime. Across this transition, increasing the chaos parameter causes the real eigenvalues of the channel to drift, coalesce at exceptional points, and bifurcate into complex-conjugate pairs, signaling the progressive breaking of symmetry constraints in operator space. We further show that the channel spectrum sharply distinguishes chaotic, ergodic, many-body localized, and scarred dynamical regimes. Finally, we connect the leading channel eigenvalues to experimentally accessible probes based on quantum mutual information, establishing a link between the spectral organization of reset-driven quantum channels and observable relaxation dynamics.

We introduce a new general-relativistic timing observable that measures the breaking of reflection symmetry in photon arrival times caused by black hole spin. Using backward ray tracing in the Kerr spacetime, we construct time-delay maps across the observer image plane and define a mirror-paired asymmetry based on photons arriving from opposite sides of the projected spin axis. In the Schwarzschild limit ($a=0$), the asymmetry vanishes to numerical precision, providing a stringent validation test of the method. For rotating black holes, Kerr rotation breaks the left-right propagation symmetry of null geodesics, producing systematic differences between prograde and retrograde photon trajectories and resulting in a nonzero mirror-paired timing asymmetry, $A_t$. We find that $A_t$ increases with spin and depends strongly on observer inclination and emission radius, with the largest signals arising from emission close to the black hole and from intermediate to high inclinations. Converting the dimensionless asymmetry into physical units yields timing offsets ranging from seconds to hours for representative supermassive black hole systems. Unlike traditional timing analyses based on spatially integrated signals, the observable introduced here isolates directional information encoded in Kerr photon propagation and provides a physically motivated timing signature of black hole rotation. We discuss the implications of this effect for strong-gravity timing studies and X-ray reverberation mapping.

GW240925 and GW250207 are two loud gravitational-wave signals from binary black hole coalescences observed with network signal-to-noise ratios $\sim 32$ and $\sim 69$, respectively, by the LIGO Hanford--LIGO Livingston--Virgo network. Gravitational-wave signals from coalescing binaries have characteristic phase and amplitude evolution predicted by general relativity. These signal waveforms, together with measured instrumental calibration uncertainties, are used to infer source parameters. However, for sufficiently loud detections it is possible to constrain the calibration of the detectors directly using the signals themselves. We present the first informative astrophysical measurements of gravitational-wave detector calibration. For GW240925, we verify the inference of Hanford calibration from the astrophysical signal through cross-checks with known calibration errors obtained from in-situ measurements. At the time of GW250207, the Hanford detector was not fully stabilized, leading to elevated calibration uncertainties; thus, astrophysical calibration is essential to obtain accurate data and to enable source localization. These well-localized, high signal-to-noise observations have the potential to offer precise measurements of source properties, stringent tests of general relativity, and informative dark siren measurements, provided that calibration uncertainties are properly incorporated. As detector sensitivity improves, astrophysical calibration will become an increasingly valuable complement to in-situ calibration measurements. Obtaining accurate calibration will be essential for precision gravitational-wave science.

Encrypted cloning offers a means of introducing redundancy into quantum storage while respecting the no-cloning theorem: an unknown state is encoded into multiple signal-noise pairs, and only authorized subsets can recover the original information. However, the leakage properties of unauthorized subsets particularly for higher-dimensional systems (qudits) have remained unexplored. In this work, we systematically classify the informative subsets of the storage register in the qudit encrypted-cloning protocol. We focus on unauthorized subsets of size $n$ that contain exactly one qudit from each signal-noise pair. We show that the presence or absence of information leakage is determined by the solution set of a system of congruences whose coefficients depend on the dimension $d$ and on the numbers of signal and noise qudits in the subset. The reduced state is completely uninformative if and only if the congruence system admits only the trivial solution; otherwise, it retains a residual dependence on the input state through specific generalized Pauli operators. Low-dimensional examples ($n=1,2,3$) are worked out explicitly, and the complete classification is expressed in terms of a greatest-common-divisor condition. Our results extend the parity-based classification known for qubits ($d=2$) to arbitrary finite dimensions, revealing a dimension-dependent boundary of confidentiality in encrypted cloning.

This study investigates a cosmological scenario within the f(Q,L_m) gravity framework to explore whether one geometric model can simultaneously describe the early and late-time accelerated epochs. Motivated by the recently proposed f(Q,L_m) gravity framework by Hazarika et al. [Phys. Dark Universe 50 (2025) 102092], we adopt a minimal polynomial form, f(Q,L_m) = -Q + alpha Q^2 + 2L_m + beta QL_m, and the late-time dynamics are reconstructed by introducing Holographic Ricci Dark Energy (HRDE) as an effective fluid. The resulting background evolution demonstrates smooth accelerated expansion, stable Hubble parameter behavior, and an effective equation of state that approaches the de Sitter regime. Bayesian analysis utilizing Pantheon supernovae, cosmic chronometer, and DESI BAO data reveals that the matter-geometry coupling parameter beta is weakly constrained and remains consistent with the LambdaCDM limit. In the high-curvature regime characteristic of the early Universe, the quadratic non-metricity term alpha Q^2 dominates the dynamics, resulting in a Starobinsky-like inflationary phase driven solely by geometric effects with predicted n_s and r values consistent with Planck 2018 observations. Furthermore, quantum-gravity-inspired corrections are examined through a Relativistic Generalized Uncertainty Principle (RGUP), implemented as a momentum-dependent deformation of the effective spacetime metric. These corrections maintain the geometric inflationary background while introducing minor perturbative shifts in higher-order inflationary observables, specifically the running of the spectral index. Overall, these findings indicate that the f(Q,L_m) framework offers a dynamically consistent geometric model in which early and late cosmic acceleration arise from distinct curvature regimes, with RGUP effects causing sub-leading modifications.

Nanophotonic quantum memory is a vital component for scalable quantum information processing in quantum computing, networking, and sensing. Here we store single-photon-level telecom-band optical pulses for more than 1 microsecond using an atomic frequency comb in erbium-doped thin-film lithium niobate, far exceeding what is practically achievable by propagation in even the best nanophotonic devices because of propagation losses. We verify the quantum nature of this storage by demonstrating phase coherence and sub-single-photon noise upon retrieval. We also show the flexibility of our platform by storing up to 20 temporal modes and demonstrating an acceptance bandwidth up to 2.2 GHz. These results establish erbium-doped thin-film lithium niobate as a practical platform for on-chip quantum memory at telecom wavelengths, a key missing element for photonic quantum computing and quantum networking.

External matter distributions can substantially reshape the strong field environment of compact objects, yet this effect is usually neglected in idealized isolated models. In this work, we investigate geometrically thin, optically thick relativistic accretion onto a static axisymmetric space-time that describes a slightly deformed compact object immersed in an external quadrupolar field as an exact solution of vacuum Einstein field equations. Our aim is to determine whether such locally geometries can produce distinctive accretion signatures and, more broadly, to identify the physically meaningful radial domain over which the local solution remains self-consistent. We show that the external quadrupolar distortion leaves a clear imprint on both orbital dynamics and accretion structure. We further find that the outer edge of the radiating region is closely tied to the transition between radiation pressure and gas pressure dominance, which may link the geometry to the thermodynamic properties of the flow. Therefore, the local nature of the distorted spacetime is not merely a formal geometric feature, but has observable consequences for the morphology and emission properties of accretion flows.

The circuit dynamics constructed by traveling-wave parametric amplifiers (TWPA), using superconducting nonlinear asymmetric elements (SNAILs), are known to be approximately described by the Korteweg-de Vries (KdV) or modified KdV equations in the continuum limit and admit soliton solutions. The soliton spatially modulates the effective propagation velocity of the weak probe field, which leads to the effective realization of the causal structure of the analogue event horizons in the SNAIL-TWPA circuit system. In this paper, we derive the master equation for the weak probe field where the background soliton acts as an effective potential. We show the absence of normalizable negative modes in the SNAIL-TWPA circuit system by using the language of supersymmetric quantum mechanics. We also present the first study of quasi-normal modes (QNM) of the SNAIL-TWPA analogue black-white hole system by semi-analytic and numerical methods. Based on the resultant QNM frequency, we clarify the timescale at which nonlinear dispersion becomes effective in the SNAIL-TWPA circuit system and demonstrate how ringdown is excited.

While world models learn compact representations of complex environments, they lack a physics-grounded metric to assess the structural fidelity of their latent spaces. We identify the wavelet scaling exponent $α$ as a critical diagnostic, proposing optimal representations satisfy variance equipartition ($α\approx 1/2$) -- mirroring Kolmogorov's inertial range. We establish $α= 1/2$ as a sharp transition boundary for the classical simulability of amplitude-encoded quantum kernels. Using tensor-network theory, we prove latents with $α> 1/2$ reside in an area-law phase admitting efficient classical emulation, while $α< 1/2$ triggers a volume-law phase where the Matrix Product State bond dimension $χ$ grows exponentially with qubit count $n$. Analyzing pre-trained VideoMAE latents reveals a dichotomy: spatial tokens approach the equipartition limit ($α\approx 0.423$), but permutation-invariant feature channels exhibit unstructured disorder ($α\approx -0.123$). This forces real-world latents deep into the volume-law phase, providing a data-driven necessary condition for simulation hardness. Finally, we apply Weingarten calculus to derive the exact variance of the scrambled transition probability under a 2-design ensemble. We prove this variance scales strictly as $\Var[X] = Θ(d^{-2})$. We confirm this numerically with a log-log slope of $-1.881$ ($R^2 = 0.999$), identifying a formidable shot-noise wall demanding a measurement budget of $M = Ω(d^2)$ that constrains quantum machine learning scalability.

Running a quantum circuit on current hardware involves a sequence of engineering decisions, each with tunable parameters and distinct error characteristics. Existing tools optimize each decision in isolation, leaving practitioners unable to determine how much each decision contributes to final output quality. We present QuBridge, a pipeline analysis tool that decomposes quantum computation into three decision layers and measures each layer's fidelity contribution through progressive ablation and isolation experiments. Applied to quantum teleportation under IBM-calibrated noise models, the framework surfaces three phenomena that end-to-end measurement obscures. Qubit selection narrows the worst-case fidelity band from 11.8% to under 2% with downstream layers held fixed, without changing the peak. Per-gate pulse-shape assignment adds a +0.9% residual gain whose attributed magnitude depends on upstream layout. Error-detection encoding is not uniformly advantageous, and its conditional benefit emerges for input states whose dominant error channel is detectable by the chosen code. QuBridge operates on cached calibration data without requiring live hardware access.

In the Noisy Intermediate-Scale Quantum (NISQ) era, limited qubit counts and high gate error rates directly constrain circuit fidelity, making the minimization of CNOT gate counts crucial. While conventional compilers prioritize heuristic efficiency, there is a compelling need for "accuracy-first" transpilation that prioritizes gate reduction over compilation latency. We propose a framework leveraging the Digital Annealer (DA) via two complementary strategies: (1) Hybrid, which uses DA-driven global initial mapping combined with high-speed heuristic routing by Qiskit, and (2) Full DA, which solves mapping and routing as separate DA-assisted QUBO subproblems within an iterative workflow. Benchmarks demonstrate that our Hybrid approach achieves an average CNOT reduction of 13.7 % (up to 57.4 %) compared to Qiskit's highest optimization level, with the largest gains on structured circuits such as GHZ and ASP where the initial layout is decisive. The Full DA approach matches Hybrid on structured circuits and outperforms ISAAQ by 23.1 % on average (maximum 90.8 %), but degrades on circuits with random or concentrated connectivity - exposing a trade-off between QUBO size and solution quality when the entire circuit is encoded in a single annealing pass. Although these global optimizations incur higher computational overhead than pure heuristics, our results indicate that for high-precision workflows where gate noise is the primary bottleneck, DA-assisted global initial placement provides a practical "time-for-quality" trade-off for enhancing the utility of near-term quantum hardware.

Light propagating through a perturbed spacetime could imprint the underlying gravitational waveform directly onto electromagnetic observables. In this Letter, we develop a covariant perturbative framework for polarized photon propagation in generic curved spacetimes, and derive a compact expression for the observable polarization-angle (PA) swing during Kerr ringdown, explicitly demonstrating its time-domain locking to the quasi-normal modes. We confirm this behavior using dynamical ray-tracing calculations for a broad class of photon trajectories. Photons grazing the strong-field region exhibit an achromatic, damped PA oscillation that tracks the ringdown, with a phase set by the mode's angular structure. The swing amplitude can reach $\sim 10^{\circ}$ and leaves distinctive signatures in spatially resolved autocorrelations. These results open a new polarimetric window onto black hole mergers and ringdown.

Scaling superconducting quantum processors beyond the constraints of monolithic planar architectures is essential for fault-tolerant quantum computation. Here we demonstrate a three-dimensional (3D) integrated superconducting quantum processor in which two qubit chips are vertically stacked on opposing sides of a carrier chip and galvanically connected via multilayer flip-chip bonding. Intrachip qubit coupling is mediated by planar tunable couplers, whereas interchip coupling is enabled by vertical tunable couplers embedded in the carrier chip. Randomized benchmarking reveals simultaneous single-qubit gate fidelities of 99.87 % with negligible crosstalk, and controlled-Z gates achieve an average fidelity of 97.5 % for both intrachip and interchip operations. We further demonstrate high-fidelity Bell-state preparation and coherent generation of a four-qubit $W$ state, confirming the architecture's capability for interchip entanglement distribution. These results establish vertical coupling as a promising pathway toward scalable quantum processors compatible with advanced quantum error-correcting codes.

Gravitational-wave (GW) signals from compact binary coalescences (CBCs) enable independent measurements of the Hubble constant \(H_0\) via the spectral siren method, which critically depends on an accurate model of the source-frame mass distribution. While the primary mass function has been extensively studied, the impact of the secondary mass distribution on cosmological inference has been largely overlooked. Here, we perform a joint inference of population and cosmological parameters using 142 confident CBC detections from GWTC-4.0, adopting a new parametric model that flexibly describes features in both the component-mass spectrum and the pairing function, with particular emphasis on the secondary masses. We find \(H_0 = 71.4^{+13.8}_{-13.4} \;\mathrm{km\,s^{-1}\,Mpc^{-1}}\) (68\% CL) from spectral sirens alone, and \(H_0 = 73.5^{+9.2}_{-7.2} \;\mathrm{km\,s^{-1}\,Mpc^{-1}}\) when combined with the bright siren GW170817. Compared to the standard LVK Fullpop-4.0 analysis, these constraints represent improvements of \(\sim29.8\%\) and \(\sim22.2\%\) in \(H_0\) uncertainty, respectively. The enhanced precision is driven by previously unmodeled features, including peaks near \(18\,M_\odot\) and \(65\,M_\odot\) as well as mass-dependent pairing transitions at \(28\,M_\odot\) and \(52\,M_\odot\). Our results demonstrate that the secondary mass function is also a key ingredient for precision standard siren cosmology.

Losses are ubiquitous in physics and are usually regarded as harmful in quantum information processing. Here, we propose a loss-induced scheme to achieve nonreciprocity and nonreciprocal entanglement in a superconducting platform, where two remote superconducting transmon qubits are connected via two lossy auxiliary cavities. The nonreciprocity in our scheme originates from interference between multiple lossy coupling paths. The coherent phases associated with the qubit-resonator couplings reverse sign under propagation reversal, while the loss-induced phases remain direction independent. Their combined effect leads to different interference conditions in the opposite directions, resulting in unequal effective couplings. We show that this loss-induced scheme can generate nonreciprocal quantum entanglement, indicating that loss can be utilized as a resource. Moreover, the tunability of nonreciprocity and nonreciprocal entanglement in our scheme can be manipulated by the relative phase induced by loss, allowing to tailor both reciprocal and nonreciprocal behaviors. Our results establish a direct link between engineered loss and nonreciprocal entanglement in quantum information processing and offer potential applications in scalable quantum networks.

Applied category theory provides powerful mathematical tools for modelling processes and their composition. Symmetric monoidal categories, which involve series and parallel composition, are particularly well-suited for describing the composition of processes in space and time. Also called process theories, they admit string diagrams, which constitute a visually intuitive, mathematically rigorous, expressive and flexible syntax that is applicable to wide-ranging scientific domains. In this thesis, we employ string diagrams to investigate a selection of topics in the areas of quantum foundations, computing, and natural language processing: (1) We formalise constructor theory as a process theory. In the context of quantum physics, we also demonstrate the conflict between constructor-theoretic principles of locality and composition. Moreover, we argue that if the principle of locality is rejected, categorical quantum mechanics (CQM) can be conceived as a constructor theory of quantum physics. (2) We develop a formalism for wave-based logic circuits with phase encoding. We motivate the formalism using the example of spin-wave circuits, and then demonstrate its utility in design, analysis and optimisation of Boolean logic circuits. (3) We investigate the elimination of inter-language grammatical bureaucracy in the distributional compositional circuits (DisCoCirc) framework. In particular, we develop a hybrid grammar for a restricted fragment of the Urdu language, and show that Urdu text endowed with this hybrid grammar maps surjectively to DisCoCirc text circuits. Furthermore, we show that for the same language fragment, Urdu and English text circuits become the same up to gate-level translation. The aforementioned work supports the view that a process-relational outlook in science is well-supported by applied category-theoretic tools, particularly string diagrams.

Rigidity conditions for a body considered as a discrete system of relativistic particles are proposed. They by themselves do not yet determine an evolution of the system, and some second-order equations must be added to them. Poincaré-covariant equations of motion compatible with these rigidity conditions are proposed and discussed. The resulting theory has the expected six dynamical degrees of freedom and therefore allows for more general motions than in Born's theory. Therefore, treating a relativistic body as a discrete system of particles could be a promising alternative to the standard approach based on Born's rigidity conditions.

We investigate the relationship between quantum battery capacity and quantum resources in a two-qubit system consisting of mutually coupled battery and charger subsystems. We find that the battery capacity decreases monotonically with the quantum entanglement, steering, Bell nonlocality and coherence, and peaks when these four quantum resources vanish. Moreover, we reveal the capacity gap between the total system capacity and the sum of the battery and charger spin capacities, which is the residual battery capacity, and establish its positive correlation with entanglement. Furthermore, unlike the first four resources, although the battery capacity decreases monotonically with quantum imaginarity, its disappearance under system detuning does not guarantee a peak capacity, and this effect becomes more pronounced as the detuning increases. In contrast to the first five resources, the quantum state texture shows a positive correlation with battery capacity, but a negative correlation with entanglement, steering, Bell nonlocality, coherence, imaginarity, and residual battery capacity. These monotonic relationships are independent of the choice of system parameters. Our findings reveal the relationship between quantum battery capacity and quantum resources during the dynamic evolution of a quantum battery system, and advances the theory of quantum batteries and the development of quantum energy storage systems.

We study axial gravitational perturbations of the asymptotically flat Bardeen spacetime interpreted as a string-T-duality-inspired quantum-corrected Schwarzschild black hole. Starting from the anisotropic-fluid background, we derive the Regge--Wheeler-type master equation and the corresponding effective potential, and compute quasinormal modes with high-order WKB--Padé and time-domain methods. We show that increasing the quantum-correction scale $\ell_0$ raises and shifts the barrier inward, causing the black hole to ring at higher frequencies and decay more slowly. The same deformation suppresses low-frequency transmission, shifts the onset of grey-body factors to larger frequencies, and reorganizes the partial and total absorption cross-sections. Overall, the results identify a clear and consistent imprint of short-distance regularization on both ringdown and scattering observables.

In this work, we investigate a cosmological model within modified teleparallel gravity using two functional forms of $f(T)$: a hybrid model $f(T)=e^{γT}T^σ$ and a logarithmic model, in the context of a periodic cosmic evolution driven by an oscillating deceleration parameter $q(t)=m\cos(kt)-1$. This approach describes a cyclic Universe with successive transitions between decelerating and accelerating phases. By constraining the model with observational values $m \simeq 0.48$ and $H_0 = 69.2\,\text{km}\,\text{s}^{-1}\,\text{Mpc}^{-1}$, we recover the present accelerated expansion with $q_0 \approx -0.52$, while larger values $m \geq 1$ lead to strongly oscillatory regimes including super-acceleration. For the hybrid model ($γ= 0.1$, $σ= -0.5$), the energy density remains positive, while the pressure oscillates. The equation of state evolves dynamically, crossing both quintessence and phantom regimes. In contrast, the logarithmic model stabilizes the dynamics, regularizes divergences, and yields smoother evolution, with the equation of state mainly remaining in the quintessence regime. The analysis of energy conditions shows that the violation of the SEC supports accelerated expansion, while the partial validity of NEC and DEC ensures physical consistency. Overall, this framework provides a flexible alternative to the standard $Λ$CDM model, allowing a unified description of different phases of cosmic expansion.

Large curvature perturbations generated during slow first-order phase transitions are a promising source of primordial black holes. However, recent analyses suggested that the mechanism is ruled out once the density contrast and the formation threshold are evaluated in the same gauge. In this work, we show that this mechanism remains viable: after a supercooled transition, reheating can be sufficiently slow that the Universe enters an early matter-dominated era, during which even small overdensities grow and collapse into primordial black holes. An interesting feature of this scenario is that the black holes are produced with large spins.

The measurement of top-quark spin correlations provides a key tool for probing its interactions with high precision. Owing to its extremely short lifetime ($τ\sim 10^{-25}$ s), the top quark preserves its spin polarization information, making the $t\bar{t}$ system an ideal framework for investigating quantum correlations in high-energy physics. In this work, we analyze quantum correlations in $t\bar{t}$ pairs produced in QCD using several quantum information-theoretic measures, including Bell nonlocality, quantum steering, concurrence, and geometric quantum discord. Their dependence on kinematic variables is examined in both the $gg \to t\bar{t}$ and $q\bar{q} \to t\bar{t}$ channels, with convergence toward the $gg \to t\bar{t}$ dominated regime in the ultra-relativistic limit ($β= 1$). We also investigate the effect of three effective decoherence channels (AD, PD, and PF). The AD and PD channels lead to a monotonic degradation of correlations as the decoherence parameter $p$ increases, while the PF channel exhibits a symmetric behavior around $p=1/2$. The impact of these channels on quantum teleportation is analyzed, showing that it remains above the classical threshold of $2/3$ even in the presence of noise. These results indicate that certain quantum resources can persist despite decoherence, opening new perspectives at the interface of quantum information and particle physics.

The hypergraph product creates a quantum stabilizer code from two input classical linear codes; a paradigmatic example being the surface code as a hypergraph product of two classical repetition codes. Many properties of the hypergraph product code can be inherited from those of the classical codes such as the code dimension, minimum distance and certain fault-tolerant gadgets. We investigate ways to reduce the number of physical qubits in hypergraph product codes while maintaining some of their useful properties for fault tolerance. We show that the code dimension, canonical logical basis, and minimum distances of the hypergraph product code are preserved through this reduction. We also provide distance-preserving syndrome measurement schedules as well as examples of reduced hypergraph product codes with parameter improvements such as $[\![610,64,6]\!] \rightarrow [\![441,64,6]\!]$ and $[\![1225,49,11]\!] \rightarrow [\![931,49,11]\!]$. In memory simulations with circuit-level depolarizing noise, we observe that the reduced codes can have similar subthreshold performance as their unreduced versions, but using fewer physical qubits. Finally, we show how overhead reduction can be compatible with homomorphic measurement gadgets, fold-transversal gates and automorphisms, which extends the savings to logical computation.

We develop a potential-independent cosmographic framework, in which cosmographic parameters are promoted to dynamical variables within a closed autonomous system. Although the cosmographic hierarchy is formally infinite, we achieve closure by mapping potential slow-roll parameters onto the kinematic phase space within General Relativity with a minimally coupled scalar field. Within this framework, we perform a stability analysis and show that inflationary (quasi-de Sitter) solutions arise as natural attractors, while stiff-fluid configurations act as repellers without invoking the slow-roll approximation. To describe the transition to standard Big Bang evolution, we extend the system to include a radiation component and a phenomenological decay term. This leads to a generalized, potential-independent description of reheating characterized by an effective equation of state $w_{\rm eff}$. We demonstrate that the radiation-dominated phase is the late-time attractor of the extended system. These results provide a unified kinematical description of the expansion history from inflation through reheating, bridging cosmography and scalar field dynamics.

Simple families of quantum Hamiltonians can simulate general many-body systems at arbitrary precision through the use of perturbative gadgets, however this generally requires interaction strengths spanning many orders of magnitude which scale polynomially in the system size and inverse precision, resulting in physically unrealisable systems. In this work, we show that for non-critical systems these required scalings can be exponentially reduced through classical post-processing, by simulating the model at smaller energy scales and extrapolating observables to the perturbative limit. In particular, we show that both local and extensive properties of thermal states with exponentially decaying correlations and ground states with a sufficiently stable gap can be simulated using gadgets whose interaction strengths scale only polylogarithmically in the inverse precision and the system size. As a key tool, we develop a generalised treatment of the local Schrieffer-Wolff transformation for geometrically quasi-local Hamiltonians over many energy scales, facilitating the analysis of perturbative gadget Hamiltonians without extensive global energy penalities, which may be of independent interest.

The Laser Interferometer Lunar Antenna (LILA) is a proposed gravitational-wave project aiming to take full advantage of the Moon's environment to access the deci-Hz band and detect intermediate-mass black hole (IMBH) binaries of mass $\sim 10^2-10^6 \, M_{\odot}$ (arXiv:2508.11631). With an observational period of 4 years, LILA can extend its IMBH detection horizon to the very early Universe, directly probing the first population of massive black holes ($z \sim 20-30$). LILA could also detect intermediate-mass-ratio inspiral systems with a total mass of $\sim 10^4 - 10^6 \, M_{\odot}$ and a mass ratio of $\sim 10^{-4} - 10^{-2}$. LILA can discover IMBH binaries months to years before merger with measurable eccentricity residuals retained from their formation, providing crucial early warning for multi-messenger and multi-band follow-up. The high SNR ($\gtrsim 100$) events detectable with LILA would enable strong-field tests of gravity. With these capabilities, LILA will provide important insights into the formation and evolution of massive black holes, as well as the astrophysical environments and evolutionary pathways of black hole binaries. LILA will also complement current LIGO/Virgo/KAGRA detections of pair-instability mass gap events, hierarchical merger candidates, and light IMBH mergers, while expanding the upper envelope of discovered black holes with stellar origin to masses of $\gtrsim 250 \, M_{\odot}$.

We compute the graviton absorption and emission rates by hydrogen atoms in line with the results obtained by Weinberg, Gould, Dyson and other authors. The spontaneous emission of gravitons by the hydrogen atoms has a tiny undetectable rate, while the absorption rate of gravitons is much higher and is proportional to the number of hydrogen atoms and to the graviton luminosity. The graviton luminosity of Sun, or a typical star, is induced by the scattering of electrons and protons in a completely ionised hydrogen plasma at the core of the Sun and their energies are in the eV to keV range. We suggest measuring the excess in the ratio of the photon luminosities from interstellar hydrogen atoms that is induced due to the absorption of gravitons. The excess in the ratio of photon luminosities would indicate the presence of gravitons.

The population of compact binaries encodes information about their astrophysical origins and the expansion of the universe. Hierarchical Bayesian methods infer these properties by combining single-event posteriors. As catalogs grow, however, this approach becomes computationally expensive and is subject to increasing Monte Carlo uncertainty. We introduce Dingo-Pop, a simulation-based framework that infers population posteriors directly from gravitational-wave strain data. The data for each event are embedded into low-dimensional tokens and combined using a transformer trained on simulated catalogs subject to selection effects. This enables (i) population inference without per-event Monte Carlo sampling noise, (ii) amortization across variable catalog sizes using a single network, and (iii) end-to-end inference in about one second. We train a network for catalog sizes of 25 to 1000 events, and obtain well-calibrated posteriors consistent with traditional methods. By avoiding per-event analyses that can take hours to days, Dingo-Pop enables new classes of large-scale injection studies; as an application, we examine how spectral-siren Hubble constant uncertainties change with catalog size.

It was proposed recently that the Schrödinger wave function can be reconstructed exactly from a discrete superposition of classical action branches weighted by associated classical densities, without semiclassical approximations. We examine this construction for quantum tunneling through finite potential barriers and for quantum phase phenomena. Although formally consistent when the Hamilton-Jacobi equation admits globally defined real branches, the construction breaks down in classically forbidden regions where no real classical action exists. Using rectangular and Coulomb barrier tunneling in alpha decay and nuclear fusion, we show that the wave function requires either a non-vanishing quantum potential or complex-valued action. The growing barrier component fixed by global boundary conditions is essential for transmission and cannot arise from local real classical trajectories alone. Berry phase, flux quantization, Josephson tunneling, and dc SQUID interference likewise impose global phase constraints absent from local classical action transport.

We give a quantum algorithm for a novel type of black-box problem: identifying a hidden $d$-regular base graph $G$ on $n$ vertices from oracle access to an obfuscated version of it, rather than traversing it. From $G$ we build the spired graph $G_{\rm spire}$ in three steps: each vertex is lifted into an exponentially large cluster, with adjacent clusters joined by a random bipartite graph; each cluster is then crowned with a balanced spire; finally, all vertices are randomly relabelled. Specializing to $G=K_2$ recovers the welded-trees graph. Our algorithm is conceptually simple: a continuous-time quantum walk on $G_{\rm spire}$, followed by a single Hadamard test at a classically precomputed time $t^*$; the algorithm returns the candidate whose predicted amplitude is closest to the measurement. The design rests on a rigorous spectral theory: from the apex of any spire, the walk is confined to a polynomial-dimensional invariant subspace evolving under the adjacency matrix of a simpler towered graph $G_{\rm tower}$; that matrix block-diagonalizes into $n$ independent tridiagonal systems of size $n$, each solved in closed form by a Chebyshev secular equation. Efficient numerics enabled by this decomposition supply $t^*$ and the predicted amplitudes. On the prism graphs $Y_m$ versus the Möbius ladders $M_m$ (each on $n=2m$ vertices), the numerical study supports a precise conjecture that $\widetilde O(n^2/\log n)$ measurements at evolution time of order $m^2$ suffice to distinguish the two families; we have tested $4 \le m \le 5121$ ($n$ up to $10242$). By analogy with the welded-trees lower bounds, we further conjecture that any classical algorithm requires queries exponential in $n$. Together these conjectures point to an exponential quantum speedup for the identification of an obfuscated base graph.

We present new empirically grounded forecasts for the detectability of the stochastic gravitational-wave background anisotropies assuming a population of stellar-mass compact binary coalescences as its source. We quantified the discovery potential using simulations based on the Euclid Flagship Galaxy Catalogue and LIGO-Virgo-KAGRA observational constraints in combination with detailed theoretical modelling. We considered the multi-messenger cross-correlation with galaxies as well as the gravitational wave-only cross-correlation across observation-time bins. For compact binaries up to redshift $z<3$, we found that an angular resolution of $θ= 4.1$ deg ($\ell \geq 44$) is required for discovery within five years of observation via cross-correlation with a galaxy catalogue that is complete up to limiting magnitude $i < 24.7$ and has redshift uncertainties $σ_z = 0.003 (1+z)$. Extending the time range to ten years alleviates that requirement to $θ= 6.5$ deg ($\ell \geq 28$). We also showed that binning the galaxies in redshift allows us to reconstruct the evolution of the kernel, which can be used to further constrain compact binary population models. Discovery without a multi-messenger tracer has proven significantly more challenging, requiring exclusion of the loudest events, $θ= 1.8$ deg ($\ell \geq 95$), and a favourable coalescence rate. In light of the plans being carried out in the community for ongoing and upcoming galaxy surveys, this work bodes well for the multi-messenger discovery and exploration of the stochastic gravitational-wave background in the era of next-generation observatories such as the Einstein Telescope and Cosmic Explorer.

Characterizing errors on many-qubit quantum computers remains a key challenge to understanding and improving the performance of these devices. Current characterization methods either don't scale beyond a few qubits, or make simplifying assumptions (such as assuming stochastic Pauli error) that obscure the underlying physical error mechanisms. In this work, we present a scalable extension to gate set tomography-linearized gate set tomography-that enables characterization of many-qubit systems. Linearized gate set tomography relies on sparse error models, a linear approximation to enable efficient data fitting, and data from shallow circuits-so that the systematic error in the linear approximation is small. We demonstrate the accuracy of our technique using simulations of a ten-qubit system with coherent and stochastic errors, including coherent crosstalk, and we demonstrate that it is robust in presence of additional errors that are not included within the sparse error model ansatz.

Understanding stochastic inflation, and in particular the systematic computation of controlled corrections from first principles, remains an important open problem. In this work, we address this problem from two complementary perspectives. First, we derive the effective field theory governing long-wavelength modes from the reduced density matrix of a coarse-grained description. In this framework, locality in time follows from the thin-shell approximation, while locality in space is recovered dynamically in the super-Hubble regime. The resulting open effective field theory contains both dissipative and diffusive operators, with diffusion dominating as the coarse-graining scale is pushed into the infrared. This construction reproduces the usual Fokker-Planck equation at leading order and allows us to compute its corrections, including subleading contributions to the stochastic dynamics. Second, we study the evolution of the density matrix under changes of the coarse-graining scale. We show that this flow is governed by a Polchinski-type renormalisation group equation formulated directly for the density matrix. Dissipative and diffusive operators are generated dynamically along the flow, and the resulting effective action matches the Schwinger-Keldysh description. We derive a generalised Fokker-Planck equation directly from the renormalisation group flow, systematically incorporating subleading corrections and recovering the results obtained in the open effective field theory approach.

We study how a punctured surface code can turn many local $Z$-type couplings into one protected logical signal for distributed quantum metrology, where the goal is to estimate a weighted average of the coupling strengths. We consider an ordinary planar patch with two $X$-cut holes and provide a distributed sensing protocol where all $Z$-type couplings correspond to the same nontrivial logical $\bar{Z}$ for the punctured surface code. When the couplings are disjoint, we show that the relevant global condition is equivalent to the existence of a closed dual loop, called a witness, that has an odd number of intersections with every chain. Together with a local clean opening condition, this witness criterion gives a concrete punctured-code construction in which all signal chains implement the same nontrivial logical $\bar Z$. For three-body interactions with overlapping supports, we also identify the class of interactions where our punctured surface code protocol applies. Overall, our results provide a novel, noise-robust distributed sensing protocol for many-body interactions, with corresponding topological design criteria.

It is desirable that a distributed quantum computer can operate despite the replacement or failure of its constituent components, allowing the reliability of the distributed system to exceed that of its subcomponents. We first show that when quantum error correction is performed over a modular quantum network, quantum devices can be swapped out or replaced, during operation, with minimal impact on logical error rates. We also investigate the ability of the toric and hyperbolic Floquet quantum error correcting codes to protect logical information under low rates of modular node failure. In particular, we show that under the proposed distributed quantum error scheme, the selected codes are able to maintain good logical error suppression during the failure of entire nodes. For catastrophic node failure of probability p/100, we suggest that a distributed toric code would outperform one implemented on a monolithic device below a physical error rate of 0.05%.

Today, the observable cosmos exhibits a remarkable degree of isotropy and plausibly began in a nearly isotropic initial state. The properties of the Lorentzian Chern-Simons-Kodama (CSK) functional can provide an understanding of this initial state. In gravity with a positive cosmological constant, the Chern-Simons-Kodama (CSK) wavefunctional is an exact, chiral solution of the quantum gravitational constraints. We suggest that the normalizability and other issues with this functional, if interpreted as a proper state of quantum gravity, instead suggest an embedding into a larger quantum gravitational completion, and recast the CSK functional as a gravitational sphaleron with observationally desirable properties. By perturbing around the dominant de Sitter saddle of the wavefunctional with appropriate quantum gravitational boundary conditions, we find that for a closed universe the system is dynamically driven to spatial isotropy, while all anisotropic modes acquire positive quadratic curvature and are Gaussian-suppressed. The decay of this sphaleron therefore proceeds along an isotropic channel, providing an intrinsic quantum-gravitational mechanism for dynamical isotropization. This isotropization effect is robust under the inclusion of a slow-roll inflaton, and no analogous isotropic sphaleron exists for spatially flat or hyperbolic geometries. Taken together, these results recast the Lorentzian CSK functional as a chiral sphaleron that naturally prepares an approximately isotropic de Sitter background for inflation. Beyond this phenomenological study, we further suggest that the CSK functional can be understood as a boundary functional for a class of anomaly-free objects, including a complexified generalization of the Hartle-Hawking state.

Standard (radiation-gauge) metric reconstruction excludes generic sources because it requires a tracefree metric perturbation. We remove this obstruction for perturbations of Petrov type D spacetimes by introducing a traceful radiation gauge. Two first-order transport equations determine the metric trace from the stress-energy tensor, and the remaining metric components follow hierarchically from the Newman-Penrose equations. We illustrate the method for a Schwarzschild black hole with a thin static shell, including a source-supported static completion sector.

Random circuit models often describe local dynamics using generic two-qubit gates, which have proven successful in capturing entanglement growth and operator spreading in many contexts. This approach naturally leads to the expectation that detailed gate structure plays only a limited role in coarse-grained entanglement and scrambling diagnostics. We show that the internal structure of multipartite circuit primitives can significantly influence these dynamical rates, even within a fixed random-circuit architecture. To investigate this, we study an exactly simulable family of Clifford quantum circuits built from fixed $n$-qubit graph-state preparation unitaries, which we treat as elementary building blocks. Specifically, we consider a one-dimensional chain of $N$ qubits initialized in a product state and evolved by layers in which nonoverlapping length-$n$ blocks are placed at uniformly random positions with sparsity $α$. We find that different choices of graph-state building blocks lead to strongly varying dynamical rates. Graph states that are inequivalent under local Clifford (LC) transformations generate sharply different entanglement velocities $v_E$ and butterfly velocities $v_B$, even though the circuits are drawn from the same ensemble with identical architecture and randomness parameters. We further show that this hierarchy is captured by two complementary block-level characteristics: the distribution of entanglement across internal bipartitions of the graph state, which correlates with $v_E$, and a graph-theoretic connectivity profile across bipartitions, which correlates with $v_B$. Neither descriptor alone fully determines the dynamics; rather, entanglement growth and operator spreading are controlled by distinct structural features of the local circuit blocks. Notably, AME states appear among the fastest scrambling building blocks within the ensembles studied here.

We present a novel implementation of an n-qubit fanout gate using resonance engineering. Our proposed mechanism uses Jaynes-Cummings interactions between multiple qubits and a common harmonic oscillator to realize a fanout gate at the system-level. Our theoretical analysis establishes upper bounds on the gate error, demonstrating linear infidelity scaling in constant time -- a favorable trade-off compared to a conventional CNOT decomposition. To validate the performance of our scheme at large system sizes, we exploit permutation symmetry to reduce the simulation complexity from exponential to polynomial in the number of qubits, enabling simulation up to 100 qubits. The results of this numerical analysis are consistent with our theoretical findings and allow us to characterize the performance well. Our gate will enable faster stabilizer readouts and could provide polynomial speedups in many quantum algorithms.

Hints of cosmic microwave background polarization rotation ($Δ\vartheta \sim 10^{-3}$ rad) are commonly attributed to late-time dynamics of ultralight axions. We show that such ultralight degrees of freedom are not required. Polarization rotation naturally arises as a geometric interface phase acquired when photons cross interfaces between topologically distinct dark sector vacua. The effect is a discrete phase shift fixed by the normalization of a wall-supported electromagnetic Chern--Simons interaction and protected by an emergent $1$-form symmetry of the low energy effective theory. This mechanism reproduces the familiar adiabatic rotation induced by light axion domain walls, but persists for arbitrarily thin walls where the axion is heavy or absent. In this regime the rotation manifests as a Pancharatnam phase localized at vacuum interfaces, independent of redshift and photon frequency below a natural ultraviolet cutoff. Cosmic birefringence thus emerges as a probe of vacuum structure in the dark sector, rather than of light-field dynamics.

We construct a 3D Pauli stabilizer Hamiltonian whose ground state space can encode a qubit for exponential time when coupled to a bath at non-zero temperature. Our construction recursively applies a sequence of transformations to a seed Hamiltonian that increases the memory lifetime of the encoded qubit while maintaining geometric locality in $\mathbb{R}^3$.

The ability to locally control and measure subsets of ancilla qubits in an efficient and crosstalk-free manner is a key ingredient in quantum error correction (QEC). Dual-species neutral atom arrays offer an ideal implementation of these capabilities, enabling independent state preparation, manipulation, and detection on each species. In this work, we realize such a dual-species Rydberg array of Na and Cs atoms trapped in co-localized 2D optical tweezer arrays, using Na as an ancilla to measure stabilizers of surrounding Cs data qubits. We identify the finite interspecies Rydberg-Rydberg interaction strength as a practical obstacle to high-fidelity multi-body entanglement and show that, by tuning the Rabi frequency and the detuning of the Rydberg driving field, the resulting geometric phase error can be compensated. This yields a protocol for simultaneous, non-destructive, in situ stabilizer readout of multiple data qubits via global pulses alone. Using this protocol, we demonstrate non-destructive measurement of Pauli-Z stabilizers on four-qubit Cs plaquettes via a single global Rydberg pulse sequence. Our results demonstrate dual-species tweezer arrays as a promising route towards scalable QEC and open the door to new quantum control protocols leveraging both interspecies and intraspecies interactions.

An important question in binary black hole mergers is to connect properties of the remnant black hole to those of the two initial black holes. These properties include not only the final mass and spin of the remnant, but also higher multipoles and answers to other questions such as, for a given initial configuration, which quasi-normal modes of the final black hole are excited, and what are the amplitudes of these modes? Such questions have thus far been primarily addressed through a study of the emitted gravitational wave signal. In this paper we consider a different alternative, namely using quasi-local black hole horizons themselves to establish the link between the initial and final states. Recent work has elucidated the behavior of black hole horizons in a merger. Cusps forming in such otherwise smoothly evolving horizons have been shown to play a central role in connecting the two initially separate black holes with the final remnant. In the present work, we will discuss from a numerical perspective how such cusps form in detail for the head-on collision of two non-spinning black holes. We show how the mass and higher mass multipole moments behave at the cusp and suggest a phenomenological model.

We present exact solutions for the non-equilibrium steady states of a class of dissipative spinless fermionic systems with arbitrary Hamiltonian pairing terms, global charging energy interactions, and uniform single particle loss on every site. Our exact solution is found by generalizing the coherent quantum absorber technique to fermionic systems, and our result establishes the existence of hidden time-reversal symmetry in driven-dissipative fermionic models. The steady state exhibits a first order phase transition in the particle density, with the resulting jump discontinuity in density persisting even for finite dissipation rates. A mean-field description of the model exhibits a bistable regime that encompasses the first-order transition line yet which fails to accurately predict its precise location via a Maxwell construction. We also show that the model's hidden time-reversal symmetry results in an Onsager symmetry of certain two-time correlation functions.

Analog quantum computation offers a route to machine learning using controllable physical dynamics as a computational resource. However, many existing approaches rely on task-specific protocols or observables that are difficult to access experimentally, limiting generality and implementation. Here we introduce Qlustering, an unsupervised clustering framework based on steady-state quantum transport in quantum networks governed by the GKSL master equation, developed through algorithm-hardware co-design. Data are encoded as input states, and cluster assignments are inferred from steady-state output currents, avoiding full state tomography in favor of accessible transport observables. The method realizes a hybrid classical-quantum workflow in which data preparation and training are performed classically, while clustering is carried out by transport dynamics. We benchmark the method on synthetic datasets, localization, and QM9 and Iris, finding competitive performance and stability over a broad range of dephasing strengths. These results show that unlabeled data structure can be extracted directly from steady-state transport observables, identifying terminal-current readout as a native, tomography-free mechanism for unsupervised learning in open quantum networks.

Topologically-ordered quantum states with Abelian excitations can host defects that obey effective non-Abelian statistics, in principle allowing for quantum information processing via defect braiding. These extrinsic defects (or twists) are typically studied as static features of the lattice. However, an alternative proposal considers how an underlying topologically ordered quantum substrate can be locally perturbed to create and manipulate synthetic defects \cite{you_synthetic_2013}. Unfortunately, while largely referenced, elements of this proposal were never systematically studied. Understanding the energy spectrum is particularly important in finite size and finitely perturbed systems, which are crucial for experimental realizations. In this work we announce a significant step in this direction by explicitly constructing, simplifying, and numerically studying the spectral properties of synthetic defects in a model system. First, we introduce two alternative representations of this problem in both spin and Majorana languages. In the former we describe emergent virtual symmetries which constrain and simplify the problem and in the latter we show a direct connection to Kitaev's well-known Majorana chain. We utilize these simplifications to perform numerical calculations to indicate the location of the quantum phase transition driving the emergence of the synthetic defects. We conclude by discussing key steps for future work to more clearly and completely study this phenomena.

Complementarity relations constrain the distribution of coherence, predictability, and openness in quantum systems. Here we show that, in open quantum systems, these local constraints acquire a geometric interpretation through quasistatic transport. For a driven dissipative qubit, the complementarity variables define cylindrical coordinates on the Bloch sphere, while openness appears geometrically as a radial deficit associated with reduction from a larger Hilbert space. Quasistatic driving induces a work connection on the resulting steady-state manifold whose curvature determines the cyclic response. Hamiltonian-aligned dissipation produces an exact work connection and vanishing cyclic work, whereas fixed pointer-basis dissipation generates non-integrable transport, finite curvature, and holonomic response. The resulting curvature admits a phase-resolved representation on the triality manifold and develops perturbatively with pointer--Hamiltonian mismatch. In the weak-mismatch limit, the curvature is governed by a competition between coherence-preserving and pure-dephasing channels, producing symmetry-related positive- and negative-curvature sectors. These results establish a direct connection between complementarity, dissipation, and geometric thermodynamic response, and show that cyclic quasistatic work provides an operational probe of nonequilibrium quantum geometry.

Laplacians on metric graphs are used to construct continuous families of Hamiltonians with different topological structure. One such family is used to demonstrate that Hamiltonians with real-valued eigenfunctions may possess non-trivial geometric Berry's phase. Connections between non-trivial Berry's phase and topology change are discussed.

The KAK decomposition is a fundamental tool in Lie theory and quantum computing. Despite its widespread use, the mathematical foundations remain incomplete, particularly regarding the precise conditions for the decomposition and the characterization of equivalence classes under multiplication by elements of $K$. Here, we present a mathematical theory of the KAK decomposition for connected compact semisimple Lie groups and derive the decomposition for $\mathrm{SU}(4)$. In particular, we clarify the relationship between various definitions of a Cartan decomposition in the literature and give a complete proof of a general KAK decomposition theorem. We then distinguish two distinct notions of KAK equivalence classes, double coset equivalence and projective equivalence, thereby addressing mathematical inconsistencies regarding KAK classification in the literature. Specifically, for $\mathrm{SU}(4)$, we show that local equivalence classes under multiplication by $\mathrm{SU}(2)\otimes \mathrm{SU}(2)$ are geometrically represented not by the usual "Weyl chamber" as claimed in the existing literature. Instead, the "Weyl chamber" is only recovered by the projective-local equivalence which disregards global phases. We develop a systematic theory for determining equivalence and uniqueness for both notions of equivalence. Our work establishes a rigorous Lie-theoretic foundation for the theory of quantum gates and circuits.

The gravitational field of two-body system, a high energetic particle and a massive particle at rest, is studied in the linearized Einstein gravity. The ultrarelativistic particle yields a plane-fronted gravitational shockwave which perturbes gravitational field of the particle at rest. The problem can be also considered as a fixed-target high energy collision. We show that this collision is accompanied by the gravitational radiation, as is expected from the earlier results on the high-energy scattering. The new effect is a secondary spherical gravitational shockwave when the initial shockwave hits the massive particle. In the considered approximation the flux of gravitational radiation and the amplitude of the spherical shockwave are found in an analytic form. The suggested approach is also applicable when the null particle is replaced by plane null shells of a general profile. Implications of these effects for astrophysics are shortly discussed.

We investigate the benefits of partially upgrading optical networks with hollow-core fibers for QKD-classical communication coexistence. Results show that upgrading 40% of links in a metro topology can reduce the number of quantum modules by up to 49%.

The scalability of quantum computing is currently limited by physical, technological, and architectural constraints that hinder the integration of a large number of qubits within a single quantum processor. Distributed quantum computing (DQC) has therefore emerged as a viable alternative, aiming to interconnect multiple smaller quantum processing units (QPUs) to jointly operate on a global quantum state. While this paradigm enables scalable architectures, it introduces significant communication overhead due to the cost of non-local quantum operations across distant nodes. In this work we propose a distributed formulation of the iQFT over a quantum network composed of $P$ nodes, each hosting $Q$ qubits, enabling the execution on a logical register of size $n = P \cdot Q$. Furthermore, we introduce a communication-efficient variant based on a threshold-driven pruning strategy, referred to as a \emph{communication horizon}, which exploits the exponentially decreasing significance of controlled-phase rotations to safely omit remote gates with negligible impact. By reducing the number of inter-node quantum interactions, the proposed approach significantly lowers the quantum communication requirements of the distributed iQFT while preserving its functional correctness. Crucially, we show that this approach fundamentally alters the scaling of the algorithm: the entanglement resource consumption per node saturates to a constant value, reducing the global communication complexity from quadratic $\mathcal{O}(P^2)$ to linear $\mathcal{O}(P)$. As the iQFT constitutes a critical building block in many quantum algorithms, the techniques presented in this paper directly contribute to improving the practicality and scalability of distributed quantum computation.

We introduce a hybrid oscillator-qubit formulation of linear combination of Hamiltonian simulation (LCHS) for solving linear ordinary differential equations. Instead of representing the quadrature rule with a discrete-variable (DV) ancilla register in qubit-only LCHS, the method encodes the LCHS kernel in a continuous-variable (CV) ancillary mode, thereby eliminating the explicit $O(\log M_a)$ ancilla-qubit overhead, where $M_a$ is the number of discretized integral terms in the DV quadrature rule. We derive analytical error bounds for two main approximation mechanisms for the ideal kernel state preparation, showing superalgebraic convergence for Schwartz-class kernels in the truncation cutoff $N$. The required CV non-Gaussianity is captured by the finite squeezed-Fock kernel state, which generically has stellar rank $N-1$, identifying the truncation cutoff as a discrete measure of the oracle's non-Gaussian resource. For the hybrid oscillator-qubit evolution, we also obtain a product-formula bound showing that a $p$th-order formula requires $O(t^{1+1/p}(Γ_{p,N}/ε_t)^{1/p})$ Trotter steps to reach error $ε_t$, where $Γ_{p,N}$ collects Pauli commutator terms weighted by powers of the truncated position-operator norm $\|\hat{x}\|_N$. We further derive a perturbation bound for the probability of obtaining the required oscillator measurement outcome, showing that an $ε$-close implementation of the ideal LCHS oracle in operator norm induces only an $O(ε)$ perturbation in the postselection probability. In the heat-equation benchmarks, the Law--Eberly protocol achieves end-to-end solution fidelity at least 99.90%. A comparison with a matrix-product-state-based DV LCHS implementation further shows that, the hybrid construction uses a substantially more compact oracle description with reduce circuit cost.

In our previous article [arXiv:2307.12552], we introduced local topological order (LTO) axioms for abstract quantum spin systems which allow one to access topological order via a boundary algebra construction. Using the LTO axioms, we produced a canonical pure state on the quasi-local algebra, which gives a net of von Neumann algebras associated to a poset of cones in $\mathbb{R}^n$. In this article, motivated by [arXiv:2509.23734], we introduce an axiom for LTOs which ensures Haag duality for cone-like regions using Tomita-Takesaki theory. We prove this axiom is satisfied for all known topologically ordered commuting projector models. We thus get an independent proof of Haag duality for the Levin-Wen string net models originally proved in [arXiv:2509.23734]. We also give a reflection positivity axiom for LTOs, connecting to the recent article [arXiv:2510.20662]. We again prove this axiom is satisfied for all known topologically ordered commuting projector models about some $\mathbb{Z}/2$-reflection symmetry.

This paper identifies exact probabilistic simulation cost as the natural quantitative measure of quantum advantage for finite automata under strict cutpoints. It gives sharp simulation laws for two representative models. A one-way finite automaton with $c$ classical states and a $q$-dimensional quantum register has exact probabilistic simulation cost $Θ(cq^2)$, while an $n$-dimensional measure-once one-way quantum finite automaton has worst-case cost $Θ(n^2)$. The proofs develop a prepare--test framework, in which prefixes generate the relevant real operator degrees of freedom and suffixes convert them into strict-cutpoint tests. The same obstruction is recast through finite sign-rank matrices, clarifying the role of Forster's spectral method. Placed beside the surrounding two-way separations, these results give a clean hierarchy of finite-automata quantum advantage.

Quantum computers are increasingly accessible, yet demonstrations of physically meaningful simulations for real materials remain scarce. In our work we simulate low-energy magnetic excitations, specifically spin-wave spectra, of chromium tri-halide monolayers. Starting from ab-initio electronic structure calculations for these two-dimensional magnets, we derive an effective spin model and simulate low-energy spin excitations using a real-time propagation of the spin system on the commercial quantum computing cloud platform IQM Resonance. The results for systems with up to 48 qubits are validated against classical benchmarks. While some spectral features remain challenging for today's NISQ devices, our simulation achieves good agreement at quasi-constant wall-time scaling, compared to the exponential scaling of classical methods. Our results demonstrate that, even in the absence of quantum advantage, useful quantum simulations of real materials are becoming possible for domain experts via commercial cloud access to quantum computers.

Decoded Quantum Interferometry (DQI) is a recently introduced quantum algorithm that reduces discrete optimization to decoding with potential advantages over the best known polynomial-time classical algorithms for certain Max-LINSAT problems. In its original formulation, however, DQI treats all constraints uniformly and cannot exploit the weight structure present in most optimization problems of interest. In this work, we develop a theory of DQI for weighted optimization problems, focusing on the weighted Max-LINSAT problem over a prime field. Grouping constraints into $N$ blocks by distinct weights, we introduce \emph{multivariate DQI states} built from $N$-variable polynomials of bounded total degree, and derive a closed-form asymptotic expression for both their optimal expectation value and their concentration behavior. We give an explicit preparation circuit using a single decoder call, and extend the analysis to imperfect decoding. We also show that, for certain weighted OPI problems, multivariate DQI outperforms a natural weighted analogue of Prange's algorithm, which serves as the weighted counterpart of the classical benchmark used in the unweighted setting. Finally, we extend the ideas to Hamiltonian DQI, obtaining approximate Gibbs states for commuting Pauli Hamiltonians with block structure.

In multifield inflation driven by $d$ scalar fields, $O (d)$ symmetry renders the number of fields irrelevant at classical level. This ceases to be the case once stochastic effects are accommodated. The statistical quantities such as the mean number and the variance of $e$-folds as well as the primordial power spectrum and its scale dependence are perturbatively calculated in a small-noise regime. In particular, a general formula is derived for arbitrary higher-order statistical moments of the stochastic number of $e$-folds at all perturbative orders, keeping the dependence on the number of fields fully analytical. It is also discussed that the requirement for inflation to be successfully terminated puts a theoretical bound on the number of fields from above. Those general results are demonstrated for several $O (d)$-symmetric models.

We report on a fundamental disparity between stochastic noise models and algorithmic performance in NISQ-era classifiers. Utilizing the ibm_kingston processor, we characterize the "Kingston Constant" ($κ\approx 0.07$), representing a 93% signal magnitude collapse. Despite this decay, we demonstrate that the Hadamard Test Perceptron maintains a 93.9% MNIST accuracy, validating our proposed Hadamard Resilience Law. However, a systemic divergence -- the "Coherence Gap" ($Δρ\approx 0.91$) -- emerges at high feature depths ($N=256$), where physical hardware collapses while stochastic simulations remain resilient. This gap identifies coherent phase errors, rather than depolarizing noise, as the primary barrier to scaling quantum linear layers. Furthermore, experimental results on the ibm_kingston processor reveal a "Coherence Wall" at $N=256$, where circuit depth ($D \approx 10k$) exceeds the hardware's resilient depth limit ($D_{max} \approx 3.5k$). We provide a refined hardware-aware model that accounts for this coherence-induced signal decay, establishing a predictive boundary for robust quantum linear layers on current NISQ devices.

Energy-storage singularities in quantum batteries are often associated with equilibrium quantum criticality. Here we show that, in quench-driven many-body batteries, such singularities can originate from dynamical criticality in momentum space. Using the transverse-field Ising chain as a representative free-fermion quantum battery, we develop a momentum-resolved description of the charging process. The long-time stored energy forms a dephasing plateau whose dependence on the quench strength becomes nonanalytic when a real dynamical critical momentum emerges. More generally, for free-fermion two-band quantum batteries, each momentum sector acts as an independent coherent charging channel, and the condition for a dynamical quantum phase transition (DQPT) is equivalent to perfect normalized charging of the critical mode. At the critical times, this mode has a vanishing Loschmidt amplitude, maximal normalized stored energy, and zero instantaneous power at the turning point between energy absorption and backflow. We further show that the single-mode charging signal-to-noise ratio (SNR) develops sharp signatures at the same critical times, providing a direct charging-based probe of DQPT. Thus, nonequilibrium criticality does not simply enhance the total stored energy or power, which remain shaped by noncritical modes, but reorganizes energy storage by selecting optimal microscopic charging channels. Our results establish a mode-resolved connection between DQPT and quantum-battery charging, suggesting a route toward controlling many-body energy storage through dynamical criticality.

Quantum optimization algorithms are inherently probabilistic, yet they are most often used to search for a single high-quality solution. In this paper, we instead study hypergraph partitioning problems in which the desired output is itself a probability distribution over partitions. We introduce a distributional perspective on hypergraph partitioning motivated by maximin and minimax objectives such as Fair Cut Cover, and we show how these objectives align naturally with the measurement distribution produced by QAOA. To motivate the formulation, we introduce a workforce-scheduling-inspired toy problem, the Greatest Expected Imbalance problem, in which the goal is to minimize the worst expected imbalance across hyperedges. We then develop QAOA-based quantum solvers that represent distributional solutions natively through quantum states, together with quadratic hypergraph objectives suitable for standard and multi-objective QAOA. These formulations connect balanced hypergraph partitioning, polarized community discovery, and distributional fairness under a unified quantum optimization framework. For comparison, we provide optimal polynomial-time classical approximation algorithms based on semidefinite programming and hyperplane rounding. Experiments on real-world and synthetic hypergraphs demonstrate that low-depth multi-angle QAOA can outperform these classical approximation baselines on the proposed objectives, highlighting the potential of quantum algorithms for optimization problems where the solution is a distribution rather than a single partition.

We employ the polar decomposition of the Dirac field to describe it as an effective spinorial fluid. We then construct a $(1+1+2)$ covariant formalism for the Dirac field that avoids the introduction of tetrad fields and Clifford matrices. Within this framework, we analyze the conditions under which a self-gravitating Dirac field can be consistently embedded in Locally Rotationally Symmetric (LRS) space-times of types I, II, and III. In accordance with the LRS symmetry requirements, we extend a previous work by assuming that the velocity and spin vector fields of the Dirac field lie in the planes defined pointwise by the generators of the time-like and space-like congruences, which underlie the $(1+1+2)$ decomposition. We present some analytical and numerical solutions to illustrate the applicability of the proposed framework.

We summarize a set of constraints on a proposed population of primordial, ultra-massive, electrically charged compact objects, which we call astrons. The analysis combines charge generation, charge saturation, persistence of the charge in an ionized medium, screening by the intergalactic plasma, the Reissner--Nordström geometry of highly charged compact objects, lensing, and the cosmological implications of a sparse charged population. We also discuss the possible relation to the early structures revealed by the James Webb Space Telescope: if astrons are relevant there, they would be primordial dark seeds rather than luminous objects directly observed at high redshift. The resulting scenario is sharply constrained. Ordinary accretion saturation gives charges far below the large-charge phenomenological benchmark, screening is a serious plasma-physics issue, and a large charge can place the exterior geometry deep in the super-extremal regime. As expected at the level of a homogeneous Friedmann--Lemaître--Robertson--Walker (FLRW) description, the interaction energy of a population of charged objects scales as \(a^{-4}\), so the simplest perfect-fluid reduction does not generate asymptotically late-time acceleration; any acceleration era tied to that homogeneous component can only be transitory. The astron scenario should be regarded as a constrained framework whose viability depends on plasma physics and on a cosmological treatment beyond the homogeneous approximation.

Integrated photonic technologies have recently shown significant advances, enabling the possibility to implement reconfigurable interferometers with increasing size. One of the main tasks to fully exploit the capabilities of reconfigurable integrated interferometers is the possibility to precisely program their operation to perform a desired target unitary. While recipes are known for circuit layouts based on a cascade of beam-splitter and phase-shifter operations, a methodology applicable for reconfigurable continuously-coupled waveguide arrays is currently missing. Here, we devise a machine learning based approach for this task, using a black box methodology that does not rely on precise a-priori modeling of the circuit internal architectures. We verify the effectiveness and the robustness of this approach via numerical simulations on different continuously-coupled waveguides layouts, either with planar or 3D structures. The proposed method makes use of a limited number of single- and two-photon measurements, making it suitable for optical quantum information processing. The obtained results open the perspective of employing this methodology as an effective tool to program the operation of integrated interferometers designed via different architectures.

We investigate the Raychaudhuri dynamics of charged spin--nondegenerate Lorentz--violating particle congruences under minimal electromagnetic coupling. The coupling is introduced through the gauge--covariant momentum $P_μ=π_μ-qA_μ$, so that the branch dispersion relation keeps its free functional form, while the electromagnetic field enters through the evolution of $P_μ$. For a generic branch $\mathcal D^{(\pm)}(P)$, the tangent $k^μ_{(\pm)}$ and the momentum Hessian $M^{μν}_{(\pm)}$ determine the covariant acceleration, $a^μ_{(\pm)}=-qM^{μν}_{(\pm)}F_{νρ}k^ρ_{(\pm)}$. As a consequence, the Raychaudhuri equation acquires the branch-dependent electromagnetic source $-q\nabla_μ\!\left(M^{μν}_{(\pm)}F_{νρ}k^ρ_{(\pm)}\right)$. We apply this construction to the $b_μ$, $H_{μν}$, and $d_{μν}$ sectors, obtaining the corresponding branch tangents, Hessians, accelerations, and focusing equations. In flat spacetime, the electromagnetic field modifies the expansion through the divergence of the effective branch force. Therefore, uniform fields may bend the trajectories, whereas local focusing requires field gradients or, in the magnetic case, a coupling to an already deformed congruence. We also develop the analogous description for semiclassical quasiparticle beams, where the band Hessian plays the role of an effective electromagnetic response tensor. For anisotropic parabolic, Dirac--like, and Weyl--type dispersions, the same geometric structure relates electromagnetic textures to beam focusing. In two-branch systems, the opposite Hessians of the branches can produce focusing in one congruence and defocusing in the other, giving a quasiparticle realization of branch--dependent birefringence.

We study Euclidean wineglass wormholes, which mediate the nucleation of inflationary spacetimes from an existing spacetime with asymptotically flat or Anti-de Sitter regions. These wormholes are distinguished by the presence of a local maximum of the scale factor, which allows the analytically continued Lorentzian spacetime to expand after materialization. We present explicit numerical wormhole solutions supported either by an axionic field or a magnetic gauge field, in both cases in conjunction with a self-interacting scalar field. More exotic solutions, with multiple extrema of the scale factor, are also described. As we discovered recently, in the limit of small axionic or magnetic charge, wineglass wormhole solutions split into two separate geometries, one being the background spacetime and the other a disconnected no-boundary instanton. We study the associated topology changing transition in detail and provide an extensive discussion of both the properties and puzzles exhibited by this common family of wineglass/no-boundary instantons.

In this article, we solved the time--independent one--dimensional Klein--Gordon equation in the presence of $α$--attractor potential using the Log derivative method. We calculated the reflection coefficient $\mathcal{R}$ and the transmission coefficient $\mathcal{T}$, showing that the superradiance phenomenon is present. In order to demonstrate the accuracy of our method, we performed a comparison with the analytical solution for the hyperbolic tangent potential.

We investigate which dilaton gravity models can reproduce the typical two dimensional analogue black holes realized in platforms such as superconducting quantum circuits. We identify the most reasonable assumptions these models must satisfy, and determine the dilaton models for which the state-dependence of the Hawking temperature, T, can be switched on and off, a feature that is absent in four dimensional black holes. When the analogue black hole exhibits state-independent temperature, as in the cases considered here, the kinematics governing T decouples from the dynamics underlying S. Our numerical analysis reveals that the given analogue black holes do not correspond to known dilaton gravity models, limiting their usefulness for extracting theoretical insights. We then show that the logic can be easily reversed: starting from established well known dilaton models, one can derive the conditions that laboratory implementations must satisfy. This shifts the challenge from the theoretical perspective to the experimental realization.

We study axial quasi-normal modes of admixed neutron stars composed of ordinary nuclear matter and a self-interacting bosonic dark matter component. The equilibrium configurations are obtained by solving the coupled two-fluid Tolman-Oppenheimer-Volkoff equations, where the neutron sector is modeled with several realistic equations of state and the bosonic sector is described by a repulsively self-interacting complex scalar field in the strong-coupling regime. We analyze linear axial perturbations governed by a Regge-Wheeler type equation whose effective potential reflects the combined matter distribution. Using a continued-fraction method, we compute the complex eigenfrequencies of the fundamental and overtone $w$ modes. We obtain the quasi-normal mode spectrum and investigate its dependence on the dark matter particle mass, self-coupling, and the central densities of both fluids for several realistic neutron star equations of state. We find that increasing the dark matter fraction shifts the oscillation frequencies and damping times. It can also reorder the mode hierarchy through crossings, and it drives a continuous transition from neutron star-like to boson star-like ringdown behavior. Our results demonstrate that the ringdown gravitational-wave signal from post-merger compact objects could encode clear imprints of a dark matter component, offering a new probe of the dark sector with future gravitational-wave observatories.

Thanks to feeble interactions, neutrinos show special advantages in the field of quantum information (QM). The properties of quantum correlations (QCs) are fundamental for neutrino-based QM. In this paper, we investigate the influence of the Kerr--Newman metric on QCs by varying the metric parameters, namely the mass $M$, angular momentum per unit mass $a$, and charge $Q$. Both radial and non-radial neutrino propagation are considered under the weak-field approximation. The results show that, for inward propagation in the Kerr--Newman metric, the oscillation probabilities and QCs differ significantly from those obtained in the Schwarzschild metric. In the case of radial outward propagation, the angular momentum $a$ increases the oscillation period of the neutrino survival probability $P_{ee}$, entanglement, and nonlocality, whereas the charge $Q$ decreases the corresponding periods. For non-radial propagation, the modulation effects of $M$ and $a$ on the oscillation patterns of both probabilities and QCs become more pronounced. As $M$ increases, the oscillation probability remains within a higher-value range, whereas tripartite entanglement exhibits the opposite trend. Furthermore, our results reveal that, despite differences in their variation ranges, entanglement and coherence exhibit highly consistent oscillation behaviors in both radial and non-radial propagation cases. These findings provide broader quantitative support for the potential use of neutrinos as quantum information resources.

The Bayesian inverse of a quantum channel $\mathcal{E}$ is a channel $\mathcal{F}$ in the reverse direction of $\mathcal{E}$ that yields time-symmetric correlations for sequential measurements performed on open quantum systems. Such an operational form of time-reversal symmetry for open quantum systems is quite remarkable, as the dynamics of open quantum systems are inherently irreversible due to system-environment interactions. Similar to the Petz map, a Bayesian inverse $\mathcal{F}$ is defined with respect to a fiducial reference state $ρ$ for the channel $\mathcal{E}$. However, Bayesian inverses do not always exist, and it is often a non-trivial task to determine the set of states $ρ$ for which a Bayesian inverse of $\mathcal{E}$ exists. In this work, we solve the general problem of quantum Bayesian inversion for unital channels acting on a single qubit. Our analysis is streamlined by demonstrating that finding a Bayesian inverse for a unital qubit channel may be reduced to finding a Bayesian inverse of a Pauli channel, which is simply a mixture of unitary channels associated with the Pauli matrices. As such, we provide a complete description of when operational time-reversal symmetry is attainable for sequential measurements of a single qubit in the presence of unital noise.

We study an $O(N)$ scalar multiplet nonminimally coupled to gravity and follow its renormalization-group (RG) flow in the vicinity of an interacting, nonperturbatively UV-complete scaling regime of scalar-tensor theory. In the broken phase, the radial mode mediates a universal Yukawa correction to Newtonian gravity, parametrized by a strength $α$ and range $λ$. Imposing UV completeness -- regular RG trajectories that reach the UV scaling regime -- restricts the infrared data to a finite wedge, which maps to a narrow region in the $(α,λ)$ plane. Its complement is, therefore, ruled out by UV completeness alone. Remarkably, part of this theory-excluded domain lies below current experimental exclusion envelopes, so improved fifth-force searches can directly test and potentially falsify this class of UV-complete scalar-tensor models.

We investigate multipartite entanglement via the statistical properties of pure quantum states of n-qubits. By analyzing the distribution of purity among balanced bipartitions, we compare Haar-typical states, uniformly distributed on the unit sphere of states, with Hadamard states, being characterized by equal weights in the computational basis. We analyze different ensembles of Hadamard states characterized by their phase distributions. Through analytical and numerical calculations, we show that Hadamard states exhibit, on average, a higher degree of entanglement than Haar-typical states. In addition, we show that a particular class of Hadamard states, characterized by real coefficients with alternating signs, known as hypergraph states, appears especially relevant in the search for maximally multipartite entangled states, both for their structural simplicity and the increased likelihood of sampling highly entangled states. These results identify Hadamard states as a tractable yet promising class for exploring multipartite entanglement structures and advancing the characterization of maximally multipartite entangled quantum states.

Kohn-Sham density functional theory (DFT) is the workhorse of quantum chemistry, offering an attractive balance between accuracy and computational cost. Although exact in principle, DFT in practice relies on an approximation to the unknown exchange-correlation (XC) functional, which encodes the many-body quantum effects beyond the mean-field treatment. Many such approximations exist, and machine-learned XC functionals have proliferated in recent years. A persistent challenge in this area is the trade-off between accuracy and computational cost: while high-accuracy ML functionals have shown success on strongly correlated systems that are notoriously difficult for conventional approximations, their unfavorable scaling has limited broader adoption. Here, we propose a linearly scaling non-local XC approximation based on an expander graph transformer ansatz, improving the scaling of $O(N^2)$ or worse for previous ML functionals capable of reliably capturing strongly correlated systems. We show that it recovers the correct $\mathrm{H_2}$ dissociation curve in the strongly correlated regime, with promising results on planar $\mathrm{H_4}$, a system where even high-level coupled cluster methods break down. Our approach thus charts a path toward ML functionals that are both accurate on strongly correlated systems and cheap enough to deploy at scale.

Generalizing from finite samples to unseen valid states is central to discrete generative modeling. In a controlled, exactly enumerable setting, we test whether parity losses, commonly used for tractable Instantaneous Quantum Polynomial-time (IQP) training, also provide an inductive bias for generalization. We compare an IQP circuit Born machine trained by parity supervision with the same circuit trained by coordinate-wise mean-squared-error (MSE), and with a classical maximum-entropy control given the same parity moments. Parity supervision improves exact forward Kullback-Leibler (KL) fit and unseen high-value-state recovery over IQP-MSE, while the maximum-entropy control does not reproduce the full effect. A parameter-free spectral reconstruction shows that parity moments already transfer evidence from observed samples to structurally compatible unseen states, which the IQP circuit further refines. This identifies parity supervision not only as a tractable training signal, but also as a generalization mechanism for IQP Born machines when the distribution to be learned, the parity objective, and the circuit architecture are structurally aligned.

Variational quantum algorithms have attracted attention for their potential to solve combinatorial optimization problems. We study how the choice of encoding affects the resource requirements and optimization behavior of a variational quantum optimization algorithm. In order to quantify these effects, realistically inspired constrained electric vehicle (EV) fleet management problems were considered. These problems couple determining the optimal EV battery charging schedule with assigning EVs to trips requested by customers. We compare a conventional binary (qubit) trip encoding with an integer (qudit) encoding that represents assignments more directly. Both encodings guarantee the same feasible solution set, while the qudit encoding exponentially reduces the required Hilbert-space dimension. We solve many random instances of highly constrained uni- and bi-directional charging problems using qudit-based quantum approximate optimization algorithm (QAOA) and thoroughly evaluate the performance results. We find that the qudit encoding of customer trips achieves similar or better optimization performance at much reduced resource requirements and shorter simulation runtime. These results highlight qudit-native encodings as a practical route for integer and multi-valued scheduling problems in variational quantum optimization.

We construct a spectral-triple framework for a noncommutative planar system associated with a fixed nondegenerate irreducible unitary sector of the kinematical symmetry group $G_{\mathrm{NC}}$, labelled by central parameters $(\hbar_0,\vartheta_0, B_0)$ with $\hbar_0,\vartheta_0, B_0\neq 0$ and $\hbar_0 - \vartheta_0 B_0\neq 0$. For the corresponding two-parameter family $(r,s)$ of unitarily equivalent concrete realizations, we construct even spectral triples whose Dirac operators are isospectral and have compact resolvent despite the non-unital and noncompact setting. Passing to the Moyal-side description, a linear Darboux normalization and the Stone-von Neumann theorem identify the represented smooth operator algebra with the effective Moyal-side Frechet *-algebra at $\vartheta_{\mathrm{eff}} =\vartheta_0/(1 -\vartheta_0 B_0/\hbar_0)$. For each $\varrho$, this yields locally compact non-unital base spectral triples over the involutive Moyal algebra $\mathcal{A}_{\vartheta_{\mathrm{eff}},\varrho}$, with $(r,s)$ as kinematical presentation parameters and $\varrho$ as an independent star-gauge parameter. To incorporate an external $U(1)_\star$ gauge field, we replace the linear gauge potentials by smooth cutoff localizations; the resulting bounded self-adjoint perturbations define, for every $R > 0$, locally compact non-unital spectral triples. Finally, as $R\rightarrow\infty$, we prove strong resolvent convergence to a self-adjoint limiting operator, the closure of the formal minimally coupled operator. Thus the finite-cutoff spectral triples approximate, at the level of spectral triples, the limiting minimally coupled Dirac operator over a fixed nondegenerate $G_{\mathrm{NC}}$-background.

More profound than bulk topological order of quantum materials is only its unwinding via gapless excitations along boundaries of the sample. We recast this bulk-edge correspondence -- for the experimentally relevant case of fractional quantum Hall (FQH) systems -- in terms of effective relative higher gauge theory, controlled by choices of classifying fibrations. For FQH systems, we identify the complex Hopf fibration as classifying the bulk/boundary topological effects, and find that it yields a non-Lagrangian reconstruction of Floreanini-Jackiw/Wess-Zumino-Witten chiral edge currents. Remarkably, the resulting effective FQH higher gauge theory turns out to be "geometrically engineered" on M2/M5-branes probing A-type orbi-singularities in 11D supergravity, globally completed by flux-quantization in twisted equivariant differential (TED) Cohomotopy: Here the M-string ends of M2-branes on M5-branes engineer the FQH liquid's boundary. This geometric engineering on M-branes might naturally elucidate the curious combination of $W_\infty$-symmetry and of super-symmetry that is known to govern the collective excitations of FQH liquids at long wavelengths.

A giant atom is an artificial matter configuration whose spatial scale is comparable to the wavelength of the interacting electromagnetic wave, such that the usual electric-dipole approximation is no longer valid. As a consequence, certain quasi-direct scattering channels for the electromagnetic wave can arise. Given that the well-known input-output approach can only work for the usual point scattering configuration, wherein the electric-dipole approximation is well satisfied, here we develop a modified input-output approach, wherein an additional low-Q cavity channel is introduced, to treat the electromagnetic scattering problem of a giant atom. We demonstrate that, beyond the multiple coupling-point model used widely in recent publications, the present approach can well explain the Fano-type scattering spectra observed generically and extract certain physical parameters, including the energy dissipation parameter of a two-level giant atom and its coupling strength with the scattered electromagnetic wave. Consequently, we argue that various high-performance optical quantum devices, typically the giant-atom-based optical quantum switches, can be generated by engineering the Fano-type scatterings of giant atoms.

The coherent interaction between free electrons and optical near-fields enables the active modulation of electron wave packets, a mechanism central to photon-induced near-field electron microscopy (PINEM). While existing theories effectively describe these interactions at high kinetic energies, the growing interest in low-energy ultrafast electron microscopy demands frameworks that explicitly account for finite wave packet geometries and recoil effects. In this paper, we develop a rigorous 3D quantum scattering theory for electron wave packets interacting with time-periodic potentials, capturing the case of optical near-field interaction. By mapping the time-dependent dynamics into an extended Floquet space, we formally connect the modulation process to time-independent multi-channel scattering. We evaluate the resulting scattering amplitudes using both an exact R-matrix approach and a multi-channel eikonal approximation. The latter analytical approach recovers PINEM-like probabilities weighted by the wave packet's transverse profile. Application of the theory to an oscillating potential demonstrates the generation of distinct energy sidebands, revealing that the modulation strength is sensitive to the transverse focusing of the incident electron pulse, underlining the importance of a fully 3D treatment.

Optical interfaces that connect long-lived spin qubits to photons are a central requirement for quantum networking and distributed quantum information processing. Currently, solid-state atomic defects are leading candidates due to their inherent spin and optical coherence. Building on these advancements, synthetically tailored molecular systems represent a fundamental change in the field, utilizing precise atomic control and consistent bottom-up assembly. However, the lack of a robust spin-photon interface combining bright fluorescence, high spectral stability, and the persistent spin lifetimes inherent to ground-state systems has prohibited the detection of individual molecular qubits. Here we show that a triplet ground state carbene molecule, embedded within a structurally matched host crystal, functions as a robust spin-photon interface with single-molecule addressability. The system exhibits narrow zero-phonon lines, spectral stability over more than an hour, spin-selective optical transitions and single-molecule optically detected magnetic resonance. Coherent control yields millisecond-scale dynamical-decoupling coherence and tens-of-milliseconds spin relaxation at a temperature of 4.5 K. These results establish molecular qubits as a viable platform for single-emitter quantum optics while preserving the advantages of bottom-up chemical design and processable materials.

Set coherence is a basis-independent relational form of quantum coherence: a finite family of quantum states is set incoherent exactly when all its members are diagonal in one common basis. We determine how much low-order Bargmann data are needed to decide this property. For two states, second-order data are complete for qubits but fail for qutrits, while complete third-order data are sufficient for qutrits but fail already in dimension four. We then show that fourth-order, ordering-sensitive Bargmann invariants give the first universal pairwise criterion for set coherence. Applied to all unordered pairs, this criterion yields a complete test for arbitrary finite families. The result provides a low-order hierarchy connecting cyclic trace invariants with the noncommutativity that prevents a common incoherent basis.

Nonlinear properties of quantum states are essential to quantum information and many-body physics, but assessing them experimentally is challenging, as it typically requires multi-copy operations or a large number of measurement settings. To address this challenge, we develop a universal framework, collision-based nonlinear estimation (CBNE), for efficiently measuring nonlinear quantities of a quantum state $ρ$, such as the higher-order expectation value ${\rm tr}(Oρ^t)$ for some observable $O$, using single-copy randomized measurements. Strikingly, our protocol requires only a single measurement setting, provided that the system dimension is sufficiently large or a few ancillary qubits are available; this contrasts with the conventional expectation that multiple measurement bases are necessary for nonlinear estimation. In addition, CBNE is observable-independent at the experimental stage, which enables simultaneous estimation of multiple nonlinear functions. It further extends to broader tasks, including the estimation of principal component properties and partial-transpose moments of quantum states. Our results provide a practical and scalable route for measuring nonlinear state properties on near-term quantum devices.

We consider the task of constructing pseudorandom unitaries (PRUs) with scalable security, i.e. families in which the security parameter may vary independently of the dimension (or input bit-length). It is not known whether scalable PRUs can be constructed. In this work we show that if scalable PRUs can be constructed via the prevailing paradigm for analyzing PRUs, then there would be a positive solution to the Aaronson-Kuperberg unitary synthesis problem, a longstanding question in quantum complexity theory about whether implementing arbitrary unitaries can be efficiently reduced to computing a Boolean function. Specifically, we formalize the notion of ROM-PRUs, which are statistically secure PRUs in the random oracle model (ROM). All prior known constructions of cryptographically secure PRUs are based on a ROM-PRU construction. We prove novel connections between ROM-PRUs, approximate unitary designs, epsilon-nets over the unitary group, and the unitary synthesis problem. In particular, we prove that any unitary synthesis algorithm (and thus any ROM-PRU) must use a classical oracle with input length (2 - o(1)) log d bits, where d is the dimension of the unitary to be implemented. This bound rules out all existing candidates for scalable PRUs in the literature. Together, these connections indicate that ROM-PRUs provide a fruitful idealized model for studying pseudorandom unitaries.

We construct two families of regular hairy black holes within gravitational decoupling using a fixed exponential deformation profile for an effective tensor-vacuum sector. The first family is generated from a Bardeen-type seed and produces a de Sitter-like core. The second family is generated from a hollow seed with an asymptotically Minkowski core so that the central density vanishes and no de Sitter core is produced. For each branch we determine the critical deformation strengths separating horizonless, extremal, and two-horizon geometries in the static case, and we obtain the corresponding Kerr-like rotating extension by promoting the mass parameter to the deformed mass function. Representative parameter choices are used to illustrate the horizon structure and to verify the weak energy condition in the exterior region.

Using quadratic optomechanical coupling to prepare high-purity mechanical cat states is not feasible as its strength is several orders weaker than linear optomechanical coupling. Here, using only linear coupling in a multimode system, we achieve strong interaction between photons and two phonons, enabling the deterministic generation of high-purity multicomponent mechanical cats. Mediated by an auxiliary supermode, when other two optical supermodes satisfy the two-phonon resonance condition, the process whereby the annihilation of a high-frequency photon accompanied by the creation of a low-frequency photon and two phonons is strongly enhanced. Such resonant two-phonon process drives multiple rotations and interferences of mechanical coherent states, deterministically generating a multicomponent mechanical cat immune to both mechanical and optical losses. Our work provides an universal strategy for enhancing high-order phonon nonlinearities, paving the way for quantum state engineering, quantum precision measurement and fault-tolerant quantum computation.

Variational quantum eigensolvers fail before optimization begins when strong correlation splits the molecular energy landscape into competing basins and the initial state selects a non-ground-state basin. We introduce a geometry-conditioned preconditioner $\mathcal{P}_{\mathrm{eq}}:\mathbf{R}\mapsto\boldsymbolθ_0$ constrained by the $SE(3)$ covariance of the molecular Hamiltonian, so that nuclear geometry is mapped directly into circuit parameters in the correlated ground-state basin. This basin localization changes the relevant gradient statistics from concentration controlled to curvature controlled. In statevector benchmarks on six stretched molecules, $\mathcal{P}_{\mathrm{eq}}$ reduces Hartree--Fock initialization errors by factors of $38\times$--$6250\times$, reaches sub-mHa initialization in CO, LiH, and H$_8$, and places N$_2$, H$_2$O, and BeH$_2$ in the mHa-scale correlated basin. In disordered H$_{10}$ chains, equivariant basin targeting and stochastic escape reach unit success probability at fixed optimization budget. The procedure performs basin selection before the shot-limited quantum loop; the quantum circuit then refines correlation inside the selected basin.

It is well known that two parallel photon beams do not deflect under the effect of their energy-momentum tensor. In this work, we propose a novel model where two spatially separated Bose-Einstein condensates are outcoupled to create two parallel atom laser beams. We find out that apart from the classical deflection, a purely quantum gravity induced tidal deflection is observed which results in an irreducible noise in the geodesic separation of the two beams. Based on this simple but novel theoretical outcome, we propose an experimental model for detecting this quantum gravity induced standard deviation in the geodesic separation of the two parallel matter-wave beams.

It is known that there exist multi-prover interactive protocols ($\mathsf{MIP}$ protocols) for the complexity class $\mathsf{NEXP}$, succinct $\mathsf{MIP}$ protocols for $\mathsf{NP}$ and multi-prover interactive protocols with shared entanglement ($\mathsf{MIP}^\ast$ protocols) for $\mathsf{RE}$. This extraordinary power of multi-prover interactive proof systems comes from the assumption that provers do not communicate with each other during the protocols. If they are allowed to communicate freely, the setting is the same as in the single-prover case, and the computational power of the system becomes significantly weaker. In this paper, we investigate for the first time the setting where communication (i.e., leakage of information) between provers is allowed but bounded. We introduce two techniques to approach this question and show that multi-prover interactive proof systems are robust against some amount of leakage. Our first technique is based on parallel repetition theorems. We apply it to show that for any polynomial $p$, we can construct two-prover one-round $\mathsf{MIP}$ and $\mathsf{MIP}^\ast$ protocols for $\mathsf{NEXP}$ and $\mathsf{RE}$, respectively, that are robust against $p(n)$ bits of leakage. We further derive our second technique to convert any low-soundness PCP construction to a two-prover one-round $\mathsf{MIP}$ protocol for $\mathsf{NP}$ robust against leakage. We also discuss the relation between robustness against leakage in multi-prover interactive proof systems and the Sliding Scale Conjecture in the PCP literature.

We propose a quantum network consisting of optical waveguides in the linear regime for quantum state transfer. The circular topology of our network introduces novel functionalities that enable us to analytically identify the conditions under which perfect state transfer (PST) is achievable. We utilize the properties of the Fourier modes, in particular the zero Fourier modes, which provide a protected subspace for the efficient propagation of quantum states, resulting in PST to the diametrically opposite site in a network with any number of sites $N = 4n$. The coupling profiles in the photonic network modulate the number of zero-energy eigenmodes, with uniform couplings yielding more than evanescent ones, confirming that the expedition of observed PST originates from the collapse of the eigenvalue spectrum into three distinct eigenvalue blocks, including $N/2$ manifolds of zero Fourier modes. We investigate PST in both discrete- and continuous-variable input regimes, using single photon state, Schrödinger cat states, and two-mode squeezed vacuum state. Our findings apply to the engineering of quantum networks and photonic lattices, paving the way for applications in controlled routing in integrated quantum circuits.

We introduce two-parameter classes of exactly-solvable novel systems whose Hamiltonian operators could be represented by tridiagonal symmetric matrices in some orthonormal basis set. The associated wavefunction is written as point-wise convergent series in the basis elements. The expansion coefficients of the series are orthogonal polynomials in the energy that satisfy the resulting three-term recursion relation starting with two-parameter initial values. These polynomials contain all physical information about the system and they depend on the values of the two parameters. However, we could not write down the associated two-parameter potential function analytically but could realize them numerically for a given set of physical parameters. We give several illustrative examples of these systems with continuous and/or discrete energy spectra. Moreover, a curious phenomenon is observed where bound states and/or resonances are induced in a system with pure continuous spectrum (e.g., a free particle) if the two parameters in the initial values exceed certain critical limits.

We identify a class of finite quantum systems, namely, acyclic systems whose transition graph is a directed acyclic graph (DAG), for which the Born series collapses into an exact algebraic identity with finitely many terms and strictly zero truncation error. The sufficient condition is the nilpotency of the transfer operator T = G_0(E)V. If T^{m+1} = 0, then the exact solution of the Lippmann-Schwinger equation is the finite sum |psi> = sum_{k=0}^{m} T^k |phi>, with no condition on ||T||. We prove that the acyclicity of the transition graph implies the nilpotency of T (Theorem 19), and that the nilpotency index coincides with the maximal path length of the graph (Proposition 21). The main result (Theorem 23) concerns the four-level quantum system with diamond-graph structure. In this case, the transition amplitude toward the final state is A_4 = t_{42}t_{21} + t_{43}t_{31}, an exact algebraic identity encoding constructive interference, exact destructive interference (dark state formation), and partial interference. The first-order Born approximation predicts identically zero amplitude in all regimes, thereby failing quantitatively in 100% of the cases. The Born-SON framework additionally provides the exact full resolvent, the exact T-matrix, explicit error control in the quasi-nilpotent regime, and a scalar structural metric, the Born-SON depth, quantifying the intrinsic complexity of an acyclic quantum system.

We introduce the gravielectric (GE) and gravimagnetic (GM) fields in stationary spacetime using the Komar two-form and its dual. This opens the way to extend the Komar-Tomimatsu derivation of mass formulas to a more detailed picture in terms of the local lines of force. We show that Misner strings (MS) carry singular GE and GM fluxes connecting the horizon and the asymptotic zone. Moreover, MS are laterally transparent, so field lines can flow in and out of the bulk. This explains why the usual Komar mass integrals around the Misner strings in the Taub-NUT vacuum solution are negative: the pattern of field lines shows that they flow onto the string from the horizon, so it is necessary to calculate the incoming (positive) but not the outgoing Komar fluxes. This incoming flux is then turned back to the horizon through the Misner strings, realizing the closed circuit without sources. So Misner strings are massless empty tubes, but not rigid rods of negative mass. Similarly, GM field lines can connect positively and negatively charged regions of the horizon, generating, for example, the gravimagnetic dipole moment of the Kerr metric.

We analyze a quantum Maxwell demon operating a Szilard engine in free fall near a black hole horizon, where quantum information, thermodynamics, and spacetime causality intersect. The demon is modeled as a coherent two-level system, and the working substance is a single particle in a one-dimensional chamber crossing the event horizon. As the chamber crosses the horizon, the particle's Hilbert space splits into accessible and inaccessible sectors, leading to non-unitary reduced dynamics for an external demon due to tracing over interior degrees of freedom. We construct explicit measurement, expansion, and wall removal protocols for demons located outside or inside the horizon. Our results show that an external demon experiences degraded measurement correlations and reduced work extraction due to horizon-induced information loss, yet still obeys local thermodynamics and Landauer's principle. For an internal demon, the protocol reduces locally to the flat spacetime case, preserving the equivalence principle at the level of dynamics. While the equivalence principle holds dynamically, quantum information processing provides an operational signature of the horizon through reduced accessibility and irreversible open system behavior, clarifying how information, causality, and thermodynamics coexist in black-hole spacetimes.

Pure Lovelock black holes are geometrically more transparent than their Einstein counterparts, but they radiate far less. We compute scalar and higher-dimensional electromagnetic greybody factors and Hawking spectra on the critical branch $d=2N+2$, compare them with Schwarzschild--Tangherlini black holes at the same horizon radius $r_h$, and show that the smaller Hawking temperature overwhelms the enhanced transmission. In the benchmark $d=6$ case, the integrated scalar and electromagnetic powers are reduced by about $10^{-3}$ and $10^{-5}$, respectively. We also find a clean higher-curvature signature: as the Lovelock order $N$ grows, Hawking radiation becomes increasingly dominated by the scalar-type electromagnetic sector.

We investigate the divergent perturbative series of correlation functions for a massless, self-interacting scalar field in de Sitter space. First, we use our previously proposed method of autonomous equations to obtain finite time-dependent functions, and show that these functions approximate the time evolution of the correlation functions of the stochastic theory reasonably well. Second, we apply the technique of autonomous equations to the Borel-Le Roy transforms of correlation functions, and use solutions of these equations to perform Borel resummation. The results match the time evolution obtained in the stochastic picture substantially better. In addition, we propose an alternative method for extracting perturbative coefficients and provide a new derivation of our autonomous equation by truncating a system of Schwinger-Dyson-type differential equations.

Quantum systems with more than two levels $-$ so-called qudits $-$ offer increased computational density and reduced circuit complexity compared to qubit-based architectures, but achieving universal and scalable control remains challenging. We propose an all-optical scheme for universal qudit control in trapped neutral atoms in moderate to high magnetic fields, focusing on the fermionic isotope $^{173}$Yb ($I=5/2$). The strong hyperfine interaction in the $^3P_1$ manifold enables fast and selective Raman transitions between nuclear-spin states in the $^1S_0$ ground-state manifold using a single linearly polarized laser. For each neighboring transition in the qudit manifold, we identify a magic polarization angle that enables coherent, state-selective control while suppressing off-resonant excitations, with operation frequencies exceeding 100~kHz. Combined with phase-shift operations, this provides universal control of the full single-qudit space. We further discuss compatible two-qudit gates based on the Rydberg blockade mechanism, completing a universal gate set, and analyze state-selective readout schemes compatible with the proposed protocol. Our results identify $^{173}$Yb as a promising platform for high-fidelity, all-optical qudit-based quantum information processing.

A set of quantum states is said to be antidistinguishable if, upon being given a randomly chosen state, it is possible to identify a state that the system was definitively not prepared in. In this work, we begin with a study of quantum nonlocality within the framework of local state antidistinguishability (LSAD), and find that any ensemble of mutually orthogonal multipartite pure states is locally antidistinguishable. We then extend this paradigm by introducing the task of local state antimarking (LSAM), where a non-repetitive sequence from a known set of multipartite states is randomly selected and distributed to spatially separated parties who must identify at least one sequence that was not supplied using LOCC only. We present an ensemble of product states that is not globally antidistinguishable, but choosing states from it, without replacement, produces such sequences of states which are globally antidistinguishable but not locally-revealing a form of nonlocality without entanglement. Finally, we compare LSAD and LSAM with conclusive local state discrimination and conclusive local state marking. We demonstrate that no strict hierarchy exists between these paradigms: there exist product-state ensembles that permit one task while strictly forbidding the other, and vice versa.

Detection based on quantum principles such as entanglement has the capacity to achieve finessed levels of sensitivity, bringing transformative impacts to applications. In this study, we propose a rotation sensor using ultra-cold dipolar atoms trapped in a four-well configuration. The design, based on a simple population imbalance measurement to quantify rotation, profits from the property of superintegrability. The implementation of the measurement protocol achieves rotation-detection sensitivity beyond the Heisenberg limit. Our results spotlight superintegrability opportunities for advancing the field of quantum sensing.

We study lower bounds for the quantum relative entropy between a density matrix and its block-diagonal part. For a block matrix with diagonal blocks A,C>0 and off-diagonal coherence block B, we prove a lower bound expressed through the associated Bogoliubov--Kubo--Mori (BKM) kernel. The proof uses a midpoint estimate for the BKM Hessian along the affine interpolation between the matrix and its block-diagonal projection. The resulting estimate is genuinely noncommutative and retains information about the joint spectral structure of the diagonal blocks and the coherence term. As a consequence, under a spectral gap condition on A relative to C, we obtain an explicit logarithmic lower bound proportional to the squared Frobenius norm of the coherence block. The appearance of the BKM metric is natural in this setting because it coincides with the Hessian of quantum relative entropy.

Fault-tolerant quantum computing typically requires the transpilation of arbitrary quantum circuits into a finite, universal gate set, such as Clifford+T. As a baseline, Diagonal approximation can be used for synthesizing single-qubit Pauli rotations, yielding an approximating sequence with $T$-count that equals $3 \log_2(1/ε)$ for a target precision $ε$. Magnitude Approximation can reduce the $T$-count to only $1 \log_2(1/ε)$ by allowing large residual errors, which are rotations about orthogonal axes. Within a complete quantum circuit, these residual errors can then be absorbed into neighboring gates before they are approximated themselves. Determining the optimal allocation of approximation strategies within a large, multi-qubit circuit presents a significant combinatorial challenge. In this work, we present a linear-time algorithm that guarantees an optimal solution to this problem. We demonstrate that the issue of delegating Magnitude versus Diagonal approximation across a circuit maps formally to a classical 1D Ising model with a spatially varying field. By minimizing the energy of this Hamiltonian, we identify the optimal approximation configuration for each rotation without exponential overhead. Benchmarking our method against standard diagonal approximation on random quantum circuits, we observe an average reduction of 26\% in the total approximating circuit gate count, offering a significant efficiency gain for the implementation of quantum algorithms on near-term and fault-tolerant architectures.

We show that within the framework of the Friedmann cosmological model it is possible to derive general multimessenger consistency conditions, independent of the form of dark energy. We first derive a general relation for the curvature parameter, uniquely in terms of the gravitational wave (GW) and the electromagnetic wave (EMW) luminosity distances, which can be used to probe the curvature of the Universe with multimessenger astronomy, independently of the dark energy equation of state. We then use this to derive a general multimessenger consistency relation for the Friedmann model, independent of the dark energy model and of cosmological density parameters. As a special case, a multimessenger consistency test for the cosmological constant is also derived, independent of the curvature and matter density parameters.

Experiments aimed at quantifying the interface between quantum and classical physics necessarily require a high degree of isolation from the environment: wavefunction collapse and quantum gravity effects at laboratory scales are predicted to be very subtle. Ideally, such tests would be performed in a closed system at extremely low temperatures in order to rule out any external influence and thermal fluctuations. Cryogenic levitated macroscopic bodies are excellent candidates for an accurate laboratory approximation of such systems, as a tether to another body would violate the requirement for the system to be fully closed. Here we report a significant milestone on the way to a practically suitable approximation of such closed system. We have built a milligram-mass superconducting oscillator operating at millikelvin temperatures showing extremely low dissipation rate, with the oscillator ring-down time exceeding 110 hours. This corresponds to the resonance linewidth of less than 0.8 $μ$Hz. The experimental setup is highly tunable and is compatible with adiabatic nuclear demagnetisation, promising even lower temperatures and lower dissipation levels in the future. We demonstrate the capability of our device by measuring drag from $^3$He impurities in superfluid $^4$He at a level of $\sim10^{-8}$ with the drag force in the femtonewton range.

Within modified gravity, we study static spherically and axially symmetric self-gravitating non-Abelian monopoles in $SU(2)$ Yang-Mills-Higgs theory. By comparing these monopoles with those obtained in Einstein-Yang-Mills-Higgs theory, we identify the differences introduced by the modification of gravity and show that they can be quite significant for systems with strong Higgs self-coupling.

Quantum computing promises disruptive capabilities, yet its energy footprint has received far less attention than its asymptotic speedups. We present a first-order, full-system energy model for quantum computing in an high performance computing (HPC) context. The model separates costs common to NISQ and FTQC, such as system maintenance and classical processing, from regime-specific ones such as error mitigation for NISQ and error correction for FTQC. We instantiate the model on 96- and 100-qubit Heisenberg time-evolution simulations on IBM Eagle r3 and a representative VQE workload, and sketch the FTQC energy pipeline. We find that NISQ energy is dominated by the QEM sampling multiplier, while FTQC cost shifts to physical-qubit overhead set by the code distance and magic states. Our model provides actionable insights into the energy consumption of both NISQ and FTQC workloads, and paves the way toward energy-efficient quantum advantage.

Many quantum computing workflows manipulate long lists of Pauli strings. A basic classical subroutine involves taking $m$ Pauli strings on $n$ qubits, each of weight bounded by a constant, to determine if they are pairwise commuting, identify any counterexamples, or calculate the exact number of anticommuting unordered pairs. The standard general-purpose route represents Pauli strings in binary symplectic form and checks pairs in $O(m^2)$ time. Here, we provide an $O(m)$ algorithm for the bounded locality regime. It maintains counts of all labeled subpatterns of previously inserted strings and answers each new string query by a subset zeta identity. Our algorithm is particularly useful for processing large collections of Pauli strings within the bounded locality regime.

Contextuality is considered as one of the most distinctive features of nonclassical systems. Here, we show that a Spekkens contextual system (which previous work has shown is a necessary condition for nonclassicality) formed of an odd-dimensional stabiliser system plus a magic state becomes noncontextual (a sufficient condition for classicality) under the action of a depolarising channel after a certain decoherence threshold. We show also that some quasiprobability representations are more effective than others in witnessing this transition from contextuality to noncontextuality. Given previous work has shown that magic states and Spekkens contextuality are both necessary for universal quantum computation, this result helps us understand the relationship between decoherence, Spekkens' generalised contextuality, and quantum advantage.

Randomness extraction is indispensable for quantum random number generators, serving to eliminate bias and potential information leakage from raw measurement data. Conventional extractors operate in a block-wise fashion, requiring the complete accumulation of raw data before processing. To circumvent the latency and buffering overheads that hinder real-time random number generation, recent work introduced a stream-cipher implementation for the randomness extractor based on the Toeplitz matrix hashing. In this work, we generalize this stream-processing paradigm to the broader family of randomness extractors based on (almost dual) universal$_2$ random hashing. Specifically, we shift the computational burden from a time-consuming block-wise post-processing stage into an offline pre-processing stage that generates a pseudo-random mask. This allows the raw data to be processed by the mask on the fly using a simple bitwise exclusive-OR operation. Crucially, we prove that this stream implementation strictly preserves the security guarantees of the original block-wise protocols. We detail the transformation of three typical constructions -- based on standard Toeplitz, circulant, and modified Toeplitz matrices -- from block to stream implementations, and benchmark their practical performance using realistic quantum experimental data. We anticipate our framework will enhance the efficiency of real-time quantum cryptographic systems.

Quantum batteries have recently emerged as promising candidates for microscopic energy-storage technologies exploiting uniquely quantum mechanical effects. In this work, we introduce the concept of a quantum capacitor, a quantum device designed for reversible and ultrafast energy storage and release through coherent quantum polarization. Unlike conventional quantum batteries, whose primary focus is maximizing extractable work, the proposed quantum capacitor emphasizes reactive energy accumulation, coherence-assisted charging, and rapid discharge dynamics analogous to classical capacitive systems. We formulate a minimal theoretical framework based on a driven two-level system and define a quantum capacitance associated with the susceptibility of stored energy to external driving. We further discuss charging dynamics, coherent oscillatory behavior, and the role of environmental decoherence. Our proposal establishes a bridge between quantum thermodynamics, quantum coherence theory, and nanoscale energy-storage architectures.

We study quasinormal modes, greybody factors, and the absorption cross section of a massive scalar field in the asymptotically flat parity-symmetric beyond-Horndeski black-hole background. The scalar mass raises the asymptotic level of the effective potential and can eliminate its barrier peak, thereby changing both the ringing spectrum and the scattering characteristics relative to the massless case. Using Padé-improved high-order WKB calculations together with time-domain evolution, we find that the damping rate decreases strongly as the field mass increases, indicating the approach to long-lived quasi-resonant states for representative parameter families. At the same time, in the large-mass regime these weakly damped modes become progressively harder to isolate in the time domain, because the oscillatory massive tails are expected to dominate on the Koyama--Tomimatsu scale $μ_s t\gg μ_s M$, which is comparatively early when $M=1$ and $μ_s$ is not small. The time-domain profiles also exhibit the transition from quasinormal ringing to an oscillatory late-time tail. Interpreting the same effective potential semiclassically, we show that increasing the scalar mass suppresses low-frequency transmission and shifts the onset of efficient absorption to higher frequencies, while larger deviations from the Schwarzschild limit enhance the absorption cross section. These results show that the competition between long-lived modes and rapidly dominant massive tails makes the massive sector an especially subtle and sensitive probe of the interplay between field mass and geometric deformation in this class of black holes.

We consider the Clauser-Horn (CH) inequality for a qubit-qutrit system. We derive the necessary and sufficient conditions for the violation of the inequality as well as some sufficient conditions. Remarkably, we demonstrate the importance of local parameters in violation of the inequality. In other words, there are some families of mixed states violating the inequality for which the correlation part alone is useless in the Bell-CH test.

The viability of traversable wormholes as exotic compact objects requires the identification of signatures that distinguish them from other compact objects. Given recent advances in observing rotating black hole signatures, identifying characteristic imprints that reflect the absence of an event horizon and the presence of a throat structure is of considerable significance. Motivated by this, in the present work, we analyze the propagation of a massless scalar field in a rotating traversable wormhole spacetime described by Teo's class of solutions. We numerically compute the transmission (greybody) factor and the corresponding absorption spectrum across a broad range of frequencies. The spectrum exhibits a series of sharp peaks in the amplitudes, which we identify as Breit-Wigner-type resonances. The emergence of such peaks can be attributed to the scalar modes temporarily trapped within the potential well formed by barriers on either side of the throat. These resonant features, previously identified in static wormhole backgrounds, persist in the rotating case. In particular, for Teo's class of wormholes, we find that rotation enhances the strength of the resonances. Overall, our results demonstrate the role of rotation in shaping the resonance effect and indicate these features as characteristic signatures of wormhole geometries.

Loopy tensor networks exhibit internal correlations that often render their compression inefficient. We show that even local bond optimization can more effectively exploit locally available information about relevant loop correlations. By cutting a bond, we define a set of states whose linear dependence can be identified through a zero mode of the states' metric tensor and used to truncate the bond dimension. In the absence of an exact zero mode, a linear combination of a small number of the lowest modes can instead be optimized to provide the optimal approximation to a zero mode. The truncation does not require prior gauge fixing. The method is applied to the two-dimensional finite-temperature $Z_2$ lattice gauge theory, whose thermal-state purification is represented by an infinite projected entangled-pair state (iPEPS).

Fusion-based quantum computing (FBQC) relies on a set of small, typically photonic, resource states that are fused together through Bell state measurements. The main bottleneck of FBQC is the low rate of generating the resource states, which stems from the probabilistic nature of photonic fusion gates. Previous work introduced a general algorithm for constructing circuits that deterministically generate photonic resource states from a minimal number of quantum emitters for a specified photon emission ordering. However, finding the minimal number of emitters and CNOT gates across all possible orderings is an NP-hard problem. Here, we exploit the symmetries present in FBQC resource states to dramatically simplify this optimization problem. We find that logically encoded 24-photon FBQC resource states can be produced using as few as 3 emitters and 11 CNOTs.

We develop a microscopic theory for how slow Liouvillian sectors are selected in an open correlated lattice. The starting point is not a postulated non-Hermitian band, but a local interacting resonance between an on-site doublon and a branch-resolved nearest-neighbor bond. This resonance defines a composite shell orbital whose doublon weight controls reservoir visibility and whose mixed doublon-bond character controls shell mobility. Projecting the microscopic hopping onto the selected shell yields a branch-selective dimerized channel. In the dilute regime, a boundary doublon-loss channel yields an exponentially slow edge-memory pole through a Zeno-type return. At the shell-critical point, the edge pole is replaced by a near-zero standing-wave doublet with an algebraic coherent spacing. At finite shell filling, the same local shell becomes density dressed. A number-conserving phase-locking jump removes a bright mismatch sector, leaving defects as the asymptotic slow variables and producing a diffusive finite-size gap. We derive the local shell, the projected branch topology, the edge-memory law, the shell-critical doublet, the density-dressed shell Hamiltonian, and the defect generator within one Schur-projection framework. The resulting mechanism identifies the reservoir-engineered fast block as the selector of the observable slow sector, while the microscopic parent shell remains fixed.

Modeling extreme-mass-ratio inspirals hinges on the accurate and efficient computation of gravitational-wave fluxes from generic Kerr orbits. Conventional frequency-domain techniques are often limited by costly auxiliary parameter searches and numerical instabilities in the strong-field or high-frequency regimes. We address these challenges by reformulating both the angular and radial Teukolsky equations in terms of confluent Heun functions. Employing a hybrid analytic continuation algorithm to compute the connection coefficients eliminates the dependence on auxiliary parameters, directly yielding globally convergent solutions and scattering amplitudes. To resolve the highly oscillatory source integrands for generic orbits, we implement an adaptive bi-power mapping quadrature. Comprehensive benchmarks under standard double-precision arithmetic demonstrate that, for the total radiative flux summed over 168 low-order modes, our method achieves relative errors of order $10^{-11}$, with computational costs typically reduced by factors of 3--13 compared to the state-of-the-art GeneralizedSasakiNakamura. jl and pybhpt packages. Notably, for highly oscillatory high-order modes, our framework achieves a speedup of up to 60 times compared to specialized oscillatory integrators like GeneralizedSasakiNakamura. jl. These demonstrated gains in precision and efficiency establish the framework as a robust tool for strong-field perturbation theory, providing the numerical foundation for high-order self-force calculations and rapid, high-precision waveform generation.

We investigate a Dirac-type equation in (2+1) dimensions modified by Lifshitz spatial derivatives with dynamical exponent $z=2$, focusing on the spectral properties of bound states under radial confinement. Analytical solutions are obtained for constant backgrounds, hard-wall confinement, and harmonic potentials, while logarithmic confinement is treated numerically via the Numerov method and complemented by a semiclassical WKB analysis. The resulting spectra exhibit characteristic scaling laws governed by the Lifshitz parameter $b$, including $E - M \propto b/R_0^2$ for hard-wall confinement, $E - M \propto \sqrt{2b}\,ω$ for harmonic trapping, and $E - M \sim α\ln\sqrt{b}$ in the semiclassical regime of logarithmic confinement. These results provide a consistent characterization of how higher-order spatial derivatives modify bound-state spectra in two-dimensional Dirac systems and may be relevant for effective descriptions of materials with quadratic low-energy dispersion, such as bilayer graphene and related anisotropic 2D systems.

A direct coupling between the inflaton and Standard Model gluons can dynamically raise the QCD confinement scale during inflation, making the axion temporarily heavy and suppressing axion isocurvature perturbations. As inflation proceeds, the confinement scale relaxes, the axion becomes light, and late-time de Sitter fluctuations can generate the observed dark matter abundance. We analyze this mechanism without specifying an inflationary potential, instead parametrizing the background by $ε(N) \propto 1/N^p$, where $N$ is the number of $e$-folds before the end of inflation. The single parameter $p$ distinguishes monomial models ($p=1$), standard plateau models ($p=2$), and ultra-flat plateau or hilltop-like models ($p\ge 3$). We (analytically) show that the mechanism selects plateau-like ($p\ge 2$) inflation: monomial models generically cause the confinement scale to grow too rapidly, while plateau models keep the QCD sector under perturbative control. In the minimal scenario, reheating occurs through the same inflaton-gluon coupling, and viable axion dark matter production is obtained when deconfinement occurs after the CMB window. The early-confinement sector also shifts the scalar spectral index to larger, bluer values, opening viable parameter space for models otherwise disfavored by CMB data.

The gravitational path integral produces an asymptotic expansion in $G_N$, a fact which is puzzling in the case of observables that are expected to fluctuate wildly. Wormholes appear to compute ensemble averages of functions of such observables, though in typical constructions of AdS/CFT, there are no parameters to average over except, in some examples, a single integer $N$. We introduce a procedure that we call ``Mellin averaging'' to define a sort of asymptotic average of a function of $N$. We argue that Mellin averaging over $N$ may suffice to reproduce the apparent randomness seen in wormhole physics, provided that the dual theory admits an analytic continuation in $N$ and the relevant observables fluctuate on superpolynomially small scales in $N$. As a test case, we consider the spectral form factor in the regime where the double cone is believed to dominate the gravitational path integral and compare to a random matrix theory in which $N$ behaves as a continuous variable. We also describe some toy models of analytic continuation in $N$: a qubit model that can be analytically continued in $N$, and an explicit construction of a deterministic function of $N$ that simulates a sequence of independent draws from a Gaussian ensemble.

High-temperature dimensional reduction provides a systematic effective field theory framework for studying finite-temperature thermodynamics and cosmological phase transitions. While the matching of super-renormalizable operators in the resulting three-dimensional effective theories is well established, the matching of higher-dimensional operators has recently been reinvigorated. These operators become phenomenologically relevant in strong first-order phase transitions where they quantify the convergence of the high-temperature expansion. This work automates the matching of generic three-dimensional dimension-five and -six operators for arbitrary models containing scalars, fermions, and gauge fields, implemented as an extension of the Mathematica package DRalgo. We present the operator basis, the matching procedure, and explicit examples including a scalar-Yukawa model, hot QCD, and the full Standard Model up to dimension six, covering operators mixing the strong and electroweak sectors as well as parity-violating contributions. Redundant operators, gauge dependence, and the corresponding field redefinitions are discussed in detail. The code and example model files are publicly available at https://github.com/DR-algo/DRalgo.

Neutrino oscillation experiments present anomalous results across a vast range of baselines and energies. Here we show that a 3+1 scenario in which sterile neutrinos feel a novel matter potential $V_s$ proportional to background density of ordinary or (asymmetric) dark matter is able to explain several anomalies. At low-energies ($E\lesssim$ 1 TeV) the model behaves as an effective 3-flavor NSI-like scheme among active flavors and eliminates the tension between the two LBL experiments NOvA and T2K provided that the potential is negative and the two sterile mixing angles $θ_{14}$ and $θ_{24}$ are non-zero. A further indication in favor of a negative non-zero potential comes from the anomalous excess of $ν_e$-like events observed in Super-Kamiokande atmospheric neutrinos, which, in the new scenario is explained by a modification of the 3-flavor resonance at few GeV. A high energies ($E\gtrsim $ 1 TeV) the new framework reveals its 4-flavor nature and produces a resonant behavior at $E \simeq$ 10 TeV as hinted at by IceCube. We identify an irreducible 3-level dynamics generating a new resonance in the $(ν_e, ν_μ)$ sector intertwined with two conventional resonances in the $(ν_e, ν_s$) and $(ν_μ, ν_s)$ systems. The novel amplification mechanism manifests with the emergence of effective mixing angles in matter ($θ_{12}^m$ or $θ_{13}^m$) involving active neutrinos. The scenario requires values of $f = V_s/|V_{NC}| \sim -20 $, $Δm^2_{41} \sim 60 $ eV$^2$, $|U_{e4}|^2\simeq \sin^2θ_{14} \simeq 0.01-0.03$ and $|U_{\mu4}|^2 \simeq \sin^2θ_{24}\simeq 10^{-4}-10^{-3}$. Such a very small size of $|U_{\mu4}|^2$ eliminates the tension between IceCube and the other $ν_μ$ disappearance searches. The model can be directly probed by KATRIN, which is very sensitive to the electron-sterile neutrino admixture in the region of high $Δm^2_{41}$.

In this paper, we investigate how AdS scalar propagators are represented in the celestial basis. Starting from the standard bulk-to-boundary propagator in Euclidean AdS space, we express the propagator in a Schwinger parametrization and construct the corresponding boundary-to-boundary propagator. We then transform the resulting propagators to the celestial basis using conformal primary wavefunctions for both massless and massive scalar fields. For the massless case, the celestial propagator reduces to an effectively two-dimensional boundary-to-boundary object on the celestial sphere dependent on the AdS/CFT conformal dimension $Δ$. For the massive case, the celestial propagator exhibits a nontrivial kernel involving modified Bessel functions, closely resembling the momentum-space radial structure of AdS bulk-to-boundary propagators. The results suggest a structural translation from AdS propagators and celestial propagators.

A search for new physics in the production of three massive gauge bosons (VVV, where V is a W or Z boson) is presented. The event selection is most effective in the Lorentz-boosted regime in which all three bosons have a transverse momentum ($p_\mathrm{T}$) above 200 GeV. Standard model (SM) processes contribute few events in this regime. When a boosted W or Z boson decays hadronically, the decay products tend to form a large-radius jet with substructure that reflects the presence of two quarks from the decay; such jets are called V-tagged jets. Special techniques to reconstruct and select V-tagged jets are applied. Events are categorized according to the number and kinematic features of charged leptons and V-tagged jets. Event yields are obtained in bins of a suitable kinematic variable such as the scalar $p_\mathrm{T}$ sum of the reconstructed objects in the event. No excess over SM expectations is observed. Bounds are placed on Wilson coefficients for a set of mass dimension-6 and -8 operators in the framework of SM effective field theory. The two most stringent bounds placed by this analysis are $-$0.13 $\lt$ $c_\mathrm{W}/Λ^2$ $\lt$ 0.12 TeV$^{-2}$ and $-$0.24 $\lt$ $c_\mathrm{Hq3}/Λ^2$ $\lt$ 0.21 TeV$^{-2}$ at 95% CL, where $c_\mathrm{W}$ and $c_\mathrm{Hq3}$ are dimension-6 Wilson coefficients in the Warsaw basis and $Λ$ is the mass scale of new physics.

We apply the Worldvolume Hybrid Monte Carlo (WV-HMC) method [arXiv:2012.08468] to the two-dimensional Hubbard model, which is known to suffer from a severe sign problem when the system is doped (away from half filling). We show that the method predicts physical observables with controlled statistical errors on an $8 \times 8$ lattice at temperature $T/t = 1/6.4 \approx 0.156$ and interaction strength $U/t = 8.0$ ($t$ is the hopping amplitude), for which the standard determinant quantum Monte Carlo fails.

Inspired by the latest BESIII measurement of the $Λ(1520)\toγΣ^0$ radiative decay, we systematically study the decays $Λ(1520)\toγΛ(Σ^0)$ within the chiral unitary approach, where the $Λ(1520)$ is treated as a dynamically generated resonance from meson-baryon interactions. Compared with previous chiral unitary studies, we adopt dimensional regularization for $S$-wave loop integrals to preserve gauge invariance and, for the first time, include Feynman diagrams with photon coupling to intermediate baryons. Our calculated partial decay width $Γ(Λ(1520)\toγΣ^0)$ agrees well with the new BESIII data, whereas the predicted $Γ(Λ(1520)\toγΛ)$ is considerably smaller than the CLAS experimental result. By comparing our results with predictions from various quark models, we discuss the internal nature of the $Λ(1520)$ resonance, highlight its complex component structure, and stress the need for more refined theoretical frameworks and further experimental measurements.

$D$ meson decays into neutral kaons involve both Cabibbo-favored and doubly Cabibbo-suppressed amplitudes as well as final-state kaon mixing, providing abundant sources of CP violation. In this work, we analyze CP asymmetries in the $D\to K^0_{S,L}P$ and $D\to K^0_{S,L}V$ decays, where $P$ and $V$ denote pseudoscalar and vector mesons respectively. The formulas of the time-dependent and time-integrated CP asymmetries in these modes are derived, in which the $D^0-\overline D^0$ mixing effects and the $K^0_L$ modes are considered for the first time. The hadronic parameters that determine CP asymmetries are extracted by the global fit of branching fractions within the topological diagram approach. A significant result is that the tension between theoretical predictions and experimental data for the $K_S^0-K_L^0$ asymmetries in $D^0\to K_{S,L}^0ω$ and $D^0\to K_{S,L}^0φ$ modes is mitigated. The CP-violating effects arising from the interference between Cabibbo-favored and doubly Cabibbo-suppressed amplitudes with neutral kaon mixing could reach to $\mathcal{O}(10^{-3})$ order in the $D^+\to K^0_Sπ^+$, $D^+_s\to K^0_SK^+$, $D^0\to K^0_Sρ^0$, and $D^0\to K^0_Sφ$ modes. The difference between the CP asymmetries in the $D^+\to K^0_Sπ^+$ and $D^+_s\to K^0_SK^+$ modes is available on LHCb and Belle II in the near future.

We perform a systematic study of two-meson form factors of the scalar, vector, and anti-symmetric tensor types within the framework of the $U(3)$ resonance chiral theory. The complete perturbative form factors in both the strangeness-conserving and strangeness-changing channels are calculated by incorporating one-loop light-flavor pseudoscalar meson contributions and tree-level resonance exchanges. With these newly calculated chiral results, we construct the corresponding unitarized form factors by incorporating meson-meson final-state interactions. The parameter values obtained in previous meson-meson scattering studies are then exploited to predict the corresponding form factors. Different types of form factors are found to exhibit rather distinct resonance structures across channels.

Optimal observables provide statistically powerful probes of small deformations from a reference theory, but in realistic collider measurements they are rarely available in compact analytic form. We show that interpretable event-level observables can be discovered by AI-driven symbolic evolution using score information from matrix-element reweighting as the statistical target. Focusing on the CP-sensitive interaction $HZ_{μν}\tilde Z^{μν}$, we study two complementary realizations of the same coupling structure: associated production $e^+e^-\to Z(\to μ^-μ^+)H$ and the decay channel $pp\to H\to ZZ^*\to e^-e^+μ^-μ^+$. The learned observables retain substantially more local Fisher information than standard angular baselines while remaining compact analytic functions. In both cases, the discovered expressions recover characteristic helicity-interference harmonics. In associated production these harmonics are supplemented by laboratory-frame asymmetry mappings, while in four-lepton decay the robust component is the angular kernel, with the mass-ratio factor serving as a bounded representative prefactor. These results recast optimal-observable design as a symbolic discovery problem and provide a transparent route to information-efficient, interpretable probes of collider interference.

We calculate the next-to-next-to-leading order (NNLO) QED corrections to the $C$-odd part of the differential cross section of the $e^+e^-\toμ^+μ^-$ process. This part contributes to the angular and forward-backward asymmetry. Together with our earlier paper [10.1007/JHEP08(2025)118], this work completes the analytical calculation of $e^+e^-\toμ^+μ^-$ differential cross section at NNLO.

We show that flying focus fields can be obtained from complex conformal transformation of plane waves, and that solutions of the massless wave equation in the so-obtained fields are, correspondingly, conformal transformations of the Volkov solutions. This leads to the result that photon emission amplitudes in a totally depleting flying focus beam may be computed directly from the corresponding plane wave amplitudes by taking a simple Gaussian average over certain momentum variables. In effect, this gives a way of introducing focussing effects into strong-field QED calculations `for free'. The extension of these results to scattering amplitudes including only partial depletion is discussed and some first results presented in the anti-self-dual limit.

The NA61/SHINE experiment at the CERN SPS is a multipurpose fixed-target spectrometer for charged and neutral hadron measurements. Its research program includes studies of strong interactions as well as reference measurements for neutrino and cosmic-ray physics. One major goal of its strong interaction program is to determine the existence and pinpoint the location of the QCD critical point, an object of both experimental and theoretical studies. This contribution will summarize the current status of NA61/SHINE critical point searches in nucleus-nucleus collisions, in the collision energy range $\sqrt{s_{NN}} = 5-17$~GeV. The review includes studies of fluctuations of net-electric charge, femtoscopy analysis of $π-π$ pairs, as well as intermittency of protons and negatively charged hadrons. No clear indication of the critical point has been observed so far. Finally, we report on the development of novel methods aimed at solving the long-standing problem of bin-by-bin correlations in experimental intermittency analysis, and for a more accurate handling of systematics and uncertainties.

We provide a comprehensive overview of the current status of higher-codimension defect systems. We review the holographic description and field theoretic properties of codimension-2 defects within the framework of defect Conformal Field Theories (dCFTs). Starting from the well-established classification of $1/2$-BPS supersymmetric defects, we examine their realisation through probe branes and bubbling supergravity geometries. Special emphasis is placed on recent developments involving non-supersymmetric D3/D5 configurations and their holographic interpolations. We discuss the calculation of important physical observables, such as one-point functions of the stress-energy tensor and chiral primary operators, across both weak and strong coupling regimes. The agreement of the results in the two regimes exhibits the full power of the holographic principle. This is a proceedings contribution to the Athens Workshop in Theoretical Physics: 10th Anniversary, held at the National and Kapodistrian University of Athens on December 17-19 2025.

Motivated by the increasing precision of neutrino oscillation data, we study the corrections to the TM$_2$ neutrino mixing framework, emanating from $(1,2)$ sector of the charged lepton, for both the standard LMA and dark-LMA solutions. We employ the Wolfenstein parameterization of the charged-lepton mixing matrix, characterized by two additional parameters $(λ,δ)$, which effectively reconciles the TM$_2$ neutrino-mixing predictions with current oscillation data. For the LMA solution, the allowed ranges are $0.1 \lesssim λ\lesssim 0.33$ and $δ\in (20^\circ\!-\!90^\circ)\oplus(270^\circ\!-\!340^\circ)$, while the dark-LMA case requires $λ>0.24$ and $125^\circ<δ<235^\circ$. Interestingly, for LMA case, the upper bound $λ\le 0.33$ is found to be dictated by the atmospheric mixing angle $θ_{23}$. The model predicts sizeable CP violation, with $|J_{CP}|$ reaching values as large as $0.13$. We, also, analyze the effective Majorana mass parameter $m_{ee}$ relevant for neutrinoless double beta decay. The inverted hierarchy region lies within the sensitivity of future experiments for both solutions, whereas only part of the normal hierarchy region can be tested.

In this article we consider a $\mathbb{Z}_2$-odd $SU(2)$ quartet with hypercharge $Y = +\frac{1}{2}$ as an extension of the Standard Model whose scalar potential which introduces three additional Higgs portal and two self-couplings. We first investigate the possibility of having Landau poles (LPs) in one-loop and Fixed Points (FPs) in two-loop $β$-functions of the Higgs quartic couplings. The role of portal and self-couplings with and without residual phases is extensively investigated in obtaining the Fixed Point at two-loop. The model also can provide us with $\mathbb{Z}_2$-odd neutral scalar as the possible dark matter. However not always the lightest state corresponds to the neutral states, and we look into one-loop mass correction for an enhanced dark matter parameter space. This also gives rise to interesting phenomenology of the next-to-lightest particle which can be singly charged, doubly charged or neutral scalar. We performed a detailed study of dark matter relic calculation with one-loop masses and with direct detection bounds, and found out that, unlike the minimal inert extensions of $SU(2)$ multiplets, here the dark matter mass can go beyond 15 TeV without crossing the observed relic. Finally, we summarized with a few benchmark points for future studies.

A three-dimensional $\mathcal{N}=4$ gauge theory is constructed whose Higgs branch realizes the affine closure of the cotangent bundle of the minimal nilpotent orbit of $\mathfrak{sl}_n$. This space is a symplectic singularity recently identified by Fu and Liu as a $\mathrm{U}(1)$ hyperkähler quotient of the closure of the minimal nilpotent orbit of $\mathfrak{so}_{2n+2}$. The theory arises by gauging an $\mathrm{SO}(2)\cong\mathrm{U}(1)$ subgroup of the flavour symmetry of $\mathrm{SU}(2)$ SQCD with $n+1$ flavours. The Hilbert series is computed and the stratification is determined. A non-simply laced magnetic quiver is proposed whose Coulomb branch reproduces the same singularity. Evidence is thereby provided for a mirror pair involving a non-simply laced quiver, further tested through quiver subtraction and Hasse diagram inversion. A related $\mathbb{Z}_2$ quotient of the magnetic lattice is also analysed, and the exceptional behaviour in the case $n=2$, where $A_1 \cong C_1$, is explained. This construction provides a concrete example in which the Higgs-branch structure associated with a non-simply laced magnetic quiver can be inferred and validated through its mirror dual.

Using the multi-index approach to regularity structures due to F. Otto et al., we construct a regularity structure and a model for it associated to the stochastic Langevin equation for the 3D Euclidean Yang-Mills functional. For the model we also obtain global stochastic and global pointwise weighted Besov type estimates which hold almost surely. The model is defined as a limit of a sequence of smooth models introduced with the help of a mollified noise. When the mollification is removed the sequence converges in a certain topology defined with the help of the stochastic estimates. To obtain these results we develop the multi-index approach for systems of equations with vector-valued white noises. This project is motivated by the problem for constructing 3D Euclidean Yang-Mills measure and by the earlier results of the author on the related problem of canonical quantization of the Yang-Mills field on the Minkowski space.

Dark matter experiments are rare event search experiments that require zero background environment over very long exposures. To achieve this condition, a detailed simulation of detector geometry and experimental setup is required before the experiment is executed. Simulation plays a significant role in detector design and also provides a cost-effective and risk-free approach for predicting outcomes before real world experimentation. The present simulation work is focused on neutron background reduction for a dark matter direct detection experiment in India, the Indian Dark matter search Experiment (InDEx). The FLUKA and FLAIR simulation tools have been used throughout the simulation process. The experimental and simulation results available in the literature are being reproduced using FLUKA for validation purposes. The calibration and InDEx experiment are simulated, and the results are compared against the experimental results. For neutron background reduction in future experiments, the use of high density polyethylene (HDPE) is suggested and a shielding design using HDPE is presented. The results show that shielding reduces detector event rates by two orders of magnitude compared to the prior InDEx experiment without shielding.

Black-hole formation is expected, via holography, to correspond to thermalization in the boundary theory. For open quantum systems, an initial pure state generically evolves into a mixed state irreversibly, suggesting that horizon formation in the bulk should arise. In this paper, we extend the holographic Lindblad prescription to a non-Markovian setting and apply it to JT gravity coupled to a scalar field. Using numerical simulations in the semiclassical and high-temperature regime, we demonstrate the dynamical formation of black holes.

I derive the regularized formula for glue scalar density (gluon condensate) in terms of Dirac spectral density [arXiv:2509.03509], and elaborate on its uses and meaning. Particular attention is given to understanding of what this new formula reveals about the relation between glue and quark scalar densities, how it relates to IR phase, how it clarifies the distinction between anomalous and spontaneous ways of breaking symmetries, and what it says about the relation between UV and IR in QCD.

We study the impact of symmetry energy ($S$), hyperons, and dark matter (DM) on structural and oscillatory properties of neutron stars (NSs). Uncertainty from hadronic equation of state for NSs is considered with 15 relativistic mean field models having slope parameter ($L_0$) of $S$ in range $40-120$ MeV. DM admixed NSs (DMANSs) are described with feeble interaction between light DM fermions ($χ$) with hadronic matter in the presence of hyperons via scalar ($η$) and vector ($ξ$) dark mediators. The masses $m_χ$, $m_η$ and $m_ξ$ are related by self-interaction constraints from bullet cluster. DM self-interaction couplings are related to $m_χ$ by relic density constraint. The DM density is taken as an exponential function of baryon density with a free parameter $α$. Uncertainty from DM model is incorporated by exploring the dependence on $m_χ$ and $α$. Several DM search experiments have almost ruled out the existence of massive DM ($\gtrsim$ GeV). Lately, pursuit for sub-GeV DM has attracted significant attention. Therefore, we consider $m_χ<$ 1 GeV and $α\leq$ 0.1 such that the contribution of DM to the total mass of the DMANSs is $<10\%$. Comparing our results with various astrophysical constraints, we find that the HESS J1731-347 and GW170817 data are very important in determining the presence of light DM in NSs in moderate amount, relevant in the range $L_0\lesssim$ 58 MeV. Employing models of DMANSs that satisfy several observational data, we infer with Bayesian analysis, the likely ranges of $m_χ$ and $α$ are almost independent of the underlying hadronic model within 40 MeV $\lesssim$ $L_0$ $<$ 58 MeV. In the absence of DM and with the most probable values of $m_χ$ and $α$ obtained from the Bayesian inference, we calculate the frequencies of non-radial $f$- and $p_1$-modes oscillation of NSs/DMANSs.

We investigate a Kapitza-inspired mechanism in which rapid oscillations in the heavy-quark interaction generate an effective short-range repulsive term in the diquark--antidiquark potential. The resulting $1/r^{4}$ contribution prevents collapse at short distances and produces a stable minimum in the effective potential. Within a diquark--antidiquark picture, we construct a modified Cornell-type potential and analyze the spectrum of heavy tetraquarks using a Gaussian variational method. We compute the binding energies, wave functions, radii, and mass spectra of charm and bottom tetraquarks, including the $X(3872)$, $T_{bb}$, and fully heavy $bb\bar{b}\bar{b}$ states. The model reproduces the mass of the $X(3872)$ and predicts a deeply bound $T_{bb}$ state consistent with lattice QCD. The fully heavy $bb\bar{b}\bar{b}$ mass also agrees with recent lattice determinations. Our results indicate that the Kapitza mechanism provides a natural and robust stabilization effect in multiquark systems and offers a unified description of molecular-like and compact tetraquark configurations.

We present a complete calculation of the one-loop self-energies for all fields in the linear sigma model coupled to quarks at finite temperature and in the presence of a uniform magnetic field. The analysis consistently incorporates thermal and magnetic effects for both neutral and charged degrees of freedom, providing a unified framework valid for arbitrary values of the temperature and the field strength. The computation is performed using the Matsubara formalism to account for finite temperature effects and the Schwinger proper-time representation for charged propagators in a magnetic background. Special attention is given to loop contributions involving particles with different electric charges, for which the associated Schwinger phases do not cancel. We show that these terms can be systematically evaluated in coordinate space using the Ritus formalism, which provides the appropriate framework for treating external charged states in the presence of a magnetic background, and consistently expressed in momentum space. The resulting expressions exhibit a nontrivial interplay between thermal fluctuations and magnetic effects and allow for a clear separation between vacuum and matter contributions, providing a well-defined structure for the identification of ultraviolet divergences. Our results establish a consistent and systematic framework for the computation of thermomagnetic one-loop corrections in effective models of QCD, capturing the full interplay between thermal and magnetic effects for all dynamical degrees of freedom.

We develop bootstrap methods for mixed heavy-light four-point correlators $\langle GGOO\rangle$ in $\mathcal N=4$ super-Yang--Mills theory at large $N$, where $O\equiv {\cal O}_2$ is the chiral primary operator in the stress-tensor multiplet and $G$ are (dual) giant graviton operators with dimension of order $N$, including the maximal determinant case. The loop integrand is expanded in a basis of labelled $f$-graphs -- necessarily including non-planar topologies due to the dimension-$N$ nature of the giant gravitons -- and the coefficients are fixed by various bootstrap conditions including double-triangle and triangle rules in the cusp and OPE limits, integrated correlators from supersymmetric localization, and a ten-dimensional hidden symmetry, the latter also allowing extension to correlators involving generic chiral primaries $\mathcal{O}_k$. Together, these inputs uniquely determine the correlator through three loops, passing further non-trivial consistency checks. For the maximal determinant operator, we reproduce the known results through two loops and obtain the full three-loop correction.

Possible anomalous couplings of the Higgs boson to vector bosons and fermions are studied using Higgs boson candidates decaying to a pair of photons. The study is based on proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the CMS experiment, corresponding to an integrated luminosity of 138 fb$^{-1}$. Events with Higgs boson candidates produced via gluon fusion, electroweak vector boson fusion and in association with a vector boson, are categorized using matrix element techniques and multivariate discriminants. The $CP$ properties of the Higgs boson couplings to gluons through loops of heavy particles, as well as the tensor structure of its interactions with two electroweak bosons, are investigated. The results are interpreted in terms of the fractional contributions of anomalous Higgs boson couplings to the total production cross section of each process and are found to be consistent with the standard model expectations.

We present a study of the $τ^- \to ωπ^-ν_τ$ decay in the framework of low-energy effective field theory. By analyzing the $J^{PG}$ quantum numbers of the quark currents and the $ωπ$ final state, we find that only the Standard Model (SM) vector interaction and the non-standard tensor interaction can contribute to this decay. We construct the resonance chiral theory Lagrangian with external tensor sources and calculate both the vector and tensor form factors, with resonance couplings determined through QCD short-distance constraints, spectral function fitting, and chiral perturbation theory matching. The new physics (NP) effect is investigated in the spectral function and forward-backward asymmetry distributions. Our results show that the spectral function is dominated by the SM, while the forward-backward asymmetry, which can only arise from a non-zero tensor interaction, provides a sensitive probe of this NP effect. Future measurements at Belle II, Tera-Z, and STCF facilities are therefore strongly motivated.

Upcoming experiments need improved simulations of neutrino scattering. This work uses the popular GENIE event generator to test a variety of neutrino interaction models against recent MicroBooNE measurements of pionless charged-current interactions. The GENIE code can easily interchange model components, including nucleon form factor parameterizations, quasielastic cross-section calculations, treatments of the nuclear ground state and hadronic final-state interactions. Leveraging this software capability in comparisons with MicroBooNE data, the performance of some of GENIE's most theoretically sophisticated model components is evaluated and contrasted with more empirically-driven alternatives.

In Plebański nonlinear electrodynamics with spontaneous Lorentz symmetry breaking, nontrivial magnetic backgrounds are selected by stationary points of an effective Hamiltonian. Previous branchwise Hamiltonian analyses showed that this same stationarity requirement coincides with the vanishing of the determinant of the Poisson-bracket matrix among the second-class constraints, but the structural origin of this coincidence was not manifest. We show that it follows from the constitutive origin of the theory. The structural potential \(V(P,Q)\) generates the electromagnetic constitutive relations, while the effective Hamiltonian for magnetic vacua is the complementary energy associated with the magnetic response at fixed \(\Dvec\). Moreover, because the first-order constitutive relation enters the Dirac constraint structure, the magnetic constitutive Jacobian appears as a local block of the Poisson-bracket matrix among the second-class constraints. This complementary-energy structure implies that every nontrivial magnetic stationary point lies on a surface where the linearized map \(δ\Hvec\mapstoδ\Bvec\), at fixed \(\Dvec\), loses rank. We use this interpretation to formulate the reduced linearized theory at the vacuum, discuss the removal of the radial mode in the vacuum-restricted theory, and clarify why electric and mixed stationary branches are obstructed in single-invariant models.

We present a comprehensive analysis of the Landau-Khalatnikov-Fradkin transformations for the charged fermion propagator in reduced quantum electrodynamics (RQED). Starting from the propagator in a reference gauge, we perform a gauge transformation to obtain its analytical expression valid to all orders in an arbitrary covariant gauge and also applicable in a nonperturbative context. This work complements and extends previous studies of quantum electrodynamics in various spacetime dimensions, for both massless and massive fermions. At the perturbative level, we expand the resulting expressions up to two-loop order for both massless and massive cases, and compare our results with those available in the literature wherever possible. We argue that the most suitable choice of the reference covariant gauge in RQED is $ξ=1/3$, as in this case the leading logarithmic contribution to the massless wave-function renormalization vanishes at one-loop order. This choice provides a direct connection between perturbation theory and the constraints imposed by multiplicative renormalizability on the massless fermion propagator. We also investigate the implications of the Landau-Khalatnikov-Fradkin transformations for the dynamically generated mass function of the fermion propagator. Finally, through numerical computation, we demonstrate that both the chiral fermion condensate and the fermion pole mass are gauge-invariant quantities.

In this paper, we presented an approximate analytical treatment of the Coulomb plus logarithmic potential using perturbation theory to investigate the mass spectra of bottomonium and charmonium mesons for the low-order quantum states. The derived energy equation, to first-order corrections, was employed to model the free potential parameters through fitting to experimental data of the Particle Data Group. The proposed potential successfully reproduces asymptotic freedom at short distances through one-gluon exchange interactions and quark confinement at large distances, which are the essential features of the strong interactions in Quantum chromodynamics theory. The calculated bottomonium masses exhibited excellent agreement with experimental values, yielding an absolute percentage average deviation (APAD) of 0.24%, which improves upon several previously reported theoretical results. Similarly, the vector and pseudoscalar charmonium masses were obtained with an APAD of 1.65%, demonstrating improved and comparable accuracy relative to existing competing theoretical calculations. Although our results were limited to first-order corrections to the energy spectra within the perturbation theory, the reliability of the approximation was validated by comparison with exact numerical solutions obtained using the matrix Numerov method. The small percentage errors obtained confirm the effectiveness of the phenomenological potential and perturbation approximation in describing quarkonia systems. The results suggest that the approach can be reliably extended to higher excited states.

Collinear factorization and color-glass condensate (CGC) effective field theory are generally treated as separate approaches for calculating scattering amplitudes, valid in different kinematic regimes. For deep inelastic scattering at high photon virtuality and high center-of-mass energy, however, both of these approaches should be applicable. By expressing collinear parton distributions and generalized parton distributions in the shockwave approximation, we show that the resulting collinear-factorization amplitudes exactly reproduce the large-$Q^2$ expansion of CGC amplitudes for inclusive deep inelastic scattering, deeply virtual Compton scattering, and deeply virtual meson production. The matching holds directly at the amplitude level and includes both logarithmically enhanced and finite contributions. Our results establish the consistency between collinear factorization and the CGC in their common region of validity, clarify the origin of large momentum logarithms within the CGC framework, and provide a path toward combining high-energy and collinear evolution in a unified description of hadronic structure at small $x$ and large momentum scales.

Generalized Parton Distributions (GPDs) provide a comprehensive framework for describing the three-dimensional structure of the nucleon. Extracting GPDs from experimental data requires flexible and physically motivated ansatz. In this study, we introduce a new ansatz, AMA25, designed to address the limitations of the previous model, GSAMA24 (Phys. Rev. C 111 (2025) 2, 025203). We conduct a fast and efficient comparison by fitting AMA25 models and other relevant data using the iMinuit optimization package within a Jupyter Notebook environment. The AMA25 ansatz demonstrates superior fit quality, achieving a reduced $χ^2$, while better satisfying theoretical constraints. Additionally, AMA25 exhibits enhanced stability when extrapolated to the exclusive region. Our analysis highlights the power of modern computational tools for rapid model validation and underscores the importance of innovative ansatz in advancing nucleon structure studies.

Ultralight primordial black holes (PBHs) provide a compelling window into early-Universe cosmology. Following our earlier work, we explore a mechanism for the formation of ultralight PBHs sourced by primordial inflationary magnetic fields, without invoking an ultra-slow-roll phase of inflation. We propose a magnetogenesis model in which large curvature perturbations are induced at small scales, leading to the efficient production of ultralight PBHs across a broad mass spectrum. We analyze the phenomenological implications of these ultralight PBHs for early-Universe cosmology, particularly during reheating. We compute the resulting stochastic gravitational wave (GW) background generated by both the electromagnetic spectrum and evaporating PBHs, which exhibits distinctive features tied to the underlying magnetogenesis model parameters. Our results demonstrate that inflationary magnetic fields can serve as a viable and testable origin for ultralight PBHs, opening new avenues for probing the interplay between inflation, magnetogenesis, PBHs, and primordial gravitational waves.

We present the first combined analysis of the statistical rate function f in superallowed beta decays with ab initio calculations and data. We focus on C10 to 10B, 14O to 14N and 26mAl to 26Mg, all of which are important channels for the precise determination of the Cabibbo-Kobayashi-Maskawa (CKM) matrix element Vud. Nuclear charge form factors are obtained by combining experimental data on nuclear charge radii and theory calculations of ratios of moments with the in-medium similarity renormalization group, while the beta decay form factors are derived from exact isospin relations. This enables a rigorous study of the nuclear shape dependence in the statistical rate function f and the quantification of its uncertainties from both experiment and theory. The calculation leads to a more precise test for the first-row CKM unitarity with reduced theoretical uncertainties. This work demonstrates a reliable strategy for combining nuclear many-body calculations with high-precision nuclear data to describe beta decays at tree level for precision tests of the Standard Model.

With the next generation of both electromagnetic and gravitational wave observatories beginning to come online, rapid analysis methods for kilonova data are becoming increasingly important in astronomy. Traditional Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) is time-consuming and relies on explicit likelihood approximations that can break down when modeling uncertainties are significant. We develop a simulation-based inference (SBI) framework for kilonova parameter estimation using density-estimation likelihood-free inference. The framework uses a Gaussian process emulator trained on $\sim1300$ radiative transfer simulations generated with the POSSIS code. We demonstrate that SBI provides a rapid alternative to MCMC for inference with emulators or approximate likelihoods that is robust to emulator uncertainty and likelihood misspecification. On simulated data, the SBI method accurately recovers injected parameters and produces posterior predictive light curves consistent with the data, but the MCMC posterior recovery suffers from systematic bias caused by likelihood misspecification. When analyzing AT2017gfo, the SBI and MCMC methods yield similar light-curve predictions but different posterior distributions, with a subset of the MCMC posteriors piling up at prior boundaries. The likelihood in the MCMC fails to capture the non-Gaussian, correlated structure of the emulator uncertainty, but SBI learns the posterior directly from forward simulations that include the full predictive distribution. Once trained, the SBI framework generates $\sim2\times10^4$ posterior samples in seconds.

We propose a phenomenological model of pseudo scalar mesons to describe charged-current weak decays of heavy-light mesons. The approach combines chiral symmetry in the light sector with heavy-quark flavor symmetry, while Cabibbo--Kobayashi--Maskawa (CKM) matrix elements are incorporated as spurions that encode explicit symmetry breaking. Restricting to charged-current interactions, we systematically organize the leading-order current-current operators at dimension six and identify the relevant operator structures governing fully-leptonic, semi-leptonic, and hadronic decays. This framework reproduces known heavy-quark scaling relations for decay constants and form factors in agreement with expectations from heavy quark effective theory, providing nontrivial consistency checks. Operators responsible for hadronic transitions are further classified into double-trace operators and single-trace operators. These single traces, interestingly, often capture several higher order corrections, non-factorizable effects etc. We check for consistencies for both single-trace and double-trace operators demanding that the resulting amplitudes should satisfy established isospin sum rules. As an application, we analyze the decay modes $B\to K + η_{c} / η^{\prime}/ η$. We find that these processes receive contributions from a host of non-trivial processes such as mixing between various states, non-perturbative QCD parameters such as the heavy quark condensates, non-factorizable effects, etc, apart from the straightforward perturbative $W$ exchange diagrams in the quark picture. Our set-up neatly captures all of these effects. The phenomenological model we provide here is a symmetry-guided, hadron-level description of charged-current processes and offers a complementary perspective to conventional quark-level approaches, with a natural avenue for incorporating non-factorizable effects.

For a local quantum field theory in anti-de Sitter space with conformal boundary conditions but without dynamical gravity, the boundary theory is generically a non-local conformal field theory. Such theories can support conformal defects, but the standard local-CFT arguments based on a boundary stress tensor and conserved currents do not apply. We argue that, under general assumptions, displacement and tilt operators nevertheless exist and have protected quantum numbers. The mechanism is a Goldstone-type phenomenon in AdS: defect-induced symmetry breaking on the boundary is spontaneous from the viewpoint of the local bulk theory, whose Ward identities enforce the corresponding protected defect operators. We illustrate the mechanism in weakly coupled defect RG flows, long-range Landau--Ginzburg models, 4D Maxwell theory, and Yang--Mills theory in AdS.

Measuring charge fluctuations within a subregion provides a powerful probe of quantum many-body systems. In two spatial dimensions, the shape dependence of the dimensionless corner contribution encodes universal data of quantum critical points and reveals observables of quantum geometry in various quantum phases. Here, we systematically extend this framework to higher dimensions. In three dimensions, we derive the universal angle dependence associated with trihedral corners of a generic parallelepiped and benchmark the predictions against Monte Carlo simulations of lattice models at the O(3) quantum critical point. We further identify a wedge-corner contribution that directly probes the quantum metric, supported by numerical results for a lattice Weyl semimetal model. More generally, we obtain angle functions for polyhedral corners of arbitrary parallelotopes in general dimensions and clarify the scaling of the corner contribution across phases of matter. While insulators and conformal critical points exhibit similar behavior across dimensions, metals display a characteristic even-odd dimensional effect.

Millicharged particles (mCPs) are a well-motivated target for far-forward searches at the Large Hadron Collider. We identify and quantify a significant new source of these particles: secondary production in hadronic and electromagnetic showers initiated by energetic neutral particles striking the TAXN absorber. By combining Monte Carlo simulations with \texttt{Geant4}-based modeling, we show that these secondary cascades yield a substantial mCP flux that complements the primary production from the interaction point. For the proposed FORMOSA detector, this contribution can enhance the expected signal yield by approximately $50\%$ for $m_χ\lesssim 0.1~\textrm{GeV}$. Our results demonstrate that secondary production in downstream infrastructure is an essential ingredient for realistic sensitivity projections and new-physics searches at the High-Luminosity LHC. The simulated secondary spectra are made publicly available to facilitate future forward physics studies.

In the presence of extended defects, familiar incoming particles can scatter into exotic outgoing states created by twist operators. We show that one possible mechanism driving these "categorical scattering" processes is the presence of localized 't Hooft anomalies on the defect's worldvolume. Defect anomalies trap non-trivial charges at junctions between the symmetry lines and the interface, opening new transmission channels that would naively appear to violate selection rules. After outlining the general mechanism, we investigate several concrete examples with defects, interfaces, and boundaries. For models of massless chiral fermions already studied in the literature, we show that the emergence of twist operators can be understood as a consequence of defect anomalies. We then introduce new massive integrable theories in which a similar phenomenon occurs, and we explicitly solve the associated scattering problem, obtaining new integrable solutions. Finally, we construct lattice spin chains with defects where similar physics is expected to arise.

We study the sensitivity of the diffuse high-energy neutrino flux observed in IceCube to new-physics effects resulting in an exponential flux attenuation along the trajectory, such as invisible neutrino decay or new interactions with the background encountered during propagation. We argue that, even though the sources and production redshifts of these astrophysical neutrinos are unknown, conservative energy-conservation arguments allow to severely constrain neutrino loss in most scenarios beyond the strongest existing bounds. By performing a fit to the High-Energy Starting Events from IceCube, we quantify the bounds and study their variation with the energy dependence of the attenuation, the assumed redshift distribution of the neutrino sources, and whether the attenuation affects neutrinos exclusively or no. We also show that including an energy-dependent attenuation at the level allowed in the fit may impact the determination of the spectral index of the diffuse flux.

We propose an explanation for the dark matter-baryon coincidence based on collapsing $\mathbb{Z}_N$ domain walls, which form a novel compact baryonic state: the baryoid. A baryoid has an asteroid-scale mass and up-to-nuclear-scale energy density, and can serve as a dark matter candidate. Starting from equal baryon numbers in the domains formed in the early universe, the collapse of the domain walls after the QCD phase transition leads to a baryon-number ratio of $(N-1):1$ between the false- and true-vacuum domains. Since baryons are slightly lighter in the false-vacuum domains than in the true-vacuum domain, the resulting dark matter-to-baryon energy-density ratio is naturally close to, but slightly smaller than, $(N-1):1$, or $6:1$ for $N=7$. We calculate the domain-wall dynamics and the efficiency of baryon-number trapping, derive the resulting baryoid properties, and discuss a broad set of phenomenological probes.

Heavy spin-one particles are well-motivated new physics candidates that can have their origin in weakly coupled extensions of the Standard Model gauge group or in strongly coupled Composite Higgs models. Due to the variety of production and decay modes, heavy vector triplets are a useful benchmark for the study and comparison of future colliders. Here we perform a detailed collider analysis of a variety of $2 \to 2$ and $2 \to 3$ processes at a proposed future muon collider. We focus on decays into leptons and Standard Model gauge bosons, and find that heavy vector triplets could be probed up to masses of around $12\,$TeV for almost any (perturbative) value of the coupling. We compare the direct reach of a muon collider to the LHC and to updated projections for the HL-LHC, HE-LHC and FCC-hh, and include indirect limits from future measurements of electroweak precision observables. We find that a muon collider offers projected sensitivities that are competitive with future hadron colliders, exceeding those of the HE-LHC in the scenarios considered though not reaching the projected sensitivity of the FCC-hh.

We study local quantum field theories in Anti-de Sitter (AdS) space, with boundary conditions that break some of the bulk isometries. Specifically, we focus on conformal defects and we prove that their spectrum supports a displacement operator of protected dimension, despite the non-local nature of the conformal theory living at the boundary of AdS. If the defect breaks a global symmetry, a tilt operator is also present. The existence of a displacement was conjectured in arXiv:2508.08250 for Wilson loops in Yang-Mills theories in AdS. Our proof is valid in general and applies, in particular, to defects in long-range models, as we discuss in various examples. In the bulk, the modes sourced by the protected operators have Compton wavelength of order of the AdS radius: they constitute the AdS analogue of the Goldstone bosons for the spontaneous breaking of the corresponding symmetries.

We study the relation between boundary conditions and categorical symmetries of two-dimensional fermionic conformal field theories. We determine all anomaly-free invertible global symmetries of two free complex Weyl fermions, which take the form $\mathbb{Z}_k$ for each primitive Pythagorean triple $a^2 + b^2 = k^2$. The theory is self-dual under gauging any of these symmetries, and so to each there is associated a non-invertible topological defect. We study the properties of these lines, and show that any conformal boundary condition of two Dirac fermions that preserves a $U(1)^2$ symmetry can be found by dressing a trivial Dirichlet boundary with one of them. We discuss two microscopic descriptions of these defects: fermions coupled to a quantum-mechanical rotor degree of freedom; and an abelian gauge theory that realises symmetric mass generation in a half-space.

Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and nuance of real scientific work. To address this gap, we introduce Collider-Bench, a benchmark for evaluating whether LLM agents can reproduce experimental analyses from the Large Hadron Collider (LHC) using only public papers and open scientific software. Such analyses are often difficult to reproduce because the public toolchain only approximates the software used internally by the experimental collaborations, while the published papers inevitably omit implementation details needed for a faithful reconstruction. Agents must therefore rely on physical reasoning, domain knowledge, and trial-and-error to fill these gaps. Each task requires the agent to turn a published analysis into an executable simulation-and-selection pipeline and submit predicted collision event yields in specified signal regions. These predictions are evaluated with standard histogram metrics that provide continuous fidelity scores without a hand-written rubric. We also report the computational cost incurred by each agent per task. Finally, we evaluate the codebase and full session trace using an LLM judge to catch qualitative failure modes such as fabrications, hallucinations and duplications. We release an initial set of tasks drawn from LHC searches, together with a containerized sandbox and event simulation tools. We evaluate across a capability ladder of general purpose coding agents. Our results show that on average no agent reliably beats the physicist-in-the-loop solution.

We formulate PanScales final-state showers that account for quark masses and achieve next-to-leading logarithmic accuracy, while preserving the original accuracy of the showers for observables where the mass of the quarks is irrelevant. We validate the accuracy of the shower algorithms by performing fixed-order tests up to second order in the strong coupling constant, and all-order comparisons to (semi-)analytic resummed calculations for a series of observables, including Lund-tree shapes, non-global energy flows and Lund sub-jet multiplicities. We also include some phenomenological studies using LEP data.

A search is performed for the electroweak pair production of charginos and associated production of a chargino and neutralino, each of which decays through an $R$-parity-violating coupling into a lepton and a $W$, $Z$, or Higgs boson. This search targets the Higgs boson decay channel of the charginos and neutralinos, using events with three or more $b$-tagged jets and one or two electrons or muons. The analyzed data corresponds to an integrated luminosity of 140 fb$^{-1}$ and 56 fb$^{-1}$ of proton-proton collision data produced by the Large Hadron Collider at center-of-mass energies of $\sqrt{s}=13$ TeV and $\sqrt{s}=13.6$ TeV respectively, collected by the ATLAS experiment between 2015 and 2023. The data are found to be consistent with predictions from the Standard Model. The results are interpreted as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model. Limits are also set on the production of charginos and neutralinos for a Minimal Supersymmetric Standard Model with an additional $B-L$ gauge symmetry that is spontaneously broken. Charginos and neutralinos with masses between 150 GeV and 1100 GeV are excluded at 95% confidence level for a scenario in which they decay via Higgs bosons, assuming equal decay branching fractions to each lepton flavor. Additional limits are derived for flavor-specific decay scenarios.

We consider the ``metric-affine-like'' generalization of the Yang-Mills theory (mal-YM) which we first proposed earlier. In this model, the connection is no longer assumed to be compatible with the Hermitian form in the fibers. As a consequence, along with the usual YM potential $\boldsymbol{A}_a$ and the field strength tensor $\boldsymbol{F}_{ab}$, it contains non-trivially interacting fields $\boldsymbol{B}_a$, $\boldsymbol{h}$, and $\boldsymbol{G}_{ab}$, $\boldsymbol{N}_a$, forming a non-Abelian generalization of Stückelberg theory. Due to the spontaneous symmetry breaking $GL(n,\mathbb{C}) \to U(n)$, these new fields can be made massive and the limit $M\to\infty$ restores the standard YM theory. We perform a detailed analysis of this theory on the classical level. We discuss in detail geometric motivation for the model, field transformations, gauge symmetry and its spontaneous breaking, action, equations of motion, Noether identities, gauge fixing, and other issues.

We investigate the description of quark confinement in terms of confining strings or flux tubes. We show that compact QED with a topological $θ$-term, in the dyon condensation phase, is described by a massive two-form field $B_{μν}$ that gives rise to a string theory with an IR Brazovskii-Lifshitz fixed point at strong coupling. This corresponds to a quantum consistent "free string" in (3+1) dimensions, representing the dual of asymptotic freedom in the UV. Contrary to critical strings, which correspond to trivial Gaussian fixed points, this string is stabilized by a finite thickness, determined by the mass of the $B_{μν}$ field, instead of living in a higher-dimensional space. It correspondingly contains a massive world-sheet resonance, in addition to the Nambu-Goto phonons, that improves fitting with data. We compute the confining potential and show that it reproduces a generalized Arvis potential $V(L) = aL \sqrt{1 - c/L^2}$ with running parameters $a(L), c(L)$. We compute the mass difference ratios for the heaviest quarkonium and find 2.5 percent agreement with experiment already at the infrared fixed point. We also compute the intercept of Regge trajectories and find that the thickness of Brazovskii-Lifshitz strings tends to increase it from the Nambu-Goto value $α_0 = 1/12$. Overall, our findings strongly support Polyakov's longstanding conjecture on universality of confining gauge theories in the IR.

We study the CP-conserving flipped (Type-Y) Two-Higgs-Doublet Model (2HDM) in the large-$\tanβ$ regime ($\tanβ>30$), focusing on its implications for electroweak phase transitions (EWPTs) and LHC phenomenology. Viable parameter regions supporting a strong first-order EWPT fall into two heavy-Higgs hierarchies: (A) $m_{H^\pm}\simeq m_H<m_A$ and (B) $m_H<m_{H^\pm} \simeq m_A$, both featuring a heaviest CP-odd Higgs $A$. Scenario~A typically proceeds via one-step transitions with lower nucleation temperatures, while Scenario~B allows one-step or two-step transitions, opening the decay $A\to H^\pm W^\mp$ and yielding richer collider signatures. In all cases, nucleation conditions are satisfied, avoiding false-vacuum trapping. We assess LHC prospects through bottom-associated production with multi-$b$ final states: $pp\to bbH\to 4b$ and $pp\to bbA\to bb W^\pm H^\mp\to 4b\ell\ellνν$. The $4b$ channel offers high-statistics discovery potential, reaching signal significances $z\gtrsim 25$ at the 13 TeV LHC with 300 fb$^{-1}$ and up to $z\gtrsim 100$ at the 14 TeV HL-LHC with 3 ab$^{-1}$. The cascade channel, while experimentally more challenging, directly probes the heavy Higgs spectrum and can discriminate between EWPT scenarios. Using optimized selections with a BDT-based multivariate analysis, significances of $z \simeq 6.8$ can be achieved in favorable regions of Scenario~B at the HL-LHC. These results indicate that the HL-LHC can realistically probe the BSM Higgs sector responsible for a strong first-order EWPT and provide insight into the underlying phase transition dynamics in the flipped 2HDM.

Monolithic active pixel sensor (MAPS) developments have pushed the detection performance in various directions, especially relative to timing where nanosecond-level precision is now considered. This evolution calls for a simultaneous upgrade of the simulation tools. We have developed a simulation flow that covers steps from the signal creation in the sensitive volume to the output of the pixel digital logic that performs the time-of-arrival and time-over-threshold (ToA/ToT) measurements. This approach adds several new features to the traditional use the of the TCAD - Allpix Squared duo, among which : the integration of the pixel wells from the layout in order to precisely describe the pixel key characteristics such as leakage and punch-through currents and the coupling of Monte Carlo simulations (Allpix Squared) with high precision electrical simulations (SPICE). The first (Allpix Squared) for the precise description of the current induced at the collection electrode and the second (SPICE) to guarantee high precision simulation of the front-end electronics using realistic signal events. Irradiation is also modeled, both from the charge propagation side (charge trapping) and from the front-end response side (high input signal discharge). We have applied this methodology to the MAPS developed in the context of the Belle II vertex detector upgrade. In this contribution, we detail the key features of the exhaustive simulation flow, present the outcome of the comparison with the TJ-Monopix2 measurements and discuss the interest of the methodology for the development of modern MAPS.

In this study, a relativistic formulation of the $(q)$-deformed Dunkl-Fokker-Planck equation in $(1+1)$-dimensions is constructed within the reflection-deformed quantum framework. In this case, the formalism includes $(q)$-deformed Dunkl operators and reflection symmetry to build a generalized dynamical structure for a relativistic quantum systems framework. Moreover, the corresponding $(q)$-Wigner-Dunkl supersymmetric configuration is established via the construction of deformed ladder operators and supersymmetric algebraic relations, yielding a consistent spectral representation of the model within the algebraic framework. The analysis extends to the harmonic oscillator with centrifugal interaction, where exact algebraic solutions, similarity reduction techniques, and closed energy spectra are obtained analytically in detail. The role of the deformation parameter and reflection operator on spectral properties and wavefunction structure is examined systematically in detail. A generalized Foldy-Wouthuysen (FW) transformation is introduced within the deformed Dunkl framework to achieve relativistic decoupling of positive- and negative-energy sectors within the present theoretical formulation. In this case, this approach yields an effective reduced Hamiltonian, including higher-order relativistic and deformation-induced terms. Also, the associated Dunkl-Fokker-Planck dynamics generated through high-order FW reduction are examined in detail for reflection-deformed relativistic quantum systems. In this context, results obtained here yield a unified algebraic and relativistic description of $(q)$-deformed Dunkl structures and construct a consistent framework for investigating supersymmetric and relativistic properties in reflection-symmetric quantum models in general.

A comprehensive study of the phase structure of the two-flavor quark-meson-diquark model is presented within the nonperturbative functional renormalization group framework. The influence of mesonic fluctuations beyond the mean-field approximation is investigated, and two-point functions of the diquark fields are computed at finite real-time frequencies. Renormalization group consistency of the effective potential is ensured in order to avoid cutoff artifacts. Substantial modifications of the phase structure are found once mesonic fluctuations are included, and for sufficiently strong diquark couplings the dynamics become dominated by diquark condensation. These effects are elucidated through an analysis of the diquark pole mass and the Silver-Blaze property.

According to the $B$-mesogenesis framework, the baryon asymmetry of the Universe and dark matter can be simultaneously generated through CP-violating $B$-meson oscillations. In this mechanism, $B$-mesons decay into a Standard Model baryon and a dark-sector antibaryon, denoted by $ψ_{DS}$. Within this scenario, we investigate the allowed mass window for $ψ_{DS}$ using Light Cone Sum Rules (LCSR) for $B_d\rightarrowΛ\, ψ_{DS}$ decay. To include non-perturbative effects, we employ contributions up to twist-6 of the $Λ$ distribution amplitudes in the operator product expansion (OPE). We derive the branching fraction as a function of dark antibaryon mass and, by comparing with the experimental limits by the BaBar and Belle collaborations, determine the mass ranges of $ψ_{DS}$ consistent with the $B$-mesogenesis mechanism.

Spectral shape differences between photons produced in $π^0\toγ+γ$ and $π^0\toγ+A_D$ may provide a new avenue for dark photon searches. Assuming 70 $μ$m thick tungsten foils separated by 200 $μ$m and a 1 GeV proton beam, we developed a GEANT4 model to estimate photon production and detection including background. Our results demonstrate that multiple campaign runs with a 10-50 $μ$A beam could probe previously unexplored regions of parameter space in models where the dark photon has predominantly invisible decays. The results are highly model independent.

We present the first paleo-detector dark matter sensitivity analysis based on a calorimetric readout, in which the number of stable lattice vacancies produced by each nuclear recoil is used as a per-event observable complementary to the track length. Using full-cascade SRIM simulations in olivine, we compute the expected sensitivity for a 100 gGyr exposure. We find that a vacancy-only readout reaches a sensitivity envelope very similar to that of state-of-the-art track-only analyses. The combination of the two observables provides an event-by-event proxy for |dE/dx| and hence for the recoiling nuclear species. Since the neutron-nucleus cross section is approximately flat in nuclear mass while the dark-matter--nucleus cross section scales as $A^2$, this discrimination suppresses the dominant neutron background by more than an order of magnitude at moderate dark matter masses. The combined-analysis sensitivity reaches spin-independent dark-matter--nucleon cross sections of order $10^{-48}\,\mathrm{cm}^2$ at WIMP masses of a few tens of GeV, comparable to future direct detection experiments. A two-stage readout combining selective-plane illumination microscopy with scanning electron microscopy is identified as a path to making a 100 g-scale analysis plausible.

A search is presented for single production of a vector-like top quark T, decaying into the standard model top quark and Higgs boson, in a final state including two opposite-sign leptons (electrons or muons), jets, and missing transverse momentum. The data were recorded by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV at the CERN LHC in the years 2016$-$2018, and corresponding to an integrated luminosity of up to 138 fb$^{-1}$. No excess in data over the background expectations is observed. Upper limits at 95% confidence level on the product of the T production cross section and its decay branching fraction to tH are set, ranging from 2.0 pb at a T mass of 600 GeV to 0.1 pb at 1000 GeV. This is the first search in the T $\to$ tH channel in opposite-sign dilepton final states.

A first dedicated search for pair production of new scalars predicted by the Inert Doublet Model is performed using proton-proton collisions. Data were collected with the CMS detector at the CERN LHC at $\sqrt{s}$ = 13 TeV and 13.6 TeV, corresponding to integrated luminosities of 138 fb$^{-1}$ and 35 fb$^{-1}$, respectively. Within this model, four additional scalar bosons (H, A, H$^+$, and H$^-$) are predicted. Through an additional discrete symmetry, the lightest new scalar, H, is stable, rendering it a viable dark matter candidate. These candidates can originate from quark-antiquark annihilation producing an offshell Z boson that decays to a pair of the new scalars. The target final state consists of exactly two opposite-charge same-flavour leptons (electrons or muons), with missing transverse momentum due to the stable neutral scalars, and very little hadronic activity. A parameterised neural network is used to separate the signal from the standard model background. No significant excess of events is observed. Exclusion limits at 95% confidence level are set on the production cross section of the two new neutral scalars, H and A, expressed in terms of their masses, $m_\mathrm{H}$ and $m_\mathrm{A}$, in the $m_\mathrm{H}$ vs. $m_\mathrm{A}$ plane. The observed (expected) exclusion region reaches $m_\mathrm{H}$ = 108 (106) GeV for $m_\mathrm{H}-m_\mathrm{A}$ = 78 (76) GeV and at $m_\mathrm{H}$ = 70 GeV, covers the range of $m_\mathrm{H}-m_\mathrm{A}$ = 40$-$90 (35$-$90) GeV.

This Paper presents rapidity-differential measurements of coherent J/$ψ$ and $ψ({\rm 2S})$ photoproduction, as well as rapidity- and mass-differential measurements of exclusive dimuon production, in the forward rapidity region $-4 < y < -2.5$ in ultra-peripheral Pb$-$Pb collisions at $\sqrt{s_{\rm NN}}=5.36$ TeV using data recorded by the ALICE detector at the LHC in 2023, corresponding to an integrated luminosity of $\mathcal{L} = 1170 \pm 50~μ{\rm b}^{-1}$. The J/$ψ$ and $ψ({\rm 2S})$ results reveal the significant role of nuclear shadowing effects. The square root of the ratio of the measured quarkonium cross section to the impulse approximation prediction is about 0.76 for J/$ψ$ and 0.71 for $ψ({\rm 2S})$, at $y \approx -3$, corresponding to typical Bjorken-$x$ values of $10^{-2}$. The exclusive dimuon results highlight the sensitivity of such measurements to precise modeling of the photon flux, particularly at impact parameters near the nuclear radius.

High-purity germanium detectors are widely used in rare-event searches due to their excellent energy resolution and extremely high intrinsic (radio)purity. In experiments searching for neutrinoless double beta decay in $^{76}$Ge such as LEGEND, pulse shape discrimination is required to suppress multi-site $γ$ events. In this work, we investigate whether pulse shape discrimination classifiers trained exclusively on $γ$ ray data can be used to identify and reject $α$ events, without the need for dedicated $α$ training. In detectors such as LEGEND, the total number of registered $α$ events over the experiment lifetime is expected to be insufficient to train dedicated classifiers, while still contributing to the background. Two approaches based on machine learning are studied: a multilayer perceptron and a projective likelihood classifier. The p+ surface of a point-contact semi-planar germanium detector was exposed to $^{209}$Po and $^{210}$Po sources deposited on a thin gold foil. Two measurement campaigns were performed, yielding $1.36\times10^{5}$ and $1.87\times10^{6}$ $α$ events, respectively. Both classification methods achieve efficient separation of single-site and multi-site $γ$ events while strongly reducing the $α$ component. The multilayer perceptron provides the best overall performance, with a signal-like event survival greater than 80%, a background-like event survival below 20%, and an $α$-rejection factor exceeding $2.71\times10^{4}$. These results demonstrate that robust pulse shape discrimination for high-purity germanium detectors can be achieved using training information derived solely from $γ$ events, providing a promising strategy for next-generation neutrinoless double beta decay searches.

We determine the pion parton distribution functions (PDFs) from its light-front wave functions, obtained using the holographic Schrödinger equation of light-front chiral QCD combined with the 't Hooft equation in (1+1)-dimensional QCD at large $N_c$. We analyze the large-$x$ behavior of the valence PDF, $\sim (1-x)^{β^{\rm eff}_v}$, finding overall consistency with global analyses. These pion PDFs, together with nuclear PDFs, are then used to compute the differential cross sections up to next-to-leading order for inclusive $J/ψ$ production in pion--nucleus collisions, which show good agreement with experimental data across different energies and nuclear targets.

Heavy quark symmetries are useful for predicting the existence of heavy states, their masses, and spin states. Despite numerous studies on the $P_{c\bar{c}}(4440)$ and $P_{c\bar{c}}(4457)$ heavy states, their spin states have not been previously determined. In this study, heavy symmetries are applied to predict the spin states. If the $P_{c\bar{c}}(4440)$ and $P_{c\bar{c}}(4457)$ states are considered $\bar{D}^*Σ_c$ molecules, they can be classified as heavy partners. This classification may help clarify their potential connections with heavy antiquark-diquark symmetry partners. By utilizing these alternative spin assignments and the concept of heavy antiquark-diquark symmetry, it may be possible to estimate $Ξ_{cc}^{(*)}Σ_c^{(*)}$ states, and ultimately, their spin states, which have not been elucidated in experiments. In addition to these symmetries, the relationship between $P_{c\bar{c}}$ and $P_{c\bar{c}s}$ pentaquarks can be constructed which supports the prediction of possible $P_{c\bar{c}s}$ states. The predicted masses of the $P_{c\bar{c}s}(4338)$ and $P_{c\bar{c}s}(4459)$ states align with several studies, allowing us to eliminate a specific spin state. One spin state appears to be favored, suggesting that $P_{c\bar{c}}(4440)$ has $J^P=\frac{1}{2}$ and $P_{c\bar{c}}(4457)$ has $J^P=\frac{3}{2}$.

In the Type-I two-Higgs Doublet Model (2HDM), the additional scalars may be light ($\lesssim 100$ GeV) without conflicting with experimental constraints from LHC searches or from flavour observables. So far, the studies of light scalars at the LHC have been limited to exploring non-standard decays of the Standard Model (SM) Higgs boson or via $b\bar b$ associated production followed by leptonic decays of the light scalar. A light scalar in Type-I 2HDM can evade these search strategies due to its potentially tiny coupling to the SM Higgs boson and its suppressed coupling to quarks. In this work, we have studied electroweak production of a light scalar ($h$) in association with heavy pseudoscalar $A$ or charged Higgs $H^\pm$, which further decays into $h$, resulting in a multi-$h$ final state, where $h$ is boosted due to its lightness. The decay of the boosted $h$ into $b\bar b$ can be reconstructed within a fat-jet containing a pair of $b$-subjets. We find that tagging such a `boosted double-$b$ fat-jet ($J_{bb}$)' signature in association with a SM gauge boson provides an excellent probe of the Type-I 2HDM for hierarchical scalar spectra. Using multiple light mass $M_h$ benchmarks, we demonstrate that such analysis can explore a large region of the parameter space, with the $2σ$ exclusion reach for the heavy scalars extending up to $\sim 540$ GeV ($\sim$ 365 GeV) at the HL-LHC with 3000 fb$^{-1}$ (LHC with 300 fb$^{-1}$) luminosity for light scalar masses in the range $30$--$70$ GeV. Furthermore, we show that significant sensitivity and even resonance reconstruction can be achieved within a model-independent framework, highlighting the robustness of this search strategy.

This paper aims to clarify conceptual aspects of emergent structure in IKKT-type matrix models. Even without any adjustable parameters in the action, non-trivial matrix vacua do acquire a meaningful coupling constant, as well as two distinct uncertainty scales: a) the scale of noncommutativity of the matrix background, and b) the scale of quantum fluctuations of the matrices under the path integral. These scales are estimated for two prototypes of matrix backgrounds, known as Moyal-Weyl quantum plane and covariant quantum spacetime. Their relative importance separates two regimes: 1) the semi-classical regime interpreted in terms of semi-classical noncommutative geometry, and 2) the deep quantum regime usually interpreted in terms of holography. The quantum fluctuations are shown to be negligible in the weak coupling regime. This justifies previous work on the emergent 3+1-dimensional semi-classical geometry and (quantum) gravity in suitable vacua.

We present an implementation of Higgs-boson production in association with a hard, isolated photon via vector-boson fusion in the framework of the POWHEG BOX for the consistent matching of next-to-leading order QCD corrections with parton showers. The impact of parton-shower settings and non-perturbative effects on Higgs observables is studied and found to be small, while larger corrections are found for distributions of the sub-leading jets. Various approaches for the isolation of the photon are explored. For typical setups, the isolation strategy is found to have little impact on even the most sensitive observables.

Rational-function simplification is key bottlenecks in integration-by-parts (IBP) reduction of Feynman integrals. We study denominator factorization patterns appearing in IBP coefficients and develop practical algorithms for extracting and exploiting factorized denominator structure within the FUEL interface. The resulting workflow reduces reconstruction cost and improves robustness of large-scale reductions.

We consider the two-fermion $F_a F_b$ productions and decays via one mediator exchange at the $e^+e^-$ collider. With the assumption that the spin is defined via the Lorentz symmetry, or considering the implicit symmetry in the spin density matrix, we prove that the trace ${\rm Tr} [C]$ of the spin correlation matrix $C$ is an invariant quantity, and is invariant under basis rotations. Thus, for the exchanges of one mediator such as scalar and gauge boson, we can determine the product of the spin-analyzing powers for $F_a F_b$ via ${\rm Tr} [C]$, and reconstruct the spin correlation matrix. With the CHSH-Horodecki criterion, we can probe the Bell non-locality, and evade the no-go theorem. To be concrete, we study the Bell non-locality for the $Λ\bar Λ$ productions and decays at the BESIII experiment. In addition, the invariant ${\rm Tr} [C]$ is a new physics observable to probe the new physics beyond the Standard Model (SM) and study the SM precision measurements. Moreover, for the scalar exchanges, we discuss the general invariants of the spin correlation matrices and the related phenomenological consequences.

We present a metric on the space of scattering events based on relative transverse momenta and with explicit sensitivity to intermediate resonances. With this new metric, negative weights in an event sample can be reduced substantially through cell resampling, while preserving the predicted properties of the resonance with high accuracy. We demonstrate the efficiency on a NLO event sample for the production of a leptonically decaying W boson together with two jets.

We review a framework for the conformal bootstrap that does not rely on positivity and treats the infinite tower of high-dimension OPE contributions to conformal correlators through dispersion relations and neural networks. We apply it to scalar thermal two-point functions on $S^1\times \mathbb R^{d-1}$. We discuss the stability properties of the relevant non-convex optimisation scheme and potential relations to recent discussions of smoothness properties in CFT correlators. We illustrate the numerical application of the method to Generalized Free Fields and 4d holographic CFTs. This is a proceedings contribution to the ``Athens Workshop in Theoretical Physics: 10th Anniversary", held at the National and Kapodistrian University of Athens on December 17-19 2025.

We present the prospects for measuring $H\to \rm{invisble}$ decays at the Future Circular Collider electron-positron at $\sqrt{s} = 240 \text{ GeV}$ with an integrated luminosity of 10.8 ab$^{-1}$. In this study, we consider the $ZH$ production mode with three decay modes of the $Z$ boson: $Z\to e^+e^-$, $Z\to μ^+μ^-$ and $Z\to jj$ ($b\bar{b}, c\bar{c}, s\bar{s}, q\bar{q}$). We find that at 95\% confidence limit, the combined upper limit on the $\mathcal{B}(H\to invisible)$ could reach 0.15\%.

We study the sensitivity of the Compact Linear Collider (CLIC) to an additional neutral Higgs boson $H$ through the vector boson fusion process $e^+e^- \to Hν\bar ν$, followed by the decay $H \to W^+W^-$, with both $W$ bosons decaying leptonically, resulting in a dilepton plus missing transverse energy final state. Within the framework of the Two Higgs Doublet Model, where both production and decay are governed by the Higgs mixing angle $\cos(β-α)$, we perform a detector-level analysis and show that a high-energy CLIC can probe $H$ via this channel, allowing a direct measurement of the $HWW$ coupling.

Generalized parton distributions (GPDs) serve as indispensable tools for the exploration of proton structure. In this study, we offer a deep learning-assisted framework for the extraction of GPDs from experimental data and the results of ab-initio lattice quantum chromodynamics (LQCD).

I review the Feynman-Wiener path-integral formalism for diffusion with drift and jumps.

We study Majoron dark matter (DM) in its minimal realization, based on the Type-I seesaw framework extended by a SM-singlet complex scalar. Remaining agnostic about the origin and value of the Majoron mass, we evaluate the DM abundance from both the freeze-in and misalignment mechanisms, and identify the viable parameter space consistent with observational constraints. Without fine-tuning of the initial misalignment angle, we find that the Majoron mass is bounded by $m_J \lesssim \mathcal{O}(10)~\mathrm{MeV}$. We also discuss compatibility with thermal leptogenesis. Successful leptogenesis with two right-handed neutrinos favors misalignment-dominated production with the Majoron mass $m_J \lesssim \mathcal{O}(100)~\mathrm{eV}$, while freeze-in dominated production is compatible with leptogenesis only with a mild fine-tuning of the initial misalignment angle, $θ_i \lesssim \mathcal{O}(0.01)$.

In his 1999 preprint "Universal Lie Algebra", P. Vogel put forward a hypothesis on the existence of a universal Lie algebra. Although this hypothesis remains open, it is known that many quantities in Lie theory admit universal descriptions. Remarkably, almost all such universal formulas have been obtained through the representation theory of simple Lie (super)algebras, whereas Vogel's original framework was based on a more abstract diagrammatic algebra. Nevertheless, the diagrammatic approach has received little attention over the past two decades, since the last contributions by P. Vogel and J. Kneissler. In this work, we revive the diagrammatic technique grounded in Vogel's $Λ$-algebra and show that it enables truly universal computations. We examine numerous examples and discuss them.

We analyze the radiative decays of the the 1$P$, 1$D$, 2$S$, and 2$P$ $Λ_c$ and 1$D$, 2$S$, and 2$P$ $Ξ_c$ charmed baryons, which belong to the flavor anti-triplet ($\bf {\bar 3}_{\rm F}$), using the constituent quark model. We compute electromagnetic transitions from ground and $P$-wave states to ground states, as well as from second-shell states to both ground and $P$-wave final states. Electromagnetic decay widths are especially valuable for identifying resonances when multiple states share the same mass and total decay width. We give branching ratios which can confirm the assignment of the $Ξ_c(3055)$ reported by LHCb. We also give branching ratios that can support the assignment of the $Ξ_c(3080)$, and discuss the possibilities for the $Ξ_c(3080)$ to be the 1$D$ state with $J^P=5/2^{+}$ or the 2$S$ with $J^P=1/2^{+}$. For the first time, this work provides calculations of electromagnetic decays for $D_ρ$-wave states, $ρ-λ$ mixed configurations, and $ρ$-mode radially excited states in singly charmed baryons of the flavor anti-triplet. Both experimental and model-dependent uncertainties are taken into account throughout our analysis.

We formulate out-of-equilibrium jet momentum broadening in QCD effective kinetic theory through a moment expansion of the medium distribution function, a method traditionally used to derive relativistic viscous hydrodynamics from kinetic theory. We explicitly compute the leading near-equilibrium contribution to the spatial jet broadening tensor $\hat q^{ij}$ within the 14-moment approximation, and show that it is controlled by the medium shear-stress tensor. This provides a direct map from QCD effective kinetic theory to event-by-event viscous hydrodynamic simulations, converting local shear-stress fields into anisotropic corrections to jet broadening in heavy-ion collisions.

We report experimental evidence for electron neutrino charged-current interactions (neutrino absorption, CC $ν_e$) from $^{8}$B solar neutrinos on $^{40}$Ar using an exposure of ($7.29 \pm 0.05$) tonne$\cdot$years in the DEAP-3600 detector. A region of interest (ROI) of 10.5-13.0 MeV reconstructed energy calibrated on single-peak events, corresponding to incident neutrino energy in 12.0-14.5 MeV, is used for this measurement. We observe 5 single-peak and 1 double-peak neutrino-like events consistent with the $^{8}$B solar neutrino energy spectrum in the ROI after correcting for nonlinearities in the detector response at high energies. With an expected background of $0.48~^{+0.16}_{-0.15}$ events, the data correspond to a significance of $4.0\,σ$ with respect to the background-only hypothesis. We report an energy-averaged cross section of $(4.0~^{+2.0}_{-1.6}~\mathrm{(stat)}~^{+0.8}_{-0.7}~\mathrm{(sys)})\times 10^{-41}\,\mathrm{cm}^2$ in the ROI for the CC $ν_{e}$ signal, a factor $(2.4~^{+1.3}_{-1.0})$ higher than predicted by Bhattacharya, Goodman and García (2009).

Radioactive molecules provide a powerful new platform in the search for new physics at energy scales complementary to high-energy particle colliders. By combining enhancements from nuclear properties with the sensitivity and control offered by molecular structure, experiments with radioactive molecules offer great reach in the search for new physics beyond the Standard Model. Rapid progress in this field is being driven by advances in the production and control of radioactive molecules, alongside the development of new experimental tools and theoretical techniques. In this Perspective, we discuss the current status and future prospects of this rapidly developing, interdisciplinary field at the intersection of nuclear physics, atomic and molecular physics, and particle physics.

We study quantum chaos in $\textrm{T}\overline{\textrm{T}}$-deformed two-dimensional conformal field theories with gravitational anomaly and their holographic dual description in topologically massive gravity. Using pole-skipping and shock-wave analysis, we extract the Lyapunov exponent and butterfly velocity and analyze the interplay between irrelevant deformation and parity-violating dynamics. We find that the chaos bound remains saturated, while the butterfly velocity exhibits nontrivial dependence on the deformation parameter and anomaly. We also identify a Hagedorn regime in which the chaotic response becomes complex valued, signaling a breakdown of the physical branch of the deformed theory.

We report on a nine-month monitoring campaign of the blazar PG 1553+113, relying on three observations carried out in 2025 with the Imaging X-ray Polarimetry Explorer (IXPE) and supported by multi-wavelength facilities. The source displayed pronounced variability across the electromagnetic spectrum, with X-ray flux changes by up to a factor of $\sim5$ and complex evolution of the optical polarization properties, including one of the largest (exceeding $150^{\circ}$) and fastest rotations in the electric vector position angle (EVPA) ever recorded. This swing of the EVPA was also accompanied by a temporary drop of the optical polarization degree to nearly zero. Significant X-ray polarization was observed during the third IXPE pointing, with a polarization degree $Π_{\rm X}\,=(\,18.4\,\pm\,5.8)\%$ and $Ψ_{\rm X}\,=\,74^{\circ} \pm 9^{\circ}$ in the 2--8~keV band, while only upper limits were obtained in the first two epochs. The optical data show that the second IXPE observation occurred shortly after a dramatic optical polarization event characterized by a rapid EVPA swing and strong depolarization. Two possible scenarios may explain the broadband polarimetric behavior: (i) the superposition of two emitting regions with nearly orthogonal magnetic field configurations and variable relative contributions, and (ii) the interaction of a single emitting region with a shock that temporarily reorders the magnetic field. In both cases, the data support a picture in which the X-ray and optical emissions arise from closely related but not strictly co-spatial regions within a dynamically evolving, magnetically structured jet.

We study gauging interfaces and their defect descendants in lattice models with generalized symmetries in higher dimensions. We construct explicit interface Hamiltonians for gauging a $\mathbb Z_2^{(0)}$ symmetry in $(2+1)d$ and a $\mathbb Z_2^{(1)}$ symmetry in $(3+1)d$. In higher dimensions, and especially in the presence of higher-form symmetries, the topological nature of gauging interfaces is obscured by the fact that the constrained Hilbert space depends on the location of the interface. We resolve this by introducing movement operators acting on a common unconstrained Hilbert space, which transport both the interface Hamiltonians and the associated constraints. As applications, we analyze condensation defects obtained from finite-region gauging and reconstruct the gauging map from movement operators. Finally, we apply the same framework to subgroup gauging, focusing on the example of gauging $\mathbb Z_2\subset \mathbb Z_4$. This produces a dual symmetry carrying a mixed anomaly, which we diagnose on the lattice through symmetry fractionalization on condensation defects. Our results provide an explicit lattice framework for studying topological interfaces, condensation defects, and the associated anomalies arising from gauging in higher-dimensional systems.

Center one-form symmetries in consistent quantum gravity theories are expected to be either broken or gauged, thereby determining the global form of the gauge group. We shed light on this expectation from the perspective of distinguished extended objects, which we denote by faithful string probes, for which the gauge symmetry is realized as a holomorphic current algebra. We argue that the worldsheet counterpart of gauged center one-form symmetries is the existence of chiral simple currents extending the current algebra. Accordingly, we show that the consistency condition for such extensions reproduce and generalize known field theoretic and geometric obstructions to the gauging of center one-form symmetries in six and eight dimensions. We verify this picture in a number of examples arising from heterotic string compactifications, and apply it to infer the gauge group topology of a recently identified class of six-dimensional models with no known F-theoretic realization. In 6d supergavity, our results also clarify an observation of Kim and Vafa on the existence of BPS particles required for consistency upon circle reduction: these particles arise from worldsheet simple currents whose existence is dictated by the presence of a gauged center one-form symmetry. Intriguingly, in several models across different dimensions we find composite higher-spin chiral currents beyond the current algebra, hinting at a stringy generalization of center one-form symmetries in the bulk.

Tidal stripping is a key feature of the evolution of dark matter (DM) halos, and has major implications for the population of low-mass galaxies. In the case of ultralight DM, tidal stripping proceeds not only classically, at the tidal radius, but also via a process analogous to quantum tunneling by long-wavelength particles out of the potential of a subhalo. This modified tidal stripping behavior leads to tight constraints on the particle mass as a function of subhalo and host properties. As many models of ultralight DM predict several independent species, it is crucial to understand how these constraints can be generalized to multifield halos with different particle masses. However, numerical challenges make it difficult to directly study the tunneling process in all but the simplest multifield scenarios. We introduce a simplified approach based on semiclassical methods that entirely sidesteps the most difficult aspects of the numerical problem, and we apply this to the study of tunneling in multifield halos. Our results significantly clarify the physics of tidal stripping for ultralight DM halos even in the single-field case: we provide first-principles derivations of features of the tunneling rate previously suggested by empirical fits. We then evaluate stability bounds on two-field halos for the first time, for a wide range of density and particle mass ratios. We show that for particular parameter combinations, the stability bounds in the two-field case can be somewhat relaxed relative to the single-field case, but for much of the parameter space, the constraints become more stringent. We discuss the path towards probing realistic multifield ultralight DM halos.

We consider a model of 3d quantum gravity defined by $n$ copies of a rational Virasoro TQFT with central charge $1/2$, summed over all 3d topologies. This theory is holographically dual to an ensemble of all 2d CFTs with central charge $c=n/2$ and chiral algebra that includes $Vir_{1/2}^n$. We perform the sum over topologies and evaluate the partition function of the bulk theory. We then confirm the holographic duality by matching it to the boundary ensemble for small $n$. We proceed to consider the limit of a large central charge, in which the bulk theory simplifies and condenses to an Abelian phase. In this regime, the model manifests many features expected in semiclassical 3d quantum gravity. In particular, inclusion of all 3d topologies in the bulk sum cures the negativity of the density of states evaluated by the torus partition function. The model also exhibits a Hawking-Page transition, an exponentially suppressed wormhole amplitude, and provides a toy example of the holographic code. We discuss these aspects in detail and conclude with lessons for semiclassical quantum gravity.

Studies of the properties of the Quark-Gluon Plasma in high-energy heavy-ion collisions commonly facilitate proton-proton (pp) collisions at the same center-of-mass energy per nucleon pair as a reference measurement. In this paper, a deep neural network-based approach for interpolating and extrapolating pp reference transverse-momentum spectra to unmeasured energies is presented. The model is trained with ALICE data from LHC Runs 1 and 2 and provides predictions for center-of-mass energies relevant to LHC Run 3 and beyond.

Neural network field theory (NN-FT) formulates field theory in terms of a network architecture and a density on its parameters. We derive Schwinger--Dyson equations and Ward identities in NN-FT and utilize them to study anomalies. The equations depend on a conserved parameter space current that characterizes symmetries and how they break. It is relevant even in non-local NN-FTs, but can recover local currents in the case of a local Lagrangian by an appropriate fiber-wise average. In machine learning, this formalism is applied to feedforward networks and the attention mechanism. In physics, we use this machinery to study $U(1)$ symmetry for a complex scalar, the scale anomaly in $4d$ massless $φ^4$ theory, the Weyl anomaly for the bosonic string (including a new computation of the critical dimension), and examples involving discrete topological data, such as winding numbers and T-duality. Since the results are obtained in network parameter space rather than the standard field space, they represent a new way to understand symmetries in quantum field theories.

Following Veltman's approach, we formulate and discuss a general cutting equation for QED in a plane-wave background. We apply the corresponding cutting rules to justify the connection between the two-loop radiative corrections to elastic electron scattering and the rate of the trident process in a constant crossed field. As a byproduct, we compare the previously published results for the trident process in a constant crossed field and present a complete analytical expression for direct and exchange contributions to its rate, which is resolved in the spin of the initial electron. Our findings establish that although total rates can be reliably extracted from higher-loop by applying the cutting rules, reconstruction of differential rates requires additional care. The cutting rules apply to any loop order and may be extended to nonperturbative regimes.

We discuss various forms of refinements of Vogel's universality in Chern-Simons theory. While the original universality applies to arbitrary simple Lie groups, its counterpart in refined Chyrn-Simons theory is restricted to simply laced Lie groups.

Its cornerstone were studies of hadron production in deep inelastic scattering (DIS), which can be interpreted in the transverse-momentum-dependent (TMD) factorisation framework, allowing to access the distributions of polarisation and transverse momentum of quarks within the nucleon in the language of TMD PDFs, and the hadronisation in terms of TMD fragmentation functions. The data collected with a liquid hydrogen target in 2016-2017 will soon bring new information on the transverse momentum and may allow for the first time to extract the transverse polarisation of quarks within an unpolarised nucleon described by the Boer-Mulders function. The unique data collected with a transversely polarised deuteron target have already improved the knowledge of the d-quark transversity (transverse counterpart of the helicity PDF), reducing the uncertainties by a factor of 2.5 at large Bjorken x, and are yet to yield a number of interesting results.

We observe that the null string action possesses a previously overlooked local symmetry. By correctly accounting for this symmetry, we show that the number of physical propagating degrees of freedom of null strings in $D$ dimensional target space is $D-3$, in contrast to $D-2$ that one finds in the literature. Overlooking this symmetry has led to an unphysical over-counting of states, rendering the null string analyses inconsistent. Thus, our observation calls for a thorough revision of all statements and results in the null string literature.

Future $e^+e^-$ colliders at the Z pole place strong demands of $\frac{δL}{L}<10^{-4}$ on the integrated luminosity measurement. Small angle Bhabha scattering (SABS) remains the standard channel, while diphoton ($γγ$) events provide a complementary measurement. This contribution summarizes recent work on two dominant uncertainties. First, we investigate backgrounds to the diphoton channel and find that SABS and low-invariant-mass neutral hadrons are the most significant backgrounds. A gradient boosted decision tree (BDTG) is used to classify events by particle ID. The classification results show the existing and upgraded forward tracker and luminosity calorimeter (LumiCal) designs reject neutral hadrons but only the LumiCal upgrade can reject SABS at $\frac{δL}{L}<10^{-4}$. Second, we solve the beam deflection bias problem on an event-by-event basis using two machine learning algorithms. A BDTG and the newly written Adaptive Symbolic Memetic Regression (ASMR) are trained on beam deflection data. ASMR outperforms BDTG and provides a reduced uncertainty of $5\times10^{-6}$ for beam deflection.

We review the construction of higher-form symmetries for supersymmetric theories using a supergeometry framework. This reveals an enlarged set of topological conserved supercurrents, including Chern-Weil symmetries and new geometric Chern-Weil symmetries built from invariant supermanifold forms. In N=1 super-Maxwell theory in three dimensions, we construct the corresponding operators and charged defects, with charges determined by a super-linking number between their supporting hypersurfaces. At the end we provide as an original unpublished contribution some hints on how to construct super-symTFT for Chern-Weil and geometric Chern-Weil symmetries directly from supergravity.

Quasi parton distribution functions (QPDFs) are defined in terms of QCD fields at spacelike separations evaluated in matrix elements of hadrons moving with velocity $v$. These objects can be studied in lattice QCD. In the limit when $v$ approaches the speed of light, QPDFs converge to PDFs. It is insightful to study QPDFs and their convergence in models. In this work, we first study the QPDFs in a broad class of quark models characterized by one common feature, namely the absence of gauge degrees of freedom. We provide general proofs for the convergence and sum rules of the unpolarized quark and antiquark QPDFs for both choices $γ^0$ and $γ^3$. We choose the Covariant Parton Model (CPM) as an illustration. We derive analytical results for the small-$x_v$ behavior of QPDFs and the energy-momentum tensor form factor $\bar{c}^q(t)$ at zero momentum transfer. These results are of interest as they correspond to a Wandzura-Wilczek-type approximation.

In this paper, we draw a parallel between solutions of pure three-dimensional gravity with a negative cosmological constant and classical double copies in four dimensions. In the former case, topological solutions, such as the BTZ black hole, deficit angles, and naked singularities, emerge from identifying points in AdS using elements from its isometry algebra $so(2,2)$. The type of solution corresponds one-to-one with the orbits of $so(2,2)$. We demonstrate how various double copies of four-dimensional AdS gravity similarly arise from the $so(2,3)$ isometry elements, which also correspond one-to-one with their orbits through a Penrose-type transform. We classify all such elements and generate the corresponding double copies, which include AdS black holes, black branes, and many others. The double-copy isometries originate from the centralizer of a given AdS isometry, allowing us to define canonical coordinates associated with its Abelian part. Additionally, the two Casimir invariants of $so(2,3)$ feature in the metrics. Our classification naturally extends to higher spins, providing nonequivalent multicopies at the linearized level.

In this work, we provide a novel method to constrain the causal parameter space of a relativistic hydrodynamic system exclusively from its linear stability analysis at non-zero momenta. Our approach exploits the Lorentz-invariant stability property of causal theories. In boosted frames, the dispersion relation exhibits a feature that we call ``$γ$-suppression,'' whereby the higher-order terms in the wavenumber expansion are increasingly suppressed beyond leading order at large boosts. As a consequence, at near-luminal values of Lorentz boost, stability criteria at the spatially homogeneous limit are sufficient to identify the region of the parameter space that satisfies the necessary conditions of causality, even at non-zero momenta. After presenting the general hydrodynamic framework, we test the method in conformal Müller-Israel-Stewart theory and show that it provides an efficient way of deriving the necessary conditions of causality while remaining within the low-energy regime of hydrodynamic validity.

The existing analyses on the X(3872) lineshape are consistent with the hypothesis that it is a compact particle composed of four quarks. This conclusion follows from fitting available data with a Flatte' distribution derived from an effective Lagrangian in which X, D, and D* are all elementary fields. A molecular X, i.e., a deuteron-like bound state of D and Dbar*, must instead be described by an effective theory where the X field is initially absent or introduced as an auxiliary, unphysical, field, yielding a lineshape parametrization that differs significantly from the Flatte' one. We demonstrate, in the analogous theory of nucleons with an auxiliary deuteron field, that this parametrization gives a fully consistent description of np--> deuteron --> np scattering data, and motivate applying the same method to the X lineshape.

We present novel, ultra-thin, large-diameter silicon nitride windows for various soft X-ray applications. Together with the company NORCADA, we developed windows with 200 nm and 300 nm thickness withstanding pressure differences above 1 bar. The windows have an open diameter of 14 mm. They were intensively vacuum- and overpressure-tested, showing very good results. At a measurement campaign at the synchrotron radiation source SOLEIL in France, the transparency of the windows was measured over a range from 50 eV to 15 keV, giving results comparable with the expected transparencies.

The LHC physics programme involves a vast amount of Monte Carlo event simulation. This paper reviews current efforts towards sharing the generated events as Open Data. Open Event Generation helps reduce duplication of effort and resource consumption, and benefits the whole High Energy Physics community. We give examples of use cases and user experiences, discuss financial and environmental savings, and suggest future directions.

We compare the isospin-one, vector-current hadronic vacuum polarization (HVP) obtained from isospin-symmetric lattice QCD with that obtained from a dispersive representation employing inclusive hadronic $τ$ decay data corrected for isospin breaking. We consider the subtracted HVP evaluated at squared Euclidean momenta ranging from $0.5$ GeV$^2$ to $12$ GeV$^2$, together with the light-quark-connected HVP contribution to the muon anomalous magnetic moment and the short-, intermediate- and long-distance RBC/UKQCD window components thereof. Dispersive contributions from the region of hadronic invariant masses above the $τ$ mass are evaluated using perturbative QCD. We also consider dispersive determinations using $τ$ data only for contributions from two-pion, or two-pion and four-pion, modes, and evaluating the remaining contributions using exclusive-mode $e^+e^-\to\mbox{hadrons}$ cross sections up to about 2 GeV, lessening the dependence on perturbation theory. We find generally good agreement between lattice and $τ$-based results. However, a comparison of $τ$-based window-quantity contributions for the two four-pion modes to expectations for those contributions based on the Pais relations and $e^+e^-$ four-pion cross sections, reveals significant differences for the $2π^-π^+π^0$ mode.

The photoproduction of $J/Ψ$ in peripheral Oxygen - Oxygen ($OO$) collisions at the Large Hadron Collider (LHC) is investigated considering distinct assumptions for the modeling of the nuclear photon flux, overlap function and dipole - proton scattering amplitude. Predictions for the associated rapidity distributions and total cross - sections are presented. Our results indicate that the experimental study of the photoproduction of $J/Ψ$ in peripheral $OO$ collisions is, in principle, feasible. In addition, they point out that the combination of the results for this final state in $OO$ collisions with those obtained for $PbPb$ collisions will allow us to derive important constraints on the description of photon - induced process at peripheral collisions.

In this work, Podolsky theory, a second-order, Lorentz- and gauge-invariant extension of classical electrodynamics, is considered. The effects of Podolsky's modification on fundamental phenomena such as the Stefan-Boltzmann law and the Casimir effect for the electromagnetic field are investigated. The Thermo Field Dynamics (TFD) formalism is employed to describe quantum fields at finite temperature and under spatial confinement through its topological structure.

We present the results of a large number of simulation studies regarding the power of various goodness-of-fit as well as non-parametric two-sample tests for multivariate data. In two dimensions this includes both continuous and discrete data, in higher dimensions continuous data only. In general no single method can be relied upon to provide good power, any one method may be quite good for some combination of null hypothesis and alternative and may fail badly for another. Based on the results of these studies we propose a fairly small number of methods chosen such that for any of the case studies included here at least one of the methods has good power. The studies were carried out using the R packages MD2sample and MDgof, available from CRAN.

The Hybrid Elevated Radio Observatory for Neutrinos, or HERON, is a newly proposed ultrahigh energy Earth-skimming tau neutrino detector. Ultrahigh energy tau neutrinos which skim the Earth may produce $τ$-leptons which escape into the atmosphere and initiate up-going extensive air showers. The HERON concept consists of 24 compact phased radio arrays, embedded within a larger sparse array of 360 standalone antennas, distributed along a mountain range and designed to capture the radio emission of these up-going extensive air showers. Due to the high elevation observation sites and the long propagation length of radio, HERON achieves a very large instantaneous effective area towards the horizon, and thus excels at the detection of astrophysical transient events such as gamma-ray bursts. With the excellent pointing resolution offered by the sparse array, HERON would be capable of conducting UHE neutrino astronomy and could be incorporated into the broader network of multi-messenger instruments. Here, we detail the HERON concept and describe the science which can be accomplished with it.

We study semileptonic $B$ meson decays $B^+ \to D_1^{(\prime)}\ell^+ν_\ell$ and $B_s^0 \to D_{s1}^{-(\prime)}\ell^+ν_\ell$, where $\ell=μ,τ$. The final state axial vector mesons are treated as mixtures of the heavy quark basis states with light degree of freedom angular momenta $j_\ell=1/2$ and $j_\ell=3/2$, parametrized by the mixing angle $θ_{D_1}$. Using form factors obtained in the covariant light front quark model, we analyze the dependence of various observables on $θ_{D_1}$ such as polarized and unpolarized branching ratios, the lepton forward-backward asymmetry, the longitudinal polarization fraction, and the lepton flavor universality ratios. In addition, we also discuss correlations among different observables. We study these observables in the experimentally motivated mixing angle regions as well as over a wider range of $θ_{D_1}$. Our results show that branching ratios and other observables are sensitive to the axial-vector mixing structure. These predictions provide useful Standard Model benchmarks for future measurements of semileptonic $B_{(s)}$ decays into orbitally excited mesons and may help to clarify the long standing $1/2$ vs. $3/2$ puzzle in semileptonic $B$ decays.

We explicitly present all coupling conditions required for tree-level unitarity (tree unitarity) in theories with a finite number of massive and massless particles of spin up to 1. They allow us to diagnose tree unitarity of a system using only its particle content in the mass basis, without reconstructing the full Lagrangian. We show that all four-point amplitudes whose high-energy growth is canceled by tree unitarity conditions are on-shell constructible, thereby motivating the recursive construction of four-point amplitudes. By examining their high-energy growth, we derive tree unitarity conditions for four-point amplitudes. Imposing these conditions to simplify the Lagrangian structure, we use the Stückelberg formulation to derive the tree unitarity conditions arising from all higher-point amplitudes. We show that all tree unitarity conditions are fully captured up to five-point amplitudes, ensuring no necessity of examining higher-point ones. We apply our results to systematically examine tree unitarity conditions in the dark sector with a massive dark photon and dark matter particles of spin up to 1, and extract the essential features for mass generation in the massive dark photon case. In addition, we show that our results allow us to conclude that theories without scalars require an infinite tower of vectors and fermions for tree unitarity. Finally unitarity and related issues in the Higgs portal VDM are discussed in brief.

Top and anti-top quark pair production at LHC provides a unique setting to probe non-classical correlations at the TeV scale. We study quantum information (QI) properties of the $t\bar{t}$ spin state in $pp$ collisions at $\sqrt{s}=13$ TeV within the Standard Model Effective Field Theory (SMEFT), focusing on dimension-6 operators that induce anomalous chromo- and weak dipole moments of the top quark within their current experimental bounds. The $t\bar{t}$ spin density matrix is reconstructed from the joint angular distribution of the final state charged leptons in the $k$-$r$-$n$ helicity basis. We analyze three complementary QI quantities: concurrence-based quantum entanglement (QE), geometric quantum discord (GQD), and the Bell parameter,across four $t\bar{t}$ invariant-mass bins. Within the Standard Model (SM), non-vanishing QE appears only near threshold ($m_{t\bar{t}}\lesssim 400$ GeV), while GQD remains nonzero across the full phase space, indicating persistent non-classical correlations even for separable states. Anomalous chromo-dipole interactions modify these observables primarily near threshold: $\hatμ_t$ induces asymmetric shifts, whereas $\hat{d}_t$ produces a mild symmetric response without Bell inequality violation. Among weak dipole operators, the CP-even coupling $C_2^V$ generates the largest deformation of the QI observables, while $ΔC_1^{A,V}$ leave them unchanged. These results demonstrate that QI observables derived from the $t\bar{t}$ spin density matrix provide a complementary probe of anomalous top-quark interactions with distinct sensitivity to CP-even and CP-odd operator structures.

Based on relativistic mean field theory for atomic nuclei, we compute the mass radius and other radii associated with the energy momentum tensor for dozens of spin-0 nuclei across the nuclear chart. We also compute the D-term of these nuclei, the forward limit of the gravitational form factor $D(t=0)=D$. The dependence on the neutron number $N$ is systematically studied for calcium (Ca), nickel (Ni), zirconium (Zr), tin (Sn) and lead (Pb) isotopes. Remarkably, $|D|$ does not monotonically increase with $N$. Instead, it exhibits local maxima and minima when $N$ equals a magic number and even a sub-magic number. This results in characteristic kinks in the mass, scalar, tensor and shear radii of these isotopes. Our work for the first time elucidates the strong sensitivity of the various mechanical properties of nuclei to the nuclear shell structure.

High-granularity calorimeters make ML-based fast shower simulation a high-dimensional generative modeling problem, where voxel-space generators must balance physics fidelity with training and inference cost. This work studies large-patch tokenization with x-prediction, enabling efficient raw voxel generation. We propose CaloArt, a modernized DiT-style backbone with 3D positional encoding and architectural refinements, trained via conditional flow matching with decoupled prediction and loss spaces. On CaloChallenge Dataset 2, where small patch size remains affordable, v-prediction performs well, and CaloArt achieves the best FPD, strongest high-level metrics, and strongest ResNet classifier metrics. On CaloChallenge Dataset 3, the 40500-voxel grid makes large patches necessary; x-prediction improves all reported metrics over v-prediction and places CaloArt on the quality-generation-time Pareto frontier. The final CCD2 and CCD3 models both retain O(10) ms single-GPU generation time, with 9.71 and 11.14 ms per shower. These results support large-patch voxel-space diffusion transformers with x-prediction as a compute-efficient route to high-granularity calorimeter shower synthesis, reducing training and inference cost without a pretrained latent tokenizer.

Recent clinical evidence shows a correlation between linear energy transfer (LET) and tumor control in carbon ion radiotherapy. This prompts the direct inclusion of LET into the treatment planning. Currently, LET is mainly extracted from simulations. Good clinical practice requires adopting measurement routines that correlate with LET, such as microdosimetry. In this work, we describe an application-specific integrated circuit (ASIC) for reading out microdosimeteric sensors. The ASIC is designed for input capacitances up to 3 pF. It contains four readout channels, each with a different saturation charge ranging from 75 fC to 3.2 pC. In the 75 fC range, at 1 pF input capacitance and a shaping time of 1 microseconds, the ASIC has an equivalent noise contribution (ENC) below 15 electrons at ambient temperature. This low noise level is expected to enable new measurement possibilities, including the assessment of microdosimetric proton spectra in the low-LET region of the entrance channel, as well as studying the contribution of delta electrons.

A compact analytical scheme is presented for describing ultra-dense hadronic matter, which combines a multicomponent van der Waals (vdW)-type description with temperature-dependent effective degrees of freedom. Although the vdW formalism successfully reproduces interactions at finite density, in its standard form it cannot describe lattice-QCD thermodynamics, since it uses a fixed degeneracy. It is shown that a consistent description of the equation of state requires a temperature-dependent degeneracy $g(T)$ and an effective chemical potential $μ(T)$. Within this approach, the trace anomaly (the trace of the energy-momentum tensor), i.e. the measure of nonconformality of the energy-momentum tensor normalized to $T^4$, is naturally reproduced together with its peak structure near the crossover region. The effective chemical-potential sector becomes particularly important in baryon-rich matter, whereas for the mesonic sector a separate dynamical description of the degrees of freedom is required.

We study T-duality of $(p,q)$-hermitian geometries in backgrounds with non-Abelian gauge fields $A$ in heterotic string theories. We introduce a gauge-dressed complex geometry characterized by a shifted metric $\bar{g} = g + \frac{1}{2} \mathrm{Tr}(A^2)$, the closed 2-form $ω$ and a quasi complex structure satisfying $\bar{J}^2 < 0$, but not necessarily $\bar{J}^2 = -1$. Utilizing the positive and negative chirality half generalized complex-like structures constructed by $(\bar{g}, \bar{J})$, we derive a heterotic Buscher-like rule for geometric quantities. We also demonstrate that the gauge-dressed structures can be used to construct an extended Born geometry that satisfies algebras of hypercomplex numbers.

We present a study of cubic surfaces from the novel perspective of positive geometry. Our positive geometries have dimension two (the surface minus its 27 lines), dimension three (its complement in 3-space), and dimension four (the moduli space). In each case we explore the positive arrangement, its combinatorial rank, and the canonical forms.

Parton shower evolution is given by a renormalization group equation that reflects the infrared behavior of perturbative QCD including color and spin and including quantum interference. With added approximations, such an evolution equation can provide the basis for a parton shower event generator. To date, splitting functions for parton shower evolution have been derived only to leading order in $\as$. We provide a framework that can provide splitting functions beyond leading order, and in particular at order $\as^2$. This requires a representation of Feynman graphs in which partons are off shell and are characterized by vector or spinor indices instead of on-shell spins.

We present model calculations for the in-medium suppression of the Y(1S,2S,3S) states in sqrt(s_NN)=5.02 TeV Pb-Pb collisions at the Large Hadron Collider in comparison with recent CMS data for all three spin-triplet s-wave states. The model parameters initial central temperature, and formation times for the Y(nS) states are determined in simultaneous chi^2 minimizations with respect to the data, such that the sequential centrality- and transverse-momentum-dependent suppression of the observed states is reproduced.

We present the computation of the next-to-leading order QCD corrections to the $pp\to t\bar{t} H+X$ process in the di-lepton channel at the LHC, including relevant dimension-6 operators $({\cal O}_{tφ}, \, {\cal O}_{φG},\, {\cal O}_{tG}, \, {\cal O}_{tW})$ from the Standard Model Effective Field Theory. In our studies, higher-order corrections and effective operators are consistently included in the production part of the process as well as in the top-quark decays. We perform a detailed study of linear, cross, and quadratic contributions and their uncertainties, including renormalisation group effects. Our findings are presented at the integrated and differential cross-section level for the LHC Run III center-of-mass energy of $\sqrt{s}=13.6$ TeV. Finally, we provide predictions for $pp\to t\bar{t} H+X$ with stable top quarks and compare them with the results in which top quarks are reconstructed from their decay products. We show that kinematic cuts, as well as higher-order effects and SMEFT operators in top-quark decays, are important and should be consistently considered together, because they have a significant impact on the shape of the standard observables measured for the $pp\to t\bar{t}H+X$ process at the LHC.

The CEBAF Large Acceptance Spectrometer for operation at 12 GeV (CLAS12) at the Thomas Jefferson National Accelerator Facility has played a central role in advancing the understanding of nucleon and nuclear structure. As increasingly precise data become available, new physics opportunities emerge that extend beyond the current capabilities of CLAS12. In this article, a program to explore the quark and gluon structure of the nucleon through di-muon electro- and photoproduction is presented. Its primary focus is the measurement of beam-spin asymmetries in Double Deeply Virtual Compton Scattering, $ep \rightarrow e^\prime μ^+ μ^-p^\prime $. By independently varying the incoming and outgoing photon virtualities and momentum transfer, the DDVCS measurement provides access to the Generalized Parton Distributions over their full three-dimensional phase space, extending beyond the kinematic constraints of Deeply Virtual Compton Scattering and Timelike Compton Scattering. In addition, the large acceptance and high luminosity of the $μ$CLAS12 experiment will enable precision measurements of near-threshold $J/ψ$ production and high-statistics studies of Timelike Compton Scattering.

We study the search prospect of long-lived heavy neutral leptons (HNLs) pair produced in decays of axionlike particles (ALPs) at the proposed Super Tau-Charm Facility (STCF), focusing on the center-of-mass energy of $\sqrt{s}=3.773$ GeV. The ALPs are assumed to originate from $D^\pm$-meson decays in association with a charged pion. We perform both truth-level and detector-level Monte Carlo simulations and obtain the expected sensitivity reach to the mixing parameter between the HNL and the electron neutrino, $|V_{eN}|^2$, with a displaced-vertex search at STCF. We find that STCF can probe values of $|V_{eN}|^2$ about one-to-two orders of magnitude beyond the existing bounds. We also perform an approximate reinterpretation of a search for HNLs at the CHARM experiment, which is subject to model-dependent assumptions on the production and kinematic distributions, and find that beam-dump experiments may provide strong complementary constraints.

Hyper-Kamiokande (HK) is the world's largest water Cherenkov ring-imaging detector, planning to start data taking in 2028. The Outer Detector (OD) surrounds the Inner Detector and plays a critical role in rejecting background events entering from outside, particularly cosmic-ray muons. We report on the selection of $8\,\mathrm{cm}$ diameter photomultiplier tubes (PMTs) for the OD, comparing Hamamatsu R14374 and NNVT N2031 candidates, and present the evaluation of cosmic-ray muon background reduction performance using a full detector simulation. Hamamatsu PMTs were adopted for their superior in-water detection efficiency in deep-UV and stability. The cosmic-ray muon reduction inefficiency reaches $O(10^{-6})$ with OD-based cuts alone, and $O(10^{-9})$ is expected when combined with fiducial volume cuts, which is sufficiently negligible for nucleon decay and atmospheric neutrino analyses.

In this paper, we determine the relativistic bound-state solutions for the Dirac oscillator (DO) in the curved spacetime of a cloud of strings in $(3+1)$-dimensions, where such solutions are given by the four-component normalized Dirac spinor and by the relativistic energy spectrum. However, unlike in literature, here, we work with the spacetime in two different forms/configurations, that is, both in its original form and in its modified form. To achieve our objective, we work with the curved DO in spherical coordinates, where we use the tetrad formalism. So, by defining a stationary ansatz for the spinor, we obtain two coupled first-order differential equations, and by substituting one equation into the other, we obtain a second-order differential equation. To analytically and exactly solve this differential equation, we use a change of function and of variable. From this, we obtain the well-known Whittaker equation, whose solution is the Whittaker function. Consequently, we obtain the energy spectrum, which is quantized in terms of the radial quantum number $n$ and the angular quantum number $κ$, and explicitly depends on the angular frequency $ω$ (describes the DO), curvature parameter $a$ (describes the cloud of strings), and on the effective rest mass $m_{\text{eff}}$ (describes the rest mass modified by the curvature of spacetime). Besides, we graphically analyze the behavior of the spectrum as a function of $ω$ and $a$ for three different values of $n$ and $κ$, as well as the behavior of the radial probability density for four different values of $κ$, $ω$, and $a$ (with $n=0$).

The Aharonov--Casher (AC) effect describes the geometric phase acquired by a neutral particle carrying a magnetic dipole moment moving in an external electric field. In supersymmetric gauge theories it is often argued that exact supersymmetry enforces the vanishing of anomalous magnetic dipole moments, suggesting that the AC interaction may be incompatible with unbroken supersymmetry in four dimensions. In this work we show that this conclusion is model-dependent. We construct an $N=1$, $D=4$ supersymmetric gauge model in which a Lorentz-violating Kalb--Ramond background induces dynamically the dipole interaction responsible for the AC effect while leaving the supersymmetry algebra intact. The model couples a chiral superfield to an Abelian gauge superfield through a Chern--Simons--type interaction supplemented by a Fayet--Iliopoulos term. A duality identification between the symmetric combination $S+S^\dagger$ of the chiral superfield and the Kalb--Ramond superfield strength allows the antisymmetric tensor background to enter the supersymmetric dynamics without breaking supersymmetry. Integrating out the auxiliary $D$ field generates dynamically an effective dipole interaction of the form $\barψσ^{μν}F_{μν}ψ$. In the nonrelativistic limit the resulting equation of motion reproduces the Aharonov--Casher Hamiltonian for a neutral fermion. The effective magnetic dipole moment is expressed in terms of the parameters of the model and can be mapped onto tensor coefficients of the fermion sector of the Standard Model Extension. Our results therefore provide an explicit realization of a four-dimensional supersymmetric theory in which the Aharonov--Casher interaction emerges dynamically while supersymmetry remains exact in the presence of Lorentz violation.

We present the first amplitude analysis and branching fraction measurement of $D^{+} \rightarrow K_{S}^{0}K_{L}^{0}π^{+}$ decay. The analysis uses a dataset corresponding to an integrated luminosity of 20.3~$\rm fb^{-1}$, which was recorded at a center-of-mass energy 3.773~GeV by the BESIII detector. The measured branching fraction is $\mathcal{B}(D^{+} \rightarrow K_{S}^{0}K_{L}^{0}π^{+})=(5.780\pm0.085\pm 0.052)\times10^{-3}$, where the first uncertainty is statistical and the second is systematic. Using the known value of ${\cal B}(D^+ \to φπ^+,\,φ\to K^+K^-)$, we determine the relative branching fraction between $φ\to K_{S}^0K_{L}^0$ and $φ\to K^+K^-$ to be $\mathcal{B}(D^{+} \to φπ^{+}, φ\to K_{S}^0K_{L}^0)/\mathcal{B}(D^{+} \to φπ^{+}, φ\to K^+K^-)= 0.628\pm0.022\pm 0.015\pm0.017$, where the third uncertainty is related to $\mathcal{B}(D^{+} \to φπ^{+}, φ\to K^+K^-)$. This result is significantly lower than the previous world average and is consistent with the isospin expectation for the $φ$ meson's coupling to charged and neutral kaon pairs.

MeVPrtl is a modular event generator of beyond the Standard Model (BSM) physics particles developed for use in the Short-Baseline Neutrino (SBN) Program. A large class of BSM physics models predict that new particles could be produced in the intense Booster Neutrino Beam (BNB) and Neutrinos at the Main Injector (NuMI) beams at Fermilab, travel to the SBN Program detectors, and decay into Standard Model (SM) particles. These new physics models are motivated by dark matter, the neutrino mass scale, and a solution to the strong CP problem. MeVPrtl provides an interface to implement the overlapping phenomenology of these models, and to connect them with meson flux inputs and object outputs used by the SBN Program's LArSoft-based detector simulation. Implementations for the Higgs portal, heavy neutral lepton, and heavy QCD axion models exist within MeVPrtl. In this paper these implementations and their validation, as well as details of the MeVPrtl interface, are specified.

We construct a toy model of a nucleon, in which three static quarks interact via a SU(3) gauge field on a planar honeycomb lattice. The dynamics of the gauge field is described by the Kogut-Susskind Hamiltonian, truncated to the lowest three SU(3) irreducible representations. We show that the internal structure of the toy nucleon reflects salient features of the physical nucleon state. We then find the entanglement entropy of the gauge field within the nucleon state and compute its time evolution after a quench, in which all three valence quarks are suddenly removed. We show that the entanglement entropy in the final state is dominated by the dynamically generated contribution rather than the initial state entropy.

Recent theoretical developments revived the interest in charged particle multiplicities and their wide-spread parametrization, the negative binomial distribution (NBD). The central observable of the studies is the Shannon entropy of the NBD. A closed form is not known, however, there are representations with special series and integrals. In this note, we will investigate one of these and give an approximate formula for the entropy that is valid up to $\sim$20\% deviation from the exact value for extreme values of the NBD parameters.

In this present study, an extended Delta 54 flavor symmetry model incorporating two standard model Higgs doublets is investigated. This model generates neutrino masses through the triple inverse seesaw mechanism. It predicts deviations from tribimaximal mixing, yielding a nonzero reactor angle and an atmospheric mixing angle in the upper octant. In addition, the CP-violating phase and the Jarlskog invariant are found to be consistent with current neutrino oscillation data. Our study also includes the dark matter sector by evaluating the relic abundance and active neutrino dark matter mixing under relevant cosmological constraints. Furthermore, baryogenesis is achieved through resonant leptogenesis at the TeV scale including flavor effects. We obtain the observed baryon asymmetry, for right-handed neutrino mass 10 TeV and mass splitting d.

We propose a two-loop radiative neutrino mass model based on the modular $Γ_4 \simeq S_4$ flavour symmetry supplemented by a discrete $Z_3$ symmetry. After spontaneous modular symmetry breaking, a remnant $Z_2$ symmetry guarantees both the radiative origin of active neutrino masses and stabilizes dark matter candidates. The model successfully reproduces charged lepton masses and neutrino oscillation data for normal ordering. It also predicts observable rates for charged lepton flavour violation (LFV). Due to the singlet-doublet mixing the model provides a viable scalar dark matter candidate. A fermionic dark matter candidate, strongly linked to LFV, is also present. We identify parameter regions consistent with relic density, LFV constraints, and direct detection limits, providing testable benchmark configurations.

We analytically prove, to all orders, that the Veneziano amplitude is the unique outcome of a dual bootstrap based on dispersive sum rules, unitarity, and a small amount of additional stringy input. This stringy input can be either the string monodromy condition or the recently uncovered splitting and hidden-zero conditions. A key ingredient in our proofs is to interpret the dispersive sum rules as sequences of moments. Equally important is the precise incorporation of the extra stringy input into the amplitude ansatz, which makes the analytic bootstrap sufficiently rigid to fix the amplitude uniquely.

We will witness enormous progress in the experimental sensitivity to charged-lepton-violation processes in the near future. New physics signals of charged lepton violation might be around the corner without conflicting with existing astrophysical and accelerator bounds. In this work, we explore the possibility of having a dark matter particle as a source for $μ\to e γ$, $μ\to 3e$, and $μ\to e$ conversion in nuclei. After computing the dark matter relic density and dark matter-nucleon scattering cross section, we outline the region of parameter space where one can simultaneously accommodate a dark matter fermion in agreement with existing collider and direct detection bounds, and positive signals in charged lepton violation observables.

We study zero-temperature false vacuum decay in $D$ compact spatial dimensions and show that for volumes below a critical value a new bounce solution, different from Coleman's celebrated $O(D)$ bubble, mediates the decay process, and typically leads to an exponentially enhanced decay rate. The bounce, when analytically continued to Lorentzian signature, nucleates a homogeneous field configuration for spatial volumes below a critical value, and quasi-homogeneous configurations for slightly larger volumes, and is not of the form of a thin or thick-walled bubble embedded in a false vacuum background. We explicitly show that the new bounce has the necessary features associated with false vacuum decay, following from its eigenvalue spectrum of fluctuations. The cross-over from homogeneous to quasi-homogeneous solutions as the spatial volume is increased is discussed, as is a real-time interpretation of the bounce. We apply this bounce to the study of a scalar field model, as well as a close cousin of the Schwinger effect that applies to $(1+1)d$ axion electrodynamics in compact space.

We propose a novel broadband strategy to search for axions by leveraging observables controlled by the axion field squared. We present a practical implementation of this concept for probing the axion--photon coupling. This is done by operating a dc SQUID at the flux sweet spot, where the voltage depends quadratically on the magnetic flux, and using lock-in modulation to evade low-frequency noise. The proposed setup is ultra-broadband, spanning over 15 orders of magnitude in axion mass, with further expansion of the mass range possible. The projected sensitivity is $|g_{aγγ}| \gtrsim 10^{-16} \text{ GeV}^{-1}$, orders of magnitude better than current bounds, and largely independent of axion mass. We discuss the sources of systematic background and a nulling technique to reduce them to an acceptable level. We also discuss how our strategy could be adapted to probe the axion-fermion coupling, as well as to detect other dark matter candidates such as dark photons.

We constrain uncorrelated primordial isocurvature perturbations using a combination of large- and small-scale cosmological probes, with the small-scale data provided by the ultraviolet luminosity function (UVLF) -- a measure of number density of galaxies as a function of UV brightness. We consider several isocurvature modes, including cold dark matter, baryon, neutrino density, neutrino velocity, and dark radiation perturbations. The isocurvature power spectrum is modeled using two independent parameterizations: a broken power law and a running power law, without fixing the spectral index a priori. Our analysis combines large-scale data from the Cosmic Microwave Background (CMB), baryon acoustic oscillations, and Type Ia supernovae with small-scale constraints from UVLF measurements obtained by \textit{HST} and \textit{JWST}. The UVLF probes matter fluctuations over a continuous range of intermediate scales, $k \sim 0.5$--$10~\mathrm{Mpc}^{-1}$ over a wide range of redshift $4\lesssim z \lesssim 13$, providing a direct handle on structure formation in a regime where constraints on the scale dependence of isocurvature perturbations remain comparatively limited. Our result represents the first UVLF-based constraint on model-agnostic isocurvature perturbations carried by various components. We construct $68\%$ and $95\%$ credible envelopes in $k$-space for the allowed isocurvature power and find good agreement between the envelopes for the $95\%$ envelope across a wide range of scales, indicating that our constraints are mostly insensitive to the assumed power-law form.

It is well known that a strictly massless spin-$3/2$ particle can interact consistently only within supergravity. Recently, positivity arguments have shown that an effective field theory of a massive Majorana spin-$3/2$ particle admits a smooth $m \to 0$ limit only if a graviton is present and the four-fermion contact interactions are tuned to the values dictated by $\mathcal{N}=1$ supergravity. In this work, we investigate how this limit is approached at finite mass. Assuming that the graviton $t$-channel pole can be discarded, we derive non-forward, tree-level dispersive bounds on massive spin-3/2 contact operators and determine the region of effective couplings consistent with unitarity and analyticity. For sufficiently small $m$, we find that the allowed parameter space forms a bounded, Planck-suppressed neighbourhood of the supergravity point, defined by the supergravity values of the four-fermion couplings. The supergravity point lies on the boundary of this region. In the regime $m \ll M_{\rm Pl}$, the volume of the allowed region scales parametrically as \[ \mathrm{Vol} \sim \frac{m^{6}}{M_{\rm Pl}^{6}} \, , \] and shrinks to zero as $m \to 0$, smoothly reproducing the massless-limit results. The allowed region becomes unbounded when mass approaches the Planck scale. We further analyze the effect of including additional light scalar and pseudo-scalar degrees of freedom, motivated by the Polonyi model, and find that their couplings are also bounded in a way similar to the contact couplings and that it doesn't enlarge the allowed contact coupling space.

It has been suggested that Hořava-Witten theory could provide a concrete realization of the Dark Dimension Scenario. In this context, the observable Standard Model sector is naturally localized in the micron-sized large dimension, which is the interval in the eleventh direction. Considering Calabi-Yau manifolds supporting generic vector bundles including also abelian factors, we point out that symmetric tadpole cancellation on the $E_8$ walls has the potential to ameliorate some of the issues of such a realization, including too fast proton decay. By taking not only the hierarchically small value of the dark energy but also the size of the Standard Model gauge couplings into account, one is driven to a special infinite distance limit, which is the Hořava-Witten analogue of a limit recently at the focus of the M-theoretic Emergence Proposal. Extrapolating results obtained for BPS-saturated amplitudes, we speculate about the possibility of obtaining the moduli dependence of the scalar potential, the gauge couplings and the Planck scale by simple one-loop Schwinger integrals over towers of states.

The Large Hadron Collider (LHC) is sensitive to signals of beyond the Standard Model physics through a variety of channels including missing energy and resonance searches. In most searches, the new physics and the Standard Model backgrounds are assumed to be invariant in time, up to systematic effects from the experiment. However, new physics with a time variation would provide an additional handle to separate signal from background. Such a time variation may come from ultralight dark matter coupling to an oscillating background field. In this paper, we consider an interaction of dark matter with quarks and an additional heavy particle, and show that the sensitivity of a search that uses timing information at the LHC can be up to a factor of two stronger compared to one that does not use time information.

Recent years have seen dramatic improvements in the sensitivity of electron-based direct detection experiments. Typically, the sensitivity to dark matter scattering is determined in the light and heavy mediator mass limits. In this paper we show that the light and heavy mediator mass limits are not separated by a single scale, but instead can be separated by up to three orders of magnitude in mediator mass for sub-GeV mass dark matter. We calculate the background-free sensitivity in Si and Ge targets, and a projected DAMIC-M sensitivity, to sub-GeV mass dark matter models with ``intermediate-mass" mediators between the light and heavy mediator limits. This allows us to determine the precise range of mediator masses that electron-based direct detection experiments are sensitive to when the dark matter relic abundance is generated via freeze-in. We make the calculations presented here publicly available in an updated release of EXCEED-DM (https://github.com/tanner-trickle/EXCEED-DM).

We develop the Bogolyubov coefficient formalism for gravitational production of fermions with time-dependent mixing, which allows us to study a prototype neutrino system. The neutrino masses and mixings depend on the scalar field values, i.e. the Higgs or singlet scalar expectation values. These are time-dependent in the Early Universe and, due to de Sitter fluctuations, can reach very large values during inflation. As a result, gravitational production of all types of neutrinos can be much enhanced. We obtain an upper bound on the abundance of active and sterile neutrinos produced by classical gravity, $Y \lesssim 10^{-11}$.

We study the parafermionization of the Monster CFT with respect to its $\mathbb{Z}_{pA}$ subgroups, with $p$ an odd prime. Under certain assumptions, we show that the parafermionization is equal to a non-invertible gauging of $\mathcal{P}(p) \times \mathcal{P}(p)^\vee$, where $\mathcal{P}(p)$ is the theory of $\mathbb{Z}_p$-parafermions and $\mathcal{P}(p)^\vee$ is an appropriate dual theory, with global symmetry characterized by the centralizer of $\mathbb{Z}_{pA}$. By tracking the symmetries of $\mathcal{P}(p) \times \mathcal{P}(p)^\vee$ through the non-invertible gauging, we argue that the diagonal Monster CFT has $\mathrm{Rep}(\mathfrak{so}(3)_p) \boxtimes \mathrm{Rep}(\mathfrak{so}(3)_p)^\mathrm{op}$ symmetry, and hence that the holomorphic Monster theory has symmetry $\mathrm{Rep}(\mathfrak{so}(3)_p)$. We then compute the defect McKay-Thompson series associated to these symmetries, and prove that their invariance subgroups are $Γ_1(p+2)$.

The strong decay $ψ(4040)\to D\bar D$ is anomalously suppressed despite ample phase space, whereas the $D\bar D^*$ and $D_s\bar D_s$ channels remain sizable. In this work, we study this suppression and the associated open-charm hierarchy in the framework of the instantaneous Bethe--Salpeter equation combined with the relativistic $^3P_0$ model, with the pair-creation strength fixed independently from $ψ(3770)\to D\bar D$. Within this framework, we show that the suppressed $D\bar D$ mode can be understood as a consequence of node-induced cancellations in the relativistic decay amplitude. The $D\bar D$ amplitude is strongly reduced because the corresponding overlap integral receives comparable positive and negative contributions from different momentum regions, whereas the $D\bar D^*$ and $D_s\bar D_s$ channels do not undergo the same strong cancellation. This interpretation is further supported by the pronounced sensitivity of the $D\bar D$ width to the initial mass, the charged-neutral $D$-meson mass splitting, and the dip structure in the mass dependence of the partial width. Our results provide a dynamical explanation of the suppressed $D\bar D$ mode and the core open-charm hierarchy of $ψ(4040)$ within a conventional $3\,{}^3S_1$ charmonium picture, while the precise value of the near-vanishing $D\bar D$ width remains model dependent.

We construct a framework for near-threshold $J/ψ$ photoproduction that combines a target-mass-corrected gluon-PDF moment expansion with an explicit scalar gravitational form factor associated with the QCD trace anomaly. Both contributions are embedded into a common partial-wave K-matrix unitarization scheme, ensuring elastic unitarity at the amplitude level. The resulting hierarchy of nested models is tested against GlueX data and shown to produce distinct signatures in the differential cross section, the effective $t$-slope, and the real-to-imaginary ratio. The scalar form-factor signal is found to be robust against PDF-set variations and survives unitarization. A smooth matching to the Pomeron power-law regime at high energy is demonstrated, providing a unified description from threshold to HERA energies spanning three orders of magnitude in the center-of-mass energy.

We discuss the cosmology of axion-scalar systems in asymptotic limits of type IIB/F-theory flux compactifications. These results allow us to test a putative extension of the Distance Conjecture in a dynamical setting, which posits that towers of states should become exponentially light in the distance measured along the trajectory (as well as in the geodesic one). In the case of infinite distance limits, we review a known classification of late-time asymptotic solutions, which always verify the extension of the conjecture whenever all relevant effects are taken into account. We also extend the analysis to the case of finite distance limits, where the analogous statement would require trajectories approaching the singularity to have a finite length. Surprisingly, we find this is not the case for the class of models under consideration. Moreover, the new solutions we find exhibit asymptotic accelerated expansion when approaching the boundary of moduli space.

We propose a numerical method based on the master field for large-$N$ reduced matrix models. While the master field is originally an infinite-dimensional matrix, in this method it is regularized to a finite dimension, with the requirement that it satisfies the loop equations as much as possible. This formulation can be directly implemented for numerical computation, and since there is no sign problem at the fundamental level, the method can be applied regardless of whether the model is of Euclidean or Minkowski type. In numerical calculations for one- and two-matrix models, the exact solution is well reproduced in the Euclidean case, while perturbative results are well reproduced in the Minkowski case. This demonstrates the effectiveness of the method and supports the idea that the matrix models studied in this paper admit a regularized master-field description.

Understanding the nature of dark matter (DM) is a fundamental challenge in particle physics. In this paper, we investigate the potential of vector boson fusion (VBF) processes at the Large Hadron Collider (LHC) to demonstrate, as a proof of principle, the feasibility of distinguishing between different dark matter scenarios, focusing on Higgs portal DM (HPDM) and neutralino DM in the $2j + \not\!\! E_T$ final state and exploiting the distinctive kinematic features of the VBF jets and the missing transverse energy. Our study reveals that the polarization of weak bosons in VBF plays a crucial role in shaping the transverse momentum distributions of the tagged jets, with the jets being less energetic in the transverse direction for the Higgs portal scenario compared to the neutralino scenario. In addition, the kinematic variables $Δη$ and $Δφ$ exhibit characteristic differences between the Higgs portal and neutralino DM signals, providing significant discriminating power between these scenarios. We further apply a Kolmogorov--Smirnov test using linear discriminant analysis to quantify the distinguishability of the signals and find that the Higgs portal signals can be differentiated from neutralino DM signals with a C.L. exceeding $5σ$, thereby establishing the viability of collider-based discrimination between dark matter models.

We show how, by exploiting the process of Coherent Elastic neutrino (v) Nucleus Scattering (CEvNS), neutrinos produced by nuclear reactor experiments appear to corroborate the evidence of the so-called X17 particle, which has been invoked to explain the ATOMKI anomaly. We base our analysis primarily on CONUS+ and Dresden-II data, which, when combined with CEvNS data from COHERENT and neutrino oscillation data from IceCube, single out a unique region of couplings to neutrinos and nuclei.

We report on the design, construction, and beam test of a pilot three-dimensional projection detector based on opaque water-based liquid scintillator (oWbLS). The detector consists of an $8 \times 8 \times 16$ cm$^3$ acrylic vessel instrumented with three orthogonal planes of Kuraray Y11 multi-clad wavelength-shifting fibers read out by Hamamatsu multi-pixel photon counters. The readout electronics are based on the CITIROC front-end boards developed for the WAGASCI and SuperFGD detectors of the T2K experiment. The detector was filled with oWbLS and tested with cosmic rays and proton beams of 50, 100, 250, and 500 MeV kinetic energy at the NASA Space Radiation Laboratory at Brookhaven National Laboratory. We present three-dimensional event displays of cosmic muon and proton beam candidates, and a study of transverse light confinement via radial charge distribution measurements. The measured data show tighter light confinement than a Geant4 simulation with a 2 cm scattering length, placing the effective scattering length well below 2 cm and confirming effective optical confinement of scintillation light in the oWbLS medium. A first measurement of the hit-level timing resolution using 500 MeV proton beam data yields a single-channel timing resolution of $σ_t \approx 0.17$--$0.28$ ns with good photostatistics. These results demonstrate the viability of the 3D-projection oWbLS technology as a scalable, fully-active detector concept for next-generation particle physics experiments.

We study the Casimir effect for a parallel plate setup with one plate with dynamical edge mode (DEM) boundary conditions, and one plate with perfect electromagnetic conductor (PEMC) boundary conditions. In order to restore BRST invariance, new edge fields are introduced on the DEM plate. We then lift the boundary conditions into the action using Lagrange multiplier fields, and integrate out the bulk fields to obtain a non-local effective boundary theory from which we compute the Casimir energy. The resulting Casimir force is identical to a PMC-PEMC setup, implying that, from the point of view of the Casimir effect, a DEM plate is equivalent to a PMC plate. We also include a detailed derivation of the general functional method used to compute the Casimir energy from the partition function.

We present the perturbative heavy-quark condensate at five-loop order in QCD. This constitutes the first calculation at this order accounting for non-vanishing quark masses. Our result confirms the computation of the five-loop vacuum anomalous dimension by Baikov and Chetyrkin.

We investigate the $η^\prime \to ηππ$ decays within the framework of large-$N_{C}$ chiral perturbation theory, by calculating the decay amplitudes up to next-to-next-to-leading order in a simultaneous expansion in powers of external momenta, quark masses, and $1/N_C$. Projecting the amplitudes onto partial waves allows us to implement a unitarization procedure to account for the $S$- and $D$-wave $ππ$ final-state interactions. The relevant low-energy constants are determined by fitting our theoretical results to the precise experimental data from the A2 collaboration. A comparison of fits with and without $ππ$ final-state interactions demonstrates that including these effects significantly improves the agreement of our theoretical predictions with the experimental measurements. Consequently, the Dalitz-plot parameters are extracted as $a=-0.085(18)_{\mathrm{stat}}(4)_{\mathrm{syst}}$, $b=-0.081(10)_{\mathrm{stat}}(6)_{\mathrm{syst}}$, and $d=-0.045(6)_{\mathrm{stat}}(8)_{\mathrm{syst}}$. Our results provide therefore a refined theoretical description of the $η^\prime \to ηππ$ decay dynamics.

The persistent challenge of creating stable de Sitter vacua within string theory undermines the observational validity of the $Λ$ cold dark matter (CDM) model. This difficulty suggests that the concordance model of cosmology, characterized by a constant dark energy $Λ$, may reside in the swampland of inconsistent quantum gravity theories rather than the string landscape of consistent ones. Recent observational data, particularly from the Dark Energy Spectroscopic Instrument (DESI), have significantly challenged $Λ$CDM cosmology. Specifically, the combination of DESI baryon acoustic oscillation measurements with cosmological surveys seem to indicate a preference for a dynamic, time-evolving dark energy rather than a constant, with roughly 10\% reduction in density over the last several billion years. This review summarizes significant advancements made over the past two years in linking DESI findings to string-inspired scenarios.

We present EEXICC, a Monte Carlo event generator designed to simulate the production of doubly heavy baryons ($Ξ_{cc}$, $Ξ_{bc}$, and $Ξ_{bb}$) via $e^+e^-$ annihilation. Based on nonrelativistic QCD effective theory, the generator calculates the process $e^{+}+e^{-}\rightarrow Ξ_{QQ'}+\bar{Q}'+\bar{Q}$ using an improved trace technique at the amplitude level, which greatly improves numerical efficiency compared with traditional squared-amplitude methods. EEXICC is developed in Fortran with a modular structure and is fully compatible with the PYTHIA framework, enabling convenient integration into complete event simulation workflows. The program supports both weighted and unweighted event generation, and its numerical reliability has been verified against existing theoretical results. EEXICC provides a flexible and robust tool for studying the properties of doubly heavy baryons at future high-luminosity and high-energy $e^+e^-$ colliders such as the CEPC and FCC-ee.

In this paper, we investigate the impact of renormalization group (RG) consistency on the chiral phase transition and thermodynamic properties of QCD matter using the RGNJL and RGPNJL models. By implementing a temperature-dependent thermal cutoff $Λ_T = kΛ_0$, we ensure that thermodynamic quantities converge toward the Stefan-Boltzmann limit at high temperatures, effectively extending the applicability of these effective theories. Our analysis shows that while the RG-consistency condition ($k \rightarrow \infty$) resolves causality violations in the RGNJL model by binding the speed of sound to the conformal limit, the RGPNJL model exhibits a more complex, non-monotonic sensitivity to the parameter $k$. Furthermore, we demonstrate that the RG-improved PNJL framework significantly enhances the description of net-baryon number fluctuations ($κσ^2$) relative to lattice QCD data at vanishing chemical potential, though the intensification of these fluctuations at high baryon density highlights a critical sensitivity to the model's parametric constraints. This study provides a rigorous evaluation of the RG-consistency framework's predictive power in mapping the QCD phase diagram and interpreting experimental observables.

Neutrino flavor evolution in dense astrophysical environments such as core-collapse supernova (CCSN) is influenced by collective effects. While the Fast Flavor Instability (FFI) and the Collisional Flavor Instability (CFI) are recognized as key drivers of rapid flavor conversion, their non-linear competition with collisional damping in spatially varying environments remains poorly understood. Motivated by recent findings that FFI and resonance-like CFI co-occur in the post-bounce phase in CCSN, we scrutinize their dynamic competitions and asymptotic states. To this end, we perform numerical simulations of the quantum kinetic neutrino transport, incorporating both spatial advection and the collision terms. We demonstrate that the interplay between these coexisting neutrino flavor instabilities and collisions leads to rich dynamics. Rather than merely inducing simple decoherence, collisional damping can substantially alter the overall dynamics of collective flavor oscillations, driving the system through complex evolutionary pathways. In all cases where flavor instability develops, we find that the system converges to the same flavor-equilibrated asymptotic state, despite the diversity of intermediate dynamics. Our results suggest that this dynamic competition could alter the widely accepted picture of collisionless FFI, highlighting the need to incorporate realistic collisional effects into studies of flavor conversions in CCSN models.

Several simple asymptotically-free chiral gauge theories are studied. The only ``free parameters'' of our models are the choice of the gauge group and the matter Weyl fermion representations, and the relative magnitudes of the renormalization-group-invariant scales $Λ_i$ associated with each gauge group. None of our models has nontrivial nonabelian global symmetries (``family''--like fermion representations). We rely on some recent theoretical developments on the dynamics of strongly--coupled chiral gauge theories, based on the generalized symmetries and associated new types of anomaly-matching consideration, but also on the solid knowledge on vectorlike gauge theories such as QCD and supersymmetric Yang-Mills theories. The structures of the infrared effective theories, the RG flows, and the light spectra found in these models are surprisingly rich and intriguing.

We develop a light-front Hamiltonian formalism to study the real-time quantum evolution of a high-energy quark propagating through the Glasma phase of a heavy-ion collision. In this work, the quark Fock space is truncated to the $\ket{q}$ sector and the wavefunction is expanded in a discrete basis representation, following the time-dependent Basis Light-Front Quantization (tBLFQ) framework. The classical Glasma background fields enter as a time-dependent external potential, and physical observables are extracted as expectation values of quantum operators over the time-evolved state. We compute the transverse momentum broadening and the jet quenching parameter, finding results consistent with classical estimates, including the expected scaling with respect to the saturation momentum, and use them to perform phenomenological estimations for different collision systems. We also study the color rotation of the quark state induced by the Glasma fields, and examine its dependence on the saturation scale and the gauge choice. This formalism allows systematic improvements to include, in particular, non-eikonal propagation and parton splittings that will be considered in forthcoming publications.

In light of novel and past experimental results, we demonstrate how Weibel-mediated filamentary structures can develop in the expanding plasma plume of a laser-irradiated foil. The transverse ballistic cooling that occurs during the quasi-spherical plasma expansion naturally drives an electron pressure anisotropy, resulting in the growth of electron current filaments. This effect competes with electron-ion Coulomb collisions which tend to isotropize the electron distribution function. Based on theoretical and particle-in-cell modeling, we provide estimates of the dominant wavelength and amplitude of the self-generated magnetic fluctuations, which are found to explain experimental data obtained at the OMEGA and Laser Megajoule facilities.