arXiv Daily Digest - 2026-05-22

Plasmonic resonances in metallic nanogaps can confine light into nanometric regions, but reaching modes of volume $\approx 1$ nm$^3$ remains challenging. Here we present a detailed theoretical analysis of the optical modes of a nanoresonator that contains a picopatch formed by the lifting of a few gold atoms in the gap of a Nanoparticle-on-Mirror (NPoM) structure. This configuration is motivated by recent experiments that suggest that local lifting of an atomic monolayer from metallic substrates can occur randomly due to optical or thermal forces. We show through classical simulations that the plasmonic modes associated with the picopatch geometry can confine light to extremely small regions and are highly sensitive to the size and shape of the picopatch, enabling broad tunability. Furthermore, these modes can couple strongly with other nanocavity modes of the structure, as identified by the presence of a clear anti-crossing of the resulting polaritonic resonances. Remarkably, up to $\approx 2000$-fold electric field enhancement in the middle of the picopatch and tiny effective mode volumes that approach $\approx 1$ nm$^3$ are obtained. We also confirm that changing the morphology of the picopatch does not modify the qualitative findings, and verify that increasing the absorption losses in the classical simulations, to mimic quantum (non-local) effects in the metal permittivity, decreases the electric field enhancement only moderately. Compared to the standard picocavities formed by single-atom protrusions, this work shows that picopatches are an intriguing alternative to reach extreme optical field confinement and enhancement in plasmonic cavities.

Optomagnonic modulation techniques are an emerging platform for information transfer from the microwave to the optical domain. However, these techniques focus largely on the spectral domain of the transduced signal. Given the potential of the field to bridge the gap between microwave and optical signals, analyzing and studying the interactions real-time in temporal domain becomes equally essential. In this work, we exploit the optomagnonic modulation in a YIG microsphere to demonstrate and study microwave to optical real-time dynamic transfer on a time scale comparable to the decay of magnons. We inductively excite magnons in the microwave domain and use magnon-based Brillouin light scattering to transduce the signature of excited magnonic waveforms to the optical domain. The square type modulation of the magnons is retrieved in the corresponding optical sidebands. Our work enables real-time measurement of the magnonic dynamics and therefore direct access to lifetime measurements of the magnonic mode. Providing insight into the temporal dynamics of magnons, this work can open up new promising research directions such as in magnon coupled superconducting qubits or magnon-based Brillouin memory.

Optical amplifiers are ubiquitous in science and technology and are the workhorse of modern communications. Currently, virtually all amplifiers rely on atomic resonances, such as rare-earth-doped fibers, or are based on III-V semiconductors. Fueled by emerging applications, there is increased demand for amplifiers that are high-gain, broadband, low-noise, and deliver high output power outside traditional wavelength ranges. Over the past few decades, it has been shown that optical parametric amplifiers (OPAs) can address this challenge. Pioneering works on highly nonlinear optical fibers or bulk crystals have demonstrated their potential, but high pump powers and long fiber length limited their practical use. Recently, a renaissance of OPAs has occurred with the demonstration of photonic integrated circuits, which exhibit higher effective nonlinearity and enable wider bandwidths. Yet they require ultra-low loss, highly precise dispersion engineering, and large chip footprints, limiting OPA performance to date. Here, we overcome these limitations and, using periodically poled thin-film lithium tantalate (PPLT) photonic integrated circuits, we demonstrate continuous-wave optical parametric gain up to 23.5 dB, with a flat-top profile spanning across an 850 nm-wide optical wavelength window, corresponding to 100 THz and covering all communication bands. Moreover, on-chip output signal power as large as 313 mW in the optical O-band is achieved. We further realize all-optical inter-band modulation transfer between the C- and O-bands. Our approach uses cascaded second-order nonlinear processes that provide high effective third-order nonlinearities while preserving the wide material bandgap. These results establish PPLT integrated photonic circuits as a scalable platform for broadband optical amplification and frequency conversion across wavelengths where rare-earth doped amplifiers are absent.

In a previous article, we obtained the first-ever list of astrometric binary asteroid candidates. Some of these candidates have now been confirmed. In that previous work, however, the details of the statistical methods were not provided. Our first aim is to provide methodological details and performance evaluation of the approach used for detecting binaries. Our second aim is to establish an updated list of binary asteroid candidates from Gaia FPR astrometric residuals exploration, where we account for the statistical properties of FPR data. We account for the astrometric uncertainties from FPR and we refine the statistical model of the data, which we use in MC simulation to evaluate the strength of the individual detections; we set up a trend detection method in the residuals and apply a dedicated period search algorithm; we update the statistical selection process to build the list of candidates; we set up a method for detecting objects in multiple windows of consecutive observation; we refine the method for confidence interval estimation of these parameters and we better constrain the physical parameter selection. We detect 343 binary asteroid candidates corresponding to 410 windows of consecutive observations in the astrometric data. We show that in noise-only control simulations, the typical number of detections is 88% lower than in the FPR data. We also detect 9 known binaries, 25 candidates overlapping with the Pan-STARSS survey and 99 overlapping with our previous binary search in DR3. Finally, we report the detection of 45 objects with trends in residuals suggestive of wide binary systems. Our results and analyses demonstrate that although detecting binary asteroids is a difficult problem due to their low signal level, the proposed method is likely to provide a reliable list of detections, including systems poorly accessible to conventional techniques.

Photovoltaic generation plays a central role in the energy transition, yet understanding its adoption dynamics requires robust analytical frameworks that capture both temporal and spatial patterns of decision behavior. This study applies a data-driven decision analytics approach to examine residential self-consumption photovoltaic installations in Catalonia within an innovation diffusion framework. The temporal evolution of adoption is modeled using a logistic growth function, providing evidence that imitation effects are a primary driver of adoption decisions. To extend the analysis, a quantitative methodology is developed to estimate the influence of external factors on adoption behavior, revealing that social perception exerts a stronger impact than regulatory and socioeconomic variables when considered independently. In addition, a spatial analytics component is incorporated to assess territorial heterogeneity, identifying correlations between adoption patterns and demographic and socioeconomic characteristics. The findings contribute to predictive and diagnostic analytics by offering a structured framework to model technology diffusion and inform policy and investment decisions aimed at accelerating sustainable energy adoption.

Automated metasurface design is increasingly important, and recent advances in language-model systems are opening a route toward agentic optical design. Yet modern metasurface applications, from metalenses and holography to optical computing, require long design chains spanning modeling, simulation, coding, optimization and evaluation. These chains are error-prone, whereas existing language-model-based metasurface tools remain largely limited to simple objectives, predefined pipelines or language-to-layout generation. Here we introduce MetaDesigner, a self-correcting language-model system for agentic metasurface design. From a natural-language optical objective, MetaDesigner plans the design route, retrieves domain knowledge, invokes simulation and optimization tools, generates missing tool code and identifies errors through a dedicated Verifier. We demonstrate three tasks of increasing complexity: an RGB metalens with three independent focal spots, a six-plane full-color hologram with an average structural similarity index measure (SSIM) of 0.97, and an optoelectronic hybrid neural network for image style transfer. These tasks require 74, 136 and 90 reasoning steps, respectively, and the system self-corrects errors in frequency mapping, numerical aperture estimation, network-parameter counting and loss-function description. These results establish MetaDesigner as a self-correcting route to agentic metasurface design, where language-model systems can not only execute optical design tasks but also extend, inspect and repair the design process itself.

In its early days, online dating was heralded as a great equalizer, removing biases built into the structures of heterosexuality courtship. However, as repeatedly observed, that prophecy was never fulfilled, and some biases have even become exacerbated. In this paper, we identify a general endogenous mechanism that drives the widening of the gender gap in first-contact rates of heterosexual dating. This mechanism relies on assumptions about the participants' expectations of new contacts and their time constraints. We formulate this symmetry-breaking mechanism as a system of differential equations and analyze its fixed points and their stability.

In this work, we introduce a non-volatile heterogeneous quantum dot (QD) III-V/Al2O3/Si distributed feedback (DFB) laser exhibiting optical memristive behavior. The device operates in the O-band (~1300 nm) with a threshold current density of 234 A/cm2 and a side-mode suppression ratio exceeding 48 dB. Co-integrated Al2O3-based memristors produce bipolar resistive switching, yielding non-volatile wavelength shifts of ~ 46 pm and ~ 17 dB peak power contrast with zero static holding power. The III-V/Al2O3/Si heterojunction memristor I-V hysteresis is also modeled. This new device enables simultaneous coherent light generation and persistent optical state storage, establishing a new class of active photonic memory for neuromorphic and reconfigurable WDM applications.

IR microspectroscopy of single biological cells is challenged by strong light scattering, which produces baseline effects and peak distortions in the IR spectra and hinders the direct extraction of chemical information. Current methods for scattering correction typically rely on Mie theory and are accurate only under the assumption that the cell can be approximated by a sphere. Here, we present a framework for the scattering correction of IR absorbance spectra that is based on 3D ellipsoid models and provides efficient scattering correction for both suspended (spherical) and adhered (flattened) cells. Our approach combines deep learning approaches with computational IR microspectroscopy based on the finite-difference time-domain (FDTD) method. The FDTD method generates a synthetic library of realistic training spectra, while the deep learning model enables fast spectral inversion. We demonstrate scattering correction in silico using numerical cell phantoms of cervical cancer cells (HeLa) and show that the true absorption spectra can be inferred from IR absorbance spectra. We further show that the 3D cell dimensions can be recovered from the IR absorbance spectra, highlighting that the inherent light scattering could be exploited to realize the full analytical potential of IR spectroscopy. We anticipate that deep learning-based scattering corrections can be readily extended to increasingly complex sample geometries owing to the flexibility of the FDTD method to model arbitrary geometries.

Silicon's bandgap inherently restricts its photodetection to wavelengths below 1100 nm, necessitating the integration of costly III-V semiconductors for short-wave infrared applications. Hyperdoping silicon beyond the solid solubility limit offers a promising "silicon-native" alternative, yet achieving practical short-wave infrared applications at room temperature remains a formidable challenge. Here, we demonstrate a high-detectivity hyperdoped silicon photodetector enabling room-temperature computational short-wave infrared imaging beyond Si bandgap wavelength at λ = 1550 nm. By integrating an ultrafast laser heating process step to reduce the dark current while keeping high responsivity, we achieve a specific detectivity D^* exceeding 10^9 Jones for 1550 nm at room temperature working in a forward-biased, photoconductive mode. The improved detectivity, coupled with a 59.4 dB linear dynamic range and kHz-scale bandwidth, allows us to demonstrate a single-pixel imaging system that reconstructs 1550 nm scenes at 65x63 pixels without cryogenic cooling. Our devices simultaneously support visible-light imaging, offering a path toward monolithically integrated, multispectral Si-native optical sensors. These results establish ultrafast-laser hyperdoped silicon as a viable platform for low-cost, room-temperature, short-wave infrared photonics, bridging the gap between advanced materials science and practical computational imaging system.

Real-world deployment of AI vision models is both fueled and limited by the data available for training and testing. Real datasets are sparse and uneven: long-tailed or unbalanced distributions hinder generalization, and the low number of samples in low density regions makes it hard to run evaluations. Synthetic data can fill these gaps, providing us with a way to sample the input space more continuously and improve data coverage for benchmarks. Focusing on the autonomous driving safety-critical case of pedestrian detection in the dark, we show how synthetic low-light samples can be used to better characterize the performance of a state-of-the-art object detection model as a function of the scene illumination. We use a synthetic RAW image augmentation technique to generate low-light samples that match the noise model of the camera sensor. Performance metrics on real and synthetic low-light data are similar, indicating that the AI model finds it hard to distinguish between them.

A detailed formulation of the relativistic plane-wave Born approximation for inelastic collisions of charged particles with free atoms and positive ions is presented. The wave functions of the target atom or ion are calculated from a central-field independent-electron model with the Dirac-Hartree-Fock-Slater self-consistent potential, and the electromagnetic field is expressed in the Coulomb gauge. The double-differential cross section, depending on the energy loss and the recoil energy, is given as a sum of two terms which are products of purely kinematic factors and the generalized oscillator strengths (GOSs). Transitions induced by the instantaneous Coulomb interaction between the projectile and the active target electron are described by the longitudinal GOS. Transitions caused by the transverse interaction (exchange of virtual photons) are accounted for by a transverse GOS. We derive closed expressions for the longitudinal and transverse GOSs in terms of vector coupling coefficients and radial integrals. A set of Fortran programs have been written to compute the GOSs, the energy-loss differential cross section, and integrals of the latter. A complete numerical database of GOSs has been calculated for all the subshells of the ground-state configuration of neutral atoms of the elements with atomic numbers from 1 (hydrogen) to 99 (einsteinium). A systematic derivation of asymptotic formulas for the total cross section, the stopping cross section and the energy-straggling cross section is presented. The shell correction to the asymptotic formula for the stopping cross section of protons is obtained from the difference between computed numerical values and the predictions of that formula.

Nanopore sequencing accuracy is inherently limited by the quality of data from individual molecular translocation events, requiring advances beyond traditional sequencing-by-synthesis methods. We introduce an oxidized pyramidal sub-nm pore (OPSP) integrated in a threeterminal sensing platform, where the sub-nm silicon pore functions as an electrode for detecting displacement currents across an oxide barrier, induced by counter-ion migration within the electric double layer. This platform achieves sub-1-nm-scale spatial resolution and a signal-tonoise ratio (SNR) up to 15 for biopolymer sequencing, enabling direct identification of individual bases in single-stranded DNA and single amino acids in peptides, with raw-read accuracies exceeding 98.5% and 95.5%, respectively, without consensus-based computational correction. The OPSP demonstrates high acid tolerance, reusability in varied chemical environments, and operational stability for over six months. This work establishes OPSP as a durable, high-accuracy platform for single-mer resolution sequencing, defining a reliable and robust paradigm for next-generation sequencing technologies.

The discovery of altermagnetism offers new opportunities for exploring novel quantum states and developing spintronic devices for enabling momentum dependent spin splitting in compensated systems, while zero net magnetization limit its manipulability using conventional magnetic method. Here, we propose 2D alternating ferrimagnetism,a phase merging alternating momentum dependent spin splitting with a finite net magnetization. A tight binding model reveals that alternating ferrimagnetism originates from uncompensated magnetization in altermagnets, facilitating concurrent net magnetization and alternating spin splitting. First principles calculations and Monte Carlo simulations demonstrate stable alternating ferrimagnetism in strained and Cr substiting V2Te2O, which exhibit strain tunable net magnetization, reversable half metallicity and valley polarization, accompanied by long range magnetic order above room temperature. By combining altermagnetic and ferromagnetic properties, alternating ferrimagnetism expand the 2D magnetism landscape and offer pathways for energy efficient spintronic applications.

Forbidden atomic transitions provide some of the most stringent low-energy tests of physics beyond the Standard Model, with sensitivity set by the interplay between the sought-for signals and systematics suppressed by symmetry. Here we identify the previously unobserved $4f^{6}6s^{2}\,{}^{5}$D$_{0}$ level of neutral samarium at $14\,564.90(2)\,\mathrm{cm}^{-1}$, opening the ${}^{7}$F$_{0}\rightarrow{}^{5}$D$_{0}$ inner-shell transition for precision spectroscopy. Candidate lines extracted from dual-comb absorption spectra were assigned using double-resonance population-depletion and sequential-excitation measurements. The observed pressure broadening, $0.12(2)\,\mathrm{MHz/torr}$, and pressure shift, $0.145(4)\,\mathrm{MHz/torr}$, indicate an inner-shell $4f$-transition shielded from external perturbations. Many-body calculations predict a $\sim\!120\,\mathrm{ms}$ metastable lifetime (quality factor $\mathcal{Q}\sim 3\times 10^{14}$), large sensitivity coefficients for variation of the fine-structure constant, and a nuclear-spin-dependent parity-violation amplitude comparable to that of cesium. Crucially, the $J=0\rightarrow J=0$ selection rule suppresses by symmetry both the nuclear-spin-independent parity-violation channel and the M1 and E2 backgrounds that complicated previous heavy-atom experiments, yielding a uniquely clean window onto the nuclear anapole moment. The two stable spin-$7/2$ isotopes of samarium provide a remarkable opportunity to largely cancel atomic-structure uncertainties by measuring the ratio of parity-violation effects in the two isotopes. These results establish neutral samarium as a platform for inner-shell precision spectroscopy and tests of physics beyond the Standard Model.

Temporal ghost imaging (TGI) enables ultrafast signal reconstruction beyond electronic bandwidth limits. Extending this concept to the mid-infrared (MIR) regime through nonlinear frequency conversion offers new opportunities for high-fidelity temporal detection, but remains constrained by stringent phase-matching condition, limited spectral coverage, and intricate optical alignment. Here, we propose and demonstrate a broadband MIR TGI system based on non-degenerate two-photon absorption. A temporally encoded near-infrared pump transfers structured modulation onto a MIR signal directly at a silicon detector, which facilitates concurrent modulation and detection without external nonlinear crystals. The reconstructed temporal waveforms exceed the detector bandwidth by more than fortyfold, achieve a detection sensitivity of 0.05 pJ/pulse, allow compressed sensing with 80\% fewer measurements, and support broadband operation across 2.5-3.8 $μ$m. This compact, alignment-free, and room-temperature system establishes a practical route for fast and sensitive MIR time-domain analysis, holding great promise for applications in time-resolved molecular spectroscopy, high-precision infrared ranging, and high-speed free-space communication.

We present a systematic investigation of Ga adsorption and desorption kinetics on the wurtzite GaN(0001) surface using four in situ techniques operated simultaneously: reflection high-energy electron diffraction, laser reflectometry, line-of-sight quadrupole mass spectrometry, and optical pyrometry. Flux- and temperature-dependent experiments are performed for Ga coverages ranging from the submonolayer to the droplet regime. Despite their distinct transient responses, the signals from all four techniques and their trends with surface coverage are quantitatively reproduced by a unified kinetic model of Ga adsorption, diffusion, and desorption. An Arrhenius analysis of the Ga adlayer desorption yields an activation energy of (2.87 $\pm$ 0.04) eV.

This paper presents a unified gas-kinetic wave-particle (UGKWP) method for simulating multiscale binary-species gas mixtures. Benefiting from direct modeling in a discretized space, the UGKWP method enables the automatic decomposition of the gas distribution function into analytical hydrodynamic waves and discrete particles, which respectively describe its near-equilibrium and non-equilibrium parts. This approach offers significant advantages for simulating various multiscale physical phenomena, such as hypersonic flows, plasma transport, and radiation transport. In this study, we employ the model proposed by Groppi et al. [EPL, 96 (2011) 64002] to calculate the macroscopic velocity and temperature of the local target equilibrium distribution function, thereby recovering the correct viscosity and diffusion coefficients in the continuum flow regime. To address the heat conduction coefficient, the Shakhov model is incorporated to correct the Prandtl number. Diffusion effects are accounted for not only in the source term via an operator-splitting method, but also in the flux evolution through the characteristic integral solution, while strictly maintaining consistency between the wave and particle descriptions. Furthermore, the microscopic model for high-speed particles is improved by utilizing a physically corrected collision time to determine their free-transport time. Through a series of numerical tests spanning the continuum to rarefied regimes, the proposed UGKWP method is shown to accurately capture the differences in velocity and temperature between different species. Notably, for hypersonic flows, the predicted wall pressure, shear stress, and heat flux coefficients agree well with DSMC results.

The advent of additive manufacturing has opened opportunities to rapidly prototype devices and products ranging from automotive and aerospace applications to micro/nanoscale metastructures, as examples). Three-dimensional (3D) printing has become relevant for electromagnetic structures, integrated optics and photonics systems, however, the optical properties of commercially available 3D printed polymers at telecommunication wavelengths (wavelength 1550nm) is not always available. Provided the importance of 3D printing technologies, in this work, we evaluate both theoretically and experimentally the complex refractive index of four polymers including some recycled versions (namely Butenediol Vinyl Alcohol (BVOH), Polylactic Acid (PLA), Recycled Polyethylene Terephthalate (rPET), and recycled Polylactic Acid (rPLA)) as potential candidates for photonics applications. The 3D printed samples have thicknesses from ~100 to 400 nm (~64wavelengths to ~258wavelengths, respectively). The experimental reflectance and transmittance spectra are extracted and used to retrieve the complex refractive index of each printed material demonstrating extinction coefficients in the order of 10^-4 at wavelength=1550nm. The experimental results are validated using numerical simulations. Finally, as a proof-of-concept, a convex-planar lens and a Bragg mirror are designed and numerically evaluated, showing the potential of the proposed polymers for 3D printing photonic structures at telecommunication wavelengths.

Low-index transparent conducting oxides have attracted significant attention because ultrafast optical excitation in these materials can induce exceptionally large temporal index gradients. Due to this remarkable nonlinear optical behaviour, this material platform enables sub-picosecond, all-optical control of photon energy and momentum, with growing relevance for integrated photonics, quantum optics, and optical computation. Owing to their hybrid electronic structure, transparent conductors exhibit both intraband and interband nonlinearities, previously accessed using dual-colour excitation with near-infrared and ultraviolet pumps. Here, we show that both excitation regimes can be activated using a single, intense near-infrared pump. Above a threshold intensity, the pump drives hot-electron intraband dynamics while simultaneously generating higher harmonics that trigger interband excitation. The interplay of these two effects sharpens the temporal features of the recorded transmissivity which in turn substantially broadens the effective material bandwidth. Finally, by comparing linear and circular pumping conditions, we further demonstrate that the observed interband nonlinearities originate from harmonic generation rather than from direct multiphoton absorption. Our results provide key insights into the strong-field optical response in these time-varying photonic materials, opening new frontiers for the ultra-fast manipulation of photons in both classic and quantum regimes.

Orbital Angular Momentum (OAM) of light is a promising degree of freedom for next-generation communication. By exploiting the orthogonality of OAM modes, multi-channel division enables a linearly increase in communication performance proportional to the number of available modes. However, the multiplexing and demultiplexing of each superposition state remain essential yet complex processes. Demultiplexing has been established through spatial-domain methods that require additional optical elements such as gratings and apertures, which can decrease communication efficiency and accuracy under various conditions. In this paper, we propose a demultiplexing method under a single intensity profile by orthogonality renormalization of OAM pair states. This method can be applied directly to an OAM multichannel communication system without additional receiver-side optical structure. We present simulation results of our method under various conditions.

The reconstruction fidelity of computational optical imaging is fundamentally constrained by the model-reality gap, i.e., the inevitable discrepancy between idealized forward models and the physical imaging process. Conventional paradigms attempt to bridge this gap through exhaustive system calibration or explicit parameter estimation, which are often computationally intensive and prone to severe non-convex stagnation. This paper introduces a Residual-Subspace Constraint Framework (RSCF) to achieve robust Fourier ptychographic microscopy. Instead of treating residuals as unstructured errors, RSCF leverages subspace decomposition to decouple low-rank, systematic mismatches from stochastic noise, thereby isolating stable information manifolds that remain invariant to forward-model inaccuracies. By embedding this subspace constraint into the iterative engine, the framework selectively suppresses error-amplifying components, enabling high-fidelity phase and amplitude recovery without explicit hardware calibration. Numerical simulations and experimental validations demonstrate that RSCF yields superior convergence acceleration and artifact suppression under severe optical aberrations and LED misalignment. This information-centric paradigm provides a versatile, model-agnostic strategy to enhance robustness across diverse computational imaging modalities.

Open optical or plasmonic resonators are placed on and connected through surfaces or via waveguides, forming complex lightguiding nanostructures, e.g. for integrated photonic quantum devices. We derive general boundary conditions for quasinormal modes that account for the structure's specific geometry. We then present a general quantization scheme for multiple, interacting quasinormal-mode cavities coupled to quantum emitters and to a non-bosonic bath of propagating photons on waveguides or a surface. We derive a system-bath Hamiltonian with rigorously defined coupling elements that can be computed using Maxwell solvers, including light-matter coupling between the electromagnetic field and quantum emitters. We define system-bath correlation functions for an effective, bath-mediated, and time-delayed interaction between the quasinormal modes and quantum emitters, which is a main ingredient commonly used to simulate open quantum system dynamics.

Controlled interaction of laser light with electron beams is fundamental for ultrafast electron microscopy and electron-based quantum optics, yet their direct coupling is forbidden in free space. Here we use longitudinally polarized light at a thin membrane and show that the emerging focal fields can modulate the electron beam in a direct, coherent and linear way, without the need for nanostructured materials or slanted interaction geometries. Also, we use vectorial polarizations to excite and probe three-dimensional nanophotonic near-fields in metallic mesocrystals by coherent electron energy gain and loss. We find that longitudinal electric fields excite axial near-fields in a direct way while longitudinal magnetic fields excite oscillating ring currents via azimuthal electric fields. These possibilities enable tilt-free, collinear generation of attosecond electron pulses or free-electron qubits and provide novel imaging modes in ultrafast electron microscopy and metamaterial tomography.

Chiral-induced spin selectivity (CISS) has been shown to enhance magnetic sensitivity in radical pair mechanism (RPM) models under specific Hamiltonian conditions, yet whether these enhancements persist across a broader parameter space remains untested. We incorporate the CISS effect as a spin-dependent initial state and recombination operator and systematically evaluate the spin dynamics of a model radical pair across a comprehensive parameter sweep of the RPM Hamiltonian. We characterise the orientational response through symmetric and antisymmetric decomposition of the yield distribution under field reversal, providing a direct quantitative signature of CISS-induced symmetry breaking. Our analysis demonstrates that CISS does not function as a generic amplifier of magnetic sensitivity. Claimed enhancements are conditional on the relative alignment of the internal hyperfine and dipolar interaction axes, arising specifically under conditions of non-collinear internal interactions. Extension to a two-nucleus model confirms that these enhancements are sensitive to nuclear spin. CISS-induced effects observed in the single-nucleus model are substantially suppressed when a second collinear nucleus is introduced, with the exception of the hyperfine axis rotation sweep where non-collinear tensor misalignment drives a robust antisymmetric response. These findings indicate that the conditions for CISS-enhanced magnetoreception are more stringent than previously demonstrated, requiring highly ordered and rigid molecular geometries to sustain the effect.

In 2020, Peter Larsen reported flaws in the methods for centrosymmetry parameter computation in the existing molecular dynamics and analysis packages. He proposed an intuitive an mathematically rigorous formulation for centrosymmetry parameter in terms of minimal-weight matching (MWM) on a fully-connected graph of atomic neighbors. He proposed using Edmonds' blossom algorithm for computing such a matching. In this paper, we investigate an alternative algorithm for MWM CSP computation using path finding approach and A* algorithm.

Living cells and tissues can generate complex patterns of electric fields and fluid flows which can play important role in physiology. Both, fields and flows are rooted in ion transport across biological interfaces: cell membranes and epithelial cell layers. Here we develop a unified electrohydraulic framework that combines electric fields, osmotic pressures, and fluid flows, emphasising their couplings. We consider an active, permeable interface that drives electrohydraulic fields in the surrounding bulk. We show that spatially heterogeneous ion transport acts as a distributed current source, generating long-range electric fields, osmotic gradients, and fluid flows. Using this framework, we show that patterns of ion pumping at cell and tissue boundaries can simultaneously produce large-scale electric fields and fluid flows due to electrohydraulic coupling. A key insight is that an external electric field and an internal dipolar pumping pattern can be physically equivalent and can generate the same pattern of ion current and fluid flows. The induced dipolar osmotic pressure can drive self-propulsion through bulk osmotic coupling, with a mobility determined by interfacial permeability and system size, a mechanism distinct from classical electrophoresis or electro-osmosis. We further show that for strong fields a new effect emerges. Nonlinear coupling can lead to isotropic swelling of a hollow ball of cells. This can explain recent experiments on epithelial organoids. Finally, we show that feedback between ion transport and resulting electric fields can drive spontaneous symmetry breaking, generating dipolar or multipolar fields and patterns. Our work highlights the importance of electrohydraulic coupling in the emergence in currents and fields in the biological systems.

We study theoretically the lasing synchronization of the two arrays of lasers with the complex mode dispersion, separated by a spectrally detuned barrier. We demonstrate that for lasing at the Dirac point, the synchronization persists for an order of magnitude higher barriers than in the arrays with a usual parabolic dispersion or a purely dissipative coupling. We interpret this effect as the Klein tunneling of the laser coherence through the barrier. Our numerical findings are supported by an analysis of the delocalization of the linearized eigenmodes of the arrays, which enhances the synchronization.

Ultrasonic backscatter measurements are widely used for microstructural characterisation. However, in materials containing strong anisotropy and spatial heterogeneity, the interpretation of backscatter signals becomes challenging because distance-dependent propagation effects can obscure genuine microstructural variations across depth. In this paper, a cross-directional compensation method is presented for ultrasonic backscatter measurements acquired from opposing inspection surfaces. The method exploits the reciprocal constraint that the dominant through-thickness propagation bias should contain a shared component between opposing inspection directions. A shared distance-dependent baseline is estimated in the logarithmic amplitude domain using an anchor-based fitting approach and subsequently used to compensate the measured backscatter profiles with depth. The method is demonstrated on two macrozone-containing Ti--6Al--4V samples, where conventional attenuation-based compensation is shown to be insufficient to consistently reconcile opposing-face backscatter profiles. Across six opposing-face signal pairs, the proposed method reduces the mean standard deviation of the directional mismatch profile from $0.367$ to $0.120$ and the mean absolute fitted gradient from $0.171$ to $0.0067$, outperforming conventional attenuation compensation. These results demonstrate that reciprocity-based compensation can reduce propagation-related bias while preserving local direction-dependent scattering variations, providing a practical signal-normalisation framework for backscatter analysis in heterogeneous anisotropic materials.

Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strategies compress the reconstruction network while overlooking physical priors from the optical path, leaving a trade-off between accuracy and speed. We present Physics-aware Dual-Integrated Network (PDI-Net), a low-latency framework that integrates infrared reconstruction with object detection and further embeds optical priors into the learning process. PDI-Net uses a supervised U-Net during training, while a semi-U-Net encoder shares features directly with a YOLO-based detector during inference, avoiding full image reconstruction. To bridge the gap between fidelity-oriented reconstruction features and detection-oriented semantics, we introduce a physics-aware large-small bridge (PALS-Bridge), which uses field-dependent point spread function priors to adaptively modulate multiscale convolutional branches. A physics-informed optical degradation simulation pipeline is also developed for training and validation. The method is deployed on a single-lens infrared camera, reducing system weight by about 50% compared with traditional multi-lens designs. On the M3FD benchmark under low-SNR conditions, PDI-Net reduces inference time by 84.06% compared with the Rec+Det with pruning strategy while improving mAP@0.5:0.95 by 5.07%. These results demonstrate compact, low-latency computational infrared imaging for real-time object detection on resource-constrained platforms.

Free-electron-based nanoscopy enables the study of optical excitations in materials with deep-subwavelength spatial resolution, with cathodoluminescence (CL) being one of the resulting radiation signals. When combined with an optical collection system, CL measurements can access multidimensional information of light; yet the phase of the emitted optical fields has remained largely elusive. Here, we demonstrate a reference-free phase retrieval approach for far-field CL wavefronts using the Gerchberg-Saxton algorithm implemented with real-space and angular-space CL intensity data. Applying this approach to representative nanostructures, including a planar surface, nanosphere, plasmonic crystal, and nanowire, we reconstruct distinct phase distributions that reveal their underlying radiation mechanisms. This reference-free framework offers a robust and flexible route for retrieving the phase of electron-beam-excited optical fields without relying on a reference wave, making it readily extendable to a wide range of nanostructures.

Unidirectional electromagnetic absorption provides a powerful approach for controlling light and heat, yet broadband realization in the infrared spectral region remains experimentally unexplored. Here, we report a non-Hermitian multilayer structure that enables robust broadband infrared unidirectional absorption. By combining low- and high-loss materials and engineering their thicknesses using the transfer-matrix formulation, the structure exhibits nearly perfect absorption spectrally matched to the blackbody radiation at 373 K under forward illumination, while suppressing backward absorption below 30%. Spectral analysis indicates that the observed unidirectionality originates from non-Hermitian physics near an exceptional point. Notably, broadband unidirectional absorption is achieved even without strict exceptional-point condition. This indicates that the observed unidirectionality is governed by the combination effect of loss distribution and optical interference, rather than a singular condition, ensuring robustness against film thickness variations. Furthermore, thermal shielding experiments demonstrate that the structure enables unidirectional control of thermal radiation, resulting in a temperature difference of up to 21 0C between forward and backward configurations. These results establish a robust strategy for broadband directional control of infrared radiation, with potential applications in passive thermal management, including thermal smart windows and infrared heat-shielding devices.

We introduce a utility-driven bounded-confidence model of opinion dynamics in which opinions associated with higher utility exert stronger social influence. In the regime where all agents belong to a single opinion cluster, we derive a stochastic differential equation for the mean opinion and show that its stationary distribution is Gibbs-like, with an effective potential determined by the utility landscape and an inverse temperature controlled by the learning rate and the number of agents. For multimodal utility functions, the dynamics exhibit metastability and spontaneous switching between competing opinion states. The reduced stochastic description also captures the evolution and merging of multiple opinion clusters, in agreement with agent-based simulations.

We present a simplified method for isolating the edges of a phase object from the edges of an amplitude object using a 4f system with an off-axis q-plate. Instead of the four off-axis shifts of the q-plate required in previous work, we need only two shifts (along +/- x) combined with linear polarizers at 45 degrees and 135 degrees. The number of measurements is reduced by half, potentially doubling the acquisition speed. We derive the theoretical basis, showing that the resulting intensity corresponds to the phase gradient squared, with amplitude-object contributions eliminated. Experiments on two phase-amplitude object samples demonstrate amplitude-edge reduction up to 97.6% and correlation coefficients up to 0.78 (sample 1) and 0.75 (sample 2). In overlapping regions, the phase edge is partially recovered; full recovery would require additional processing such as inverse filtering. This research is useful for biological imaging applications where fast and simple phase-edge isolation is desired.

We propose a deep learning framework based on an encoder-decoder architecture for the design and evaluation of cloaking devices, demonstrated in this work for two-dimensional wave propagation governed by the Helmholtz equation. The cloaks under consideration are concentric layered media surrounding the object, whose geometry and material parameters determine the scattering response. We consider circular and object-fitted layer configurations and parameterize all designs by the layer thicknesses, enabling a unified representation for direct comparison of different cloaks for the same object. Training data are generated using a boundary element formulation suitable for geometries where analytic solutions are not available, and neural networks are trained with standard hyperparameters on geometry-specific datasets. The proposed approach is applied to circular, star-shaped, and kite-shaped objects. Results show that object-fitted configurations consistently outperform simpler circular-layer designs in scattering reduction, highlighting the importance of geometry in cloaking performance. Overall, we present a flexible, data-driven approach for systematic comparison of cloaking strategies, with potential extension to more complex geometries and broadband settings.

We introduce force-kernel extended-system adaptive biasing force (FK-eABF), a force-based kernel reformulation of eABF that replaces the histogram-based mean-force accumulator of conventional eABF with a sparse population of Gaussian kernels storing local running-mean forces. Biasing forces are recovered by Nadaraya-Watson regression, yielding smooth estimates from the earliest stages of a simulation without a minimum-count threshold, while the same kernel population also defines an auxiliary, self-attenuating exploration force that requires no prior knowledge of barrier heights. On N-acetyl-N'-methylalanylamide in explicit water, FK-eABF achieves full free-energy landscape coverage faster than well-tempered metadynamics (WT-MetaD), on-the-fly probability enhanced sampling (OPES), and WTM-eABF, while all four methods converge to comparable accuracy given sufficient time. FK-eABF also retains long-time accuracy: on the DFG-in/out transition of Abl1 kinase, multi-microsecond simulations recover the established near-isoenergetic balance between states. At the opposite extreme, applied to the electrocyclic ring closure of 1,3-butadiene at the ab initio molecular dynamics level, FK-eABF recovers the free-energy landscape within 30 ps. Together, these benchmarks, spanning more than four orders of magnitude in simulation time, establish FK-eABF as more than a kernelized implementation of eABF: A force-based kernel reformulation that delivers faster early-time convergence without sacrificing long-time quantitative accuracy.

We develop a direct diagrammatic Monte Carlo framework for the Renyi entanglement entropy of interacting lattice fermions. The method starts from the fermionic graded-swap representation of Z_n[A]=Tr_Aρ_A^n, which converts the entropy problem into a replicated path integral with mixed temporal boundary conditions on the entangling region. In this representation the replica momenta are half-shifted, q_m=(2m+1)π/n, and the interaction expansion has a determinant form suitable for connected-determinant summation. We combine this expansion with a many-configuration Markov-chain Monte Carlo sampler to obtain order-by-order corrections for very large systems to very high orders. As a benchmark, we compare the order-by-order coefficients of a 3*3 Hubbard cluster with exact diagonalization. We then report a production calculation for a large periodic lattice with a square subregions. The dominant system-size limitation is therefore memory rather than a conventional auxiliary-field sign problem. The results provide a step toward diagrammatic calculations of fermionic entanglement observables in regimes where direct quantum Monte Carlo sampling is costly or sign-problem limited.

Managing the emission and absorption of thermal radiation is crucial for a wide range of technologies, from radiative cooling of buildings and vehicles to thermal regulation of satellites and future lunar and Mars habitats. Despite this universal and critical need, thermal emitters capable of adaptively modulating emissivity in a broadband, high-contrast, and fully solid-state manner remain elusive. Here, we leverage neural-network-guided photonic design to enable adaptive, solid-state thermal emitters based on chalcogenide phase-change materials capable of emissivity switching with extreme spectral contrast and bandwidth. These engineered nanophotonic emitters operate over a broad spectrum$-$from solar through thermal infrared$-$providing very low solar absorptivity while enabling switchable thermal infrared emissivity with high contrast. We experimentally demonstrate the core functionality of our approach in the space-like radiative environment in the stratosphere, observing a 31.5 °C temperature differential between the two solid-state phases of a simplified chalcogenide GeSbTe-225 thermal emitter. Our results point to even more significant capabilities, such as the potential to modulate >600 W/m$^2$ of radiative heat (at 100 °C) with minimal solar heating in the vacuum of space. The proposed nanophotonic solid-state adaptive emitter could provide high-power and high-speed heat modulation while requiring no power to maintain state, offering transformative capabilities for thermal control in dynamic radiative environments on Earth and in space.

We show that Maxwell theory with a codimension-$1$ Chern-Simons interface supports chiral electromagnetic surface waves on the interface, even when the bulk theory on both sides is conventional vacuum electrodynamics in infinite space. Solving the exact boundary value problem we find that the Chern-Simons interaction acts with opposite sign on the two helicities oriented along the interface, giving rise to one normalizable mode localized on the interface. This mode is a gapless chiral surface photon with linear dispersion and a frequency-independent index of refraction set by the Chern-Simons coefficient. This mode exists despite the absence of ambient material response or geometric confinement.

Ciliated organs transport viscous fluids through confined ducts, yet how duct morphology and ciliary activity jointly set the limits of flow rate and sustainable pressure remains unclear. Here, we model dense arrays of beating cilia lining duct walls as an active porous medium driven by prescribed metachronal waves, and identify two key morphological parameters that govern transport: the ciliary confinement ratio and the mean ciliary fraction. The resulting flows are described by the incompressible Navier-Stokes-Brinkman equations, which we solve numerically using a spectral method in the low-Reynolds-number regime. We also develop a complementary mean-field analytical model. The active porous medium framework provides an intermediate description between classical envelope theories and filament-resolved simulations and enables a systematic investigation of how fluid transport is shaped by confinement and packing of ciliary material. We find that transport is characterized by a decreasing linear relationship between flow rate and pressure generation, marking a fundamental trade-off between throughput and sustainable adverse pressure. These results provide a unified physical interpretation of the morphological diversity of ciliated ducts, from high-throughput ciliary carpets to pressure-generating ciliary flames, and offer guiding principles for the design of bio-inspired microfluidic pumps.

Transparent conducting oxides near their epsilon-near-zero frequency exhibit near-unity ultrafast modulations of the refractive index which have enabled the field of time-varying metamaterials, yet the underlying carrier dynamics at high driving fluences remain poorly understood. Here, we report ultrafast modulations in the reflectivity and transmissivity of indium tin oxide, and a non-monotonic oscillatory behavior. This is especially evident in the time evolution of the complex Fresnel coefficients retrieved directly from pump-probe spectrograms using a optical gating technique, GRUMPY FROG. The dynamics of the retrieved plasma frequency and damping coefficient are well captured by an extended two-temperature model incorporating a competing nonlinear interband process: at high fluences, Auger-type scattering of hot conduction electrons promotes valence band carriers, increasing the plasma frequency while accelerating hot-electron cooling and raising the damping coefficient. These results clarify the origin of anomalous high-fluence dynamics in indium tin oxide and identify a fluence-tuneable modulation dynamic with direct implications for ultrafast refractive index engineering in time-varying photonic devices and optical switching

Extreme ultraviolet (EUV) lithography is the cornerstone of the fabrication of advanced integrated circuits at the 7-nm node and beyond, but its reliance on multi-element reflective projection optics makes it inaccessible for small-scale research and prototyping. EUV interference lithography (EUV-IL) provides a lensless alternative but is intrinsically restricted to periodic structures. Here we demonstrate EUV holographic lithography (EUV-HL) as a lensless route to arbitrary, non-periodic, curvilinear patterning at the EUV wavelength of 13.5 nm. We introduce an inverse-design framework for computer-generated holograms that captures the dominant physical effects of EUV mask diffraction within a shift-invariant convolution model that is tractable for full mask layouts. Using this framework, we design and fabricate transmissive holographic masks by direct-write electron-beam lithography in hydrogen silsesquioxane, expose them with synchrotron-generated EUV radiation, and print target layouts with critical dimensions down to 40 nm, nearly an order of magnitude finer than the previous state of the art in EUV-HL. The demonstrated combination of sub-50 nm resolution, curvilinear design freedom, and a lensless optical setup establishes EUV-HL as a uniquely flexible tool for nanostructure prototyping at EUV wavelengths, and provides a natural pathway to non-periodic pattern prototyping at beyond-EUV (BEUV) wavelengths, which is currently inaccessible to interference-based methods.

Solving partial differential equations with neural operators significantly reduces computational costs but remains bottlenecked by high training data requirements. Active learning offers a natural framework to mitigate this by selectively acquiring the most informative samples in an iterative manner. We introduce physics-based acquisition - a novel physics-informed active learning algorithm that leverages the partial differential equation residual to guide data selection. We validate the method by presenting numerical experiments for the 1D Burgers equation and the 2D compressible Navier-Stokes equations. We show that, in our experiments, physics-based acquisition consistently outperforms random acquisition and matches the state of the art in data efficiency. At the same time, it has the unique advantage of injecting a physics inductive bias into the training process, ensuring that simulation cost is spent where the model's physical understanding is weakest.

Light scattering by two-dimensional (2D) van der Waals heterostructures (vdWHs) is immense, especially given their infinitesimal volume, thus enabling strong light-matter interactions. Surface 2D polariton waves manifest through large concentration of electromagnetic field in vertical direction, normal to their propagation. By confining vdWH materials into 2D photonic shapes, one can manipulate and compress light in lateral directions. Scattering-type scanning near-field optical microscopy is a perfect tool for direct imaging of the propagating polaritons and studying the properties of confined polaritons in nanostructures. Though, thus far the quantitative analysis, such the wavelength extraction, has been challenged for confined polaritons by incapability of mapping of the wave period on sub-wavelength scale and difficulty of identifying an adequate substrate's "background" to subtract. Here, an analytical approach is developed to reveal the local propagation constant of confined polaritons under abovementioned constraints and map it with the sub-wavelength resolution. Applied to analysis of the SiC/2D-Ag/EG (epitaxial graphene) photonic nanostructures, the technique uncovered that the polaritons are highly confined in both vertical ($\simλ$/50) and lateral directions ($\simλ$/40) by 2D metal.

This paper presents our research software engineering (RSE) experiences over two years with libNEGF, a quantum transport code. We describe practical approaches to code quality assurance--including continuous integration, automated testing, and compiler warning correction--and performance engineering through continuous benchmarking. Our systematic application of these practices revealed critical defects: uninitialized memory reads, out-of-bounds writes, and notably, a misunderstood mathematical model in our boundary condition handling. We also document how continuous benchmarking exposed performance regressions caused by HPC system configuration changes. Our findings provide data points suggesting that a dangerous class of defects--equivalent to undefined behavior in C/C++ and processor-dependent behavior in Fortran--is as prevalent in Fortran scientific codes as elsewhere. While libNEGF is implemented in Fortran, most recommendations are applicable to scientific software regardless of implementation language, and they can be implemented selectively or in their entirety for both new and existing projects.

Olfactory search in turbulent environments is a sensorimotor challenge solved with remarkable efficiency by many animals, yet replicating this ability in artificial systems remains difficult because detections are intermittent and wind direction fluctuates strongly, rendering standard search strategies unreliable. We introduce a wind-relative reinforcement-learning framework in which an agent navigates a turbulent plume with a single internal variable -- the elapsed time since the last odor detection -- and selects actions relative to a locally estimated wind direction filtered through an exponential memory kernel. Policies are trained and evaluated in direct numerical simulations of turbulence, capturing the multi-scale characteristics of velocity and odor fields in natural environments, both in the presence and absence of a mean wind. In a mild mean wind, the learned policy outperforms cast-and-surge regardless of the wind memory time, yet adapts its movement pattern to wind-estimation quality. In isotropic turbulence, performance peaks at an intermediate wind memory time, identifying temporal wind integration as a regime-dependent resource. Our results highlight the importance of developing and validating olfactory-navigation strategies under realistic turbulent conditions, and offer a compact design principle for minimal robotic olfactory navigation and testable predictions for biological search behavior.

We introduce a random matrix framework for studying statistical-mechanical lattice systems through spectral observables. Equilibrium configurations sampled from a Boltzmann measure are mapped to matrix ensembles whose covariance structure is inherited from the spatial correlations of the underlying model. This construction maps real-space correlation functions to a momentum-space variance profile, providing a direct bridge between statistical-mechanical correlations and correlated random matrix ensembles. We derive this variance profile in finite-correlation-length and critical regimes, and compute spectral moments within a Wick-contraction expansion. A complementary self-consistent description of the bulk density is developed using the resolvent formalism. These analytical methods are benchmarked against Monte Carlo data for the two-dimensional Ising model and three-dimensional Edwards--Anderson spin glasses. In both cases, the spectra evolve from the semicircle law at high temperature to model-dependent critical forms reflecting the structure of correlations. The framework, therefore, provides a quantitative spectral route to probing collective behavior in ordered and disordered statistical systems, while also defining a class of physically motivated correlated random matrix ensembles.

Fourier transform infrared nanospectroscopy (nano-FTIR) is a novel, increasingly adopted characterization method that leverages decades of established knowledge in infrared spectroscopy at the nanoscale. It opens up new possibilities in the characterization of composite materials and nanophotonic systems. Besides the rapid adoption and new possibilities, the nanoscale nature of these measurements poses new challenges for infrared spectroscopy. The current implementations of hyperspectral image acquisition at high spatial resolution suffer from significant artifacts due to thermal instabilities, which heavily affect positioning. As a result, the spatial and spectral fidelity of the measurements can be unreliable for long acquisitions. Here, we propose a new nano-FTIR measurement methodology based on step-scan interferometry and image registration. We demonstrate that the method provides superior spatial fidelity for photonics research and enables the collection of larger datasets, paving the way for bringing machine learning to characterize nanoscale heterogeneity.

As a rapidly emerging interdisciplinary field that intrinsically integrates microwave and photonics, microwave photonics (MWP) provides disruptive solutions to overcome the fundamental bandwidth of conventional electronic systems. By exploiting the inherently ultra-wide bandwidth and low-loss characteristics of photonic technologies, MWP enables the generation, transmission, processing, and detection of microwave, millimeter-wave, and terahertz signals. Representative breakthroughs include fully photonic microwave radar systems, photonic analog-to-digital converters with bandwidth up to 320 GHz, and photonic wireless communication systems achieving data rate as high as 616 Gbit/s. Meanwhile, the rapid growth of artificial intelligence (AI) is reshaping scientific research, engineering, and daily life in unprecedented ways, such as AI for science/engineering and AI co-scientist/assistant. Correspondingly, AI is profoundly reshaping MWP in all aspects, ranging from signal generation, transmission to signal processing and detection. AI has revolutionized the design, simulation, fabrication, testing, deployment, and maintenance of MWP systems, delivering autonomous operation and exceptional efficiency beyond traditional systems. Motivated by these developments, this Review Paper provides the first comprehensive overview of AI-enabled MWP, systematically summarizing the state-of-the-art advances and presenting insights for both the academic community and the broader public.

Predictive simulations and experimental design involving extreme aero-chemo-thermo-mechanical regimes require high-fidelity material representation across diverse physical states. However, data for metals, polymers, and propellants, explosives, and pyrotechnics (PEP) remain fragmented, obstructing traceability for formulators, experimentalists, and simulation engineers. This work introduces Lumina, a modular Python-based informatics framework that centralizes multiscale material data from atomistic simulation datasets to macro-scale experimental records, within a unified repository. Lumina employs a hierarchical XML-based schema and a dynamic runtime parsing mechanism to enable schema-independent parameter extraction. Beyond storage, the platform provides computational modules to visualize model fits, allowing experimentalists to optimize design of experiments (DoE) and formulators to validate chemical behaviors against benchmarks. This structured architecture serves as a high-fidelity pipeline for training machine learning models and enhancing the accuracy of predictive simulations. To streamline multi-disciplinary workflows, Lumina integrates a conversational AI assistant for intelligent material retrieval and natural language querying. By consolidating multiscale data into an extensible ecosystem, Lumina provides a scalable foundation for data-driven discovery and predictive modeling in advanced defense and aerospace engineering.

The 2025 Bondi Beach mass-shooting was perpetrated by individuals inspired by ISIS (Islamic State) propaganda that increasingly featured anti-Semitic hate content following the October 2023 start of the Israel-Palestine war. Similar stories hold for other types of hate attacks, e.g. against Muslims on May 18, 2026. There is an urgent need to get ahead of future threats by understanding how and when a newly created piece of hate content will spread system-wide online. We present a two-species coalescence-fragmentation model with Susceptible-Infected-Recovered dynamics that incorporates the following published empirical features: (1) New pieces of hate content tend to be generated and promoted by a subset of in-built communities on less regulated platforms. (2) These `hate' communities create links (hyperlinks) with each other and with non-hate communities across all platforms to form dynamically evolving clusters (i.e. coalescence) across which new hate content can then spread. (3) These clusters can get broken up by moderator shutdowns (i.e. fragmentation). We present numerical solutions and derive two levels of approximate mean-field theory: Effective Medium Theory (EMT) and Beyond Effective Medium Theory (BEMT). Both numerical and analytic solutions reveal that system-wide spreading is governed by re-entrant threshold phases: as the fraction of hate communities varies, the system can transition from spreading to no-spreading and back to spreading. The derived analytic formulae give explicit insight into how these phase boundaries might be manipulated to prevent system-wide spreading. More broadly, the re-entrant phase behavior warns that policies which steadily reduce the number of hate communities can initially succeed but then backfire if pushed further, suggesting that blanket requirements for platforms to simply do `more' are over-simplistic.

The far-field emission of large-area vertical-cavity surface-emitting lasers (VCSELs) is commonly associated with multimode, high-divergence beam profiles, limiting applicability in high-brightness free-space systems. We investigate angular emission characteristics of a 1 mm-diameter ring-aperture watt-class VCSEL and establish a theoretical framework capturing the formation of its far-field radiation patterns. Modeling the near field as an azimuthally modulated ring distribution and evaluating the far field within the Fresnel approximation, we demonstrate that a quasi-Gaussian far-field profile emerges from combined lower-order azimuthal modes, even in a highly multimode cavity. Experimentally, we observe a current-driven transition of the far-field distribution from a high-divergence ring at low injection levels to a narrow central beam at elevated currents. At high drive currents, the emission approaches a near-Gaussian profile with a full width at half maximum of 8°, while maintaining watt-class output power. Angle-resolved spectroscopy associates the central emission with longer-wavelength, lower-order modes, whereas the outer ring originates from shorter-wavelength, higher-order contributions. Combined with electroluminescence measurements and wavelength-dependent photon lifetime analysis, these results demonstrate that spectral and angular emission are determined by the interplay between wavelength-dependent material gain and angle-dependent cavity losses. This approach establishes a general framework for controlling beam divergence and modal content in large-area VCSELs, enabling high-power operation with near-Gaussian, low-divergence beam profiles.

Post-translational modifications (PTMs) play essential roles in regulating protein structure, function, and cellular signalling. However, peptide level discrimination of hydroxylation at the single-molecule level remains difficult. Here, we report a particle-in-pore single-molecule surface-enhanced Raman spectroscopy (SERS) platform combined with peak occurrence frequency (POF) analysis and a one-dimensional convolutional neural network (1D-CNN) for discriminating hydroxylated and non-hydroxylated HIF peptide fragments. Three peptide pairs containing the Pro-564 hydroxylation site, with lengths of 7, 9, and 15 amino acids (AAs), were investigated. POF analysis revealed reproducible hydroxylation-dependent spectral changes in the 7AA and 9AA peptide pairs, which were attributed to changes in adsorption conformation and surface interactions. CNN-based classification achieved post-evaluation accuracies of 72.98%, 78.55%, and 89.74% for the 7AA, 9AA, and 15AA peptide pairs, respectively, with AUC values above 0.80 for all the pairs, indicating a reliable discrimination. Gradient-weighted feature visualization further showed that CNN-sensitive regions overlapped with recurrent POF features, supporting the chemical relevance of the learned classification patterns. Notably, for the 15AA peptide pair, the enhanced citrate-associated band suggests that hydroxylation can substantially alter peptide-gold nanoparticle adsorption behaviour. This adsorption-mediated effect may amplify hydroxylation-induced spectral differences and contribute to the improved discrimination accuracy despite the increased structural complexity. These results demonstrate that the particle-in-pore sensor, assisted by deep learning, can capture hydroxylation-induced spectral and adsorption changes in peptide fragments, providing a promising strategy for ultrasensitive analysis of weak PTM signatures in peptides.

Thin-film lithium niobate (TFLN) electro-optic modulators are attractive for high-speed optical interconnects, but scalable transmitter architectures require not only high modulation bandwidth but also multi-channel optical power distribution and practical laser-to-chip integration. Here, we demonstrate a hybrid-integrated 1 * 8 TFLN electro-optic modulator array passively butt-coupled to a 1550 nm distributed-feedback laser. The chip integrates a three-stage cascaded 1 * 2 multimode-interference splitter, spot-size converters, eight traveling-wave Mach-Zehnder modulators, thermal tuning electrodes, and on-chip 50 Ω terminations. The cascaded splitter provides uniform optical power distribution with a maximum normalized power deviation of 9.7%, while the optimized electrodes enable electro-optic 3 dB bandwidths exceeding 40 GHz for all channels. The measured half-wave voltages are 3.60-3.83 V, corresponding to VπL products of 2.52-2.68 V cm for a 7 mm modulation length, and the extinction ratio reaches approximately 25 dB. The bare-chip insertion loss is 15.19-16.55 dB, and DFB laser bonding introduces an additional coupling loss of approximately 5 dB while preserving channel uniformity. These results establish a practical TFLN-based multi-channel modulator platform and represent a step toward compact hybrid-integrated optical transmitters for high-speed parallel interconnects.

Purely organic room-temperature phosphorescence (RTP) emitters are key components of programmable luminescent tags (PLTs), photonic devices for rewritable information storage and UV dosimetry. In this work, we systematically explore the design space of donor-acceptor and donor-acceptor-donor organic phosphorescent emitters in symmetric and asymmetric architectures. Phenoxathiine (PX) is introduced as an alternative donor to thianthrene (TA), combined with benzophenone (BP) or pyridine (Py) as acceptors. Through photophysical characterization, quantum chemical simulations, and PLT device testing, we identify structure-property relationships and, in particular, investigate the impact of the individual moieties on the emission properties and stability. The RTP emission wavelength is primarily tunable through the donor moiety: PX-based emitters emit sky-blue (λ_P = 480 nm), while TA-based emitters emit in the green (λ_P = 520 nm) due to an increased Stokes shift. The acceptor unit strongly influences the phosphorescence quantum yield, with Py-based emitters systematically outperforming BP-based ones. All newly synthesized PX-containing emitters show sufficient performance in PLT devices, though with reduced photostability compared to TA-based counterparts. Together, these results demonstrate that systematic donor-acceptor design enables predictable control over RTP emission properties, advancing the rational development of high-performance RTP-based photonic devices.

We report an optically modulated experimental realization of a photonic time crystal (PTC) in the microwave regime, demonstrating for the first time that the PTC exponential growth can overcome losses and finite-size constraints of a practical spatio-temporal system and yield stable positive terminal gain over a continuous broadband frequency range. The developed experimental platform is a purely time-modulated capacitor (TMC) microwave circuit based on a microstrip transmission line, in which synchronized optical modulation of reverse-biased photodiodes generates strong (94.5 %) temporal modulation of the effective capacitance at 200 MHz. Broadband amplification consistent with a momentum band gap (MBG), a defining signature of photonic time-crystal physics, is observed, with a peak gain of 3.8 dB over a 65 MHz bandwidth. In addition, a narrow parametric resonance appears at the center of the band gap, reaching 4.8 dB. This sharp peak is associated with the spatial inhomogeneities of the lumped-element realization, while the corresponding homogeneous distributed system retains the Floquet-mode structure of a photonic time crystal. We show that finite microwave TMC implementations inherit the defining physics of PTCs, including phase-invariant non-resonant amplification and slow-light behavior inside the momentum band gap, while finite-size and loss mechanisms transform the ideal semicircular PTC gain profile into a continuous asymmetric non-Lorentzian gain band characterized by a Pearson type IV distribution.

We reveal the existence of a universal upper bound on the magnetoelectric coupling of any bi-isotropic nanoparticle. The bound arises solely from energy conservation, making it independent of the specific material properties of the nanoparticle and illumination conditions. Moreover, the bound does not rely on reciprocity, being identical for reciprocal (chiral) and non-reciprocal (Tellegen) nanoparticles. We further show that the chiral Mie coefficient of spherical particles of arbitrary optical size obeys the same bound across all multipolar scattering channels. Our results introduce a universal metric on the magnetoelectric coupling of bi-isotropic objects, setting identical limits on chiral and Tellegen light-matter interactions at the single particle level.

Opinion formation models typically represent each individual as a single variable. However, in practice each individual holds interconnected beliefs whose internal organization may influence collective outcomes. To explore this dependence, we study a three-state opinion model on a network of networks in which each agent has an internal belief graph and interacts with other agents through an external social graph. Each belief can take two opposite polarized states or a neutral one and a neutrality parameter tunes the relative conviction of the neutral stance. We incorporate temperature into the model to account for external social agitation and for the tolerance of internal cognitive dissonance. We explore the stationary state and dynamics of the model using analytical approaches and Monte Carlo simulations on a fully connected external social graph, with internal belief topologies given by one-dimensional chains, cliques, and star-like structures, where there is a central core belief to which all other beliefs are connected. We find that the critical temperature at which the polarized consensus destabilizes increases with the addition of more beliefs to star-like agents but saturates in the case of ring- and clique-like internal topologies. We also consider binary mixtures of agents with different internal topologies in equal proportions, showing that the interplay between agents is regime-dependent, with the dominant topology depending on the value of the neutrality parameter.

Active matter systems under confinement display persistent surface motion and a strong boundary affinity. However, despite extensive studies of their positional dynamics, much less attention has been given to the corresponding orientational behavior. Here, using molecular simulations of an active Brownian particle confined within a hard circular boundary and the Fokker-Planck equation, we show that the positional distribution of the particle is directly coupled to orientational fluctuations, as characterized by the conditional orientational distribution. Confinement generates two preferred tangential orientational states connected by stochastic flipping pathways: rapid boundary-localized switching and slower bulk-mediated excursions. Further, the positional distribution exhibits a nontrivial power-law decay with distance from the boundary that is closely linked to curvature-induced bistable orientational states and the variance of the associated conditional distribution. The mean waiting time between flips exhibits power-law dependence on the confinement strength. Our results establish that the interplay between orientational fluctuations, bistability, positional accumulation, and stochastic switching governs the observed dynamics of active particles under confinement, providing a framework for understanding transport, exploration, and escape processes in confined active systems.

We characterize spin-polarized lasing in a two-dimensional photonic lattice fabricated from a GaAs/InGaAs semiconductor microcavity sample. The lattice is defined by a staggered arrangement of rounded rectangular micrometric mesas that laterally confine and couple the optical modes. Polarization-, angle-, and energy-resolved micro-photoluminescence measurements reveal the transition from the strong-coupling regime to photon lasing, accompanied by extended spatial coherence across several lattice unit cells. Under circularly polarized nonresonant excitation, the emitted light acquires a controllable circular polarization whose handedness follows that of the pump. These results establish photonic-lattice VCSELs as a platform for spin-controlled coherent emission in extended optical systems.

Topological phononics extends the foundational concepts of topological condensed matter physics to the realm of lattice vibrations and classical mechanical waves, unlocking robust, defect-immune states and phenomena beyond the reach of conventional phononic engineering. This review provides a unified, systematic framework for understanding topological phonons across natural and artificial systems, spanning solid-state materials, acoustic/mechanical metamaterials, and non-Hermitian platforms. We cover the core theoretical principles -- from Berry curvature and symmetry-protected topological invariants to bulk-boundary correspondence -- alongside experimental advances in probing topological phonon states via inelastic scattering and momentum-resolved techniques for solid-state phonons as well as pump-probe measurements in acoustic/mechanical metamaterials. Key topics include Weyl/Dirac/nodal-line phonons in crystalline solids, symmetry-engineered topological phases in metamaterials, non-Hermitian effects (exceptional points, skin effect), and emergent directions such as Floquet engineering, synthetic dimensions, and real-space topological textures (skyrmions, merons). We also highlight technological applications in robust waveguides, on-chip surface-acoustic-wave devices, and acoustofluidics, while outlining future challenges and opportunities in quantum phononics, nonlinear topological phenomena, and interdisciplinary integration with photonics and electronics. This review serves as a comprehensive guide across physics, materials science, and engineering, bridging fundamental theory with cutting-edge experiments and innovations in topological phononics.

Incoherent photonic neural networks (PNNs) provide a robust platform for analog optical computing, yet efficient implementation of native signed operations remains challenging. Existing incoherent PNNs approaches often require additional spatial channels or temporal encoding steps to represent bipolar input signals, resulting in hardware overhead that scales with system size. Here, we demonstrate a dual-wavelength incoherent photonic architecture that natively supports both signed inputs and signed weights on a thin-film lithium niobate platform. By encoding complementary signal components onto two wavelength channels and performing computation within a shared physical path, the proposed scheme eliminates duplicated weighting units. As a result, the additional hardware overhead associated with signed computation remains constant per multiply accumulate operation, independent of matrix size. The fabricated device exhibits a modulation bandwidth exceeding 40 GHz and achieves four-quadrant optical multiplication with a standard deviation error of 1.27%. System-level functionality is validated through neural-network classification, achieving 95.1% accuracy on the Moons dataset and 91.63% on MNIST. These results establish a practical route toward scalable incoherent photonic computing systems with native bipolar processing capability.

Photoinduced force microscopy (PiFM) enables nanoscale visualization of optical responses by directly detecting photoinduced forces without relying on luminescence. In molecular assemblies, intermolecular polarization coupling can generate collective excitation modes and chiral optical responses that are absent in isolated molecules. In this study, we theoretically investigate PiFM images of ZnPc molecular assemblies using the discrete dipole approximation combined with nonlocal molecular susceptibilities. Under linearly polarized illumination, bonding and antibonding polarization-coupling modes are found to produce characteristic spatial distributions in both the optical force spectra and PiFM images of molecular dimers and tetramers. Furthermore, under circularly polarized illumination, intermolecular coupling and asymmetric molecular packing generate enhanced local circular dichroism distributions characterized by large asymmetric factors and spatially varying chiral contrasts. These results demonstrate that PiFM can spatially resolve collective polarization modes and local chiral optical responses in molecular assemblies, providing insight into nanoscale intermolecular optical interactions.

Time-modulated systems have received growing interest in recent years. They allow us to tailor effects, such as frequency conversion, single-direction propagation, etc. For the microwave band, semiconductor elements, such as varactors, are usually used as time-modulated elements but their modulation frequency has been limited to the few-gigahertz range. Recent advances in nanoplasma switches, i.e., two-state electronic switches based on a gas discharge in a nanometer-scale gap, provide a new potential for developing time-modulated systems with high operating frequencies. Here, we develop an analytical framework based on the time-Floquet method for the design of nonreciprocal time-modulated devices based on two-state time-modulated elements, for instance, nanoplasma-based switches. A practical example of a microwave isolator operating at 100~GHz frequency is developed and studied both analytically and using full-wave simulations. A potential realization in a parallel-plate waveguide is also simulated numerically.

Silicon photonic integrated circuits critically depend on compact on-chip light sources, for which nanowire (NW) lasers are an attractive solution. However, their practical implementation is often limited by broad emission linewidths and poor frequency stability resulting from weak optical feedback. Here, we integrate individual GaAsSb NWs by transfer-printing onto silicon-on-insulator (SOI) racetrack resonators to realize optical feedback at silicon-transparent wavelengths. Finite-difference-time-domain simulations reveal efficient coupling between the hybrid NW-waveguide mode and the fundamental TE resonator mode, with calculated cavity Q-factors exceeding 10$^4$. Experimentally, we observe feedback-induced lasing emission at a low threshold (P$_{th}$) of 8.6 $\pm$ 1.8 $μ$J/cm$^2$. Compared to identical NW lasers without SOI resonator, the linewidth is reduced by more than a factor of four at 3P$_{th}$ and remains stable below 1.8 meV up to 5P$_{th}$. Our results demonstrate NW-based light sources on SOI and show that tailored resonator designs enable improved linewidth control and frequency stabilization.

Temporal ghost imaging (TGI) enables ultrafast temporal signal recovery using slow detectors, offering a promising route for high-speed mid-infrared (MIR) detection. However, conventional schemes remain limited in temporal resolution by the modulation bandwidth or pattern timescale, and are mostly confined to structured illumination. Here, we demonstrated a high-resolution MIR single-photon computational TGI system, which integrated nonlinear structured detection with sub-pixel temporal shifting. A pre-programmed near-infrared pump serves as a temporally optical gate to drive sum-frequency generation in a nonlinear crystal. Consequently, MIR waveforms at 3.4 $μ$m were upconverted, and captured by a room-temperature silicon detector. We realized sub-pixel operation by fractional-bin temporal stepping of the gate and multi-shot fusion via pseudo-inverse reconstruction. The sub-pixel shifting strategy decouples the achievable resolution from modulation speed, enabling 40 ps temporal precision at a driving rate of only 3.125 Gbps. This performance surpasses both detector jitter and pattern-rate limits, while maintaining single-photon sensitivity. The presented paradigm establishes a versatile route for ultrafast MIR waveform reconstruction, opening new opportunities in high-resolution infrared sensing and quantum photonics.

We investigate controlling the lateral Goos-Hänchen (GH) shift for a TM-polarized field reflected from Otto structure containing four level N-type atomic medium. The N-type atomic configuration can be formed by coupling the standard three-level $Λ$ system to an additional upper energy level through a coherent driving field. The medium can then be switched from transparent to absorptive under the effect of the driving field. In the Otto structure, an air gap typically separates a dielectric prism from a metal film. We show that the sign and magnitude of the GH shift can be highly controlled when the air gap is replaced by the coherent atomic medium. This can be achieved by adjusting the strength of the applied fields to the atomic medium, while the geometrical characteristics of the proposed structure are unchanged.

Edge-enhanced imaging is critical for visualizing weakly absorbing and transparent objects. Extending this functionality into the mid-infrared (MIR) region enables chemical sensitivity and improved imaging performance for biomedical, material, and remote-sensing applications. Here, we present a wide-field MIR edge-enhanced upconversion imaging system that integrates vortex-pump complex-amplitude engineering with aperiodic quasi-phase matching. In contrast to the bright-field modality, the wide-field edge-enhanced operation shows sensitive dependence on the crystal position relative to the Fourier plane. The system achieves single-shot operation with a 25-mm field of view and 79-$μ$m spatial resolution, yielding a record-high space-bandwidth product of $7.9 \times 10^4$. We show that this capability enables direct visualization of phase gradients in transparent optical elements and enhances structural contrast in biological specimens. The demonstrated architecture combines high sensitivity, spectral specificity, and robust edge detection, offering a promising route toward advanced MIR imaging in industrial inspection and biomedical diagnostics.

Achieving diffraction-limited focusing of high-power laser pulses to generate ultra-high intensities is crucial for developing compact laser-driven particle accelerators and exploring strong-field quantum electrodynamics. However, accurately diagnosing and optimizing the focal spots of petawatt (PW) laser pulses remains a significant challenge. In this work, we present an experimental methodology utilizing a twin-focus scheme to precisely characterize the intensity distribution and wavefront of focused PW femtosecond laser pulses, and employ it to elucidate their power-dependent evolution. Furthermore, we optimized the focal spots at full power via our in-situ wavefront correction method termed ``HotLoop', achieving a Strehl ratio of 0.80 for 1 PW laser pulses. Consequently, the cutoff proton energies in laser proton acceleration experiments were significantly enhanced. The success of this approach underscores the necessity of in-situ high-energy wavefront correction for ultra-high intensity laser-matter interactions.

The coherent lattice vibrations significantly impact physical and chemical processes in solids, such as heat transfer, displacive phase transitions, and thermal conductivity. Thus, probing lattice dynamics in real-space and real-time is essential for understanding ubiquitous phenomena in solids. High-harmonic spectroscopy (HHS) has emerged as a preferred technique for investigating static and dynamic properties of solids on ultrafast timescales. Yet, despite these accomplishments, the applicability of HHS to probe the influence of coherent lattice vibrations on electronic responses has remained unexplored. In this thesis, we explore the impact of coherent lattice dynamics on attosecond electronic responses in solids using HHS. We observe that coherent excitation of the in-plane phonon mode in graphene results in sidebands in the harmonic spectrum, separated by the frequency of the excited phonon mode. Additionally, we demonstrate the capability of HHS to characterize energy, polarization, phase difference, and the "chirality" of phonon modes. This thesis offers an avenue to probe phonon-driven processes in solids with sub-cycle temporal resolution. In the later segment, our focus shifts toward probing coherent lattice dynamics in real-space and real-time. We demonstrate that inelastic scattering techniques, combined with theoretical analysis, yield comparable results to those from time-resolved diffraction and imaging measurements within pump-probe configurations. Our findings exhibit excellent agreement with results from a time-resolved diffuse x-ray scattering experiment. Our proposed method serves as an alternative to time-resolved diffraction and imaging methods for probing lattice dynamics in real-space and real-time with atomic-scale spatiotemporal resolution.

Hybridization of resonances is known to overcome inherent limitations of individual systems, enabling advanced functionalities and applications. Here we discuss hybrid plasmonic-Mie resonators that emerged recently as a promising direction in advancing nanophotonic structures by synergistically combining the strong near-field enhancement of plasmonic components with the low-loss, multipolar resonances of dielectric Mie elements. We review the recent progress in the field, encompassing the fundamental physical principles, structural design strategies, material platforms, computational optimization approaches, and representative device implementations. Our discussion starts by evaluating the complementary characteristics of plasmonic and Mie resonances followed by a description of the coupling between these resonances in order to boost light-matter interactions. Afterward, we explore the performance of efficient hybrid resonators for different application areas. Apart from the conventional metal-dielectric systems, we consider the recent class of epsilon-near-zero (ENZ) materials, which can provide unique advantages in terms of field localization, phase engineering, and energy flow management in the vicinity of zero-permittivity conditions, offering more flexibility in designing hybrid nano-optical devices. Lastly, we point out potential research avenues aiming to improve functional and efficient nanophotonic devices, especially those involving emerging topological material systems, such as Sb2Te3, Bi2Te3, Bi2Se3, combining plasmonic amplification, dielectric confinement, and spin-dependent optical behavior.

Pentagonal gold bipyramids with dimensions of 75x25 nm and a longitudinal plasmon resonance (PR) at 753 nm are synthesized. For comparison, gold nanorods with a diameter of 20 nm, lengths ranging from 95 to 50 nm, and longitudinal PR from 945 to 644 nm were synthesized by chemical etching. The samples were characterized by UV-vis spectroscopy and transmission electron microscopy (TEM). It is shown that the absorption spectral quality factor of the bipyramids is significantly higher than that of the nanorods. To compare the nanoparticles as platforms for surface-enhanced Raman scattering (SERS), their surface was functionalized with thiolated nitrobenzene molecules (NBT). It is demonstrated that the SERS enhancement factor for the bipyramids is approximately three times higher than that for the nanorods. The red shift of the bipyramids' PR after functionalization with NBT molecules is also about three times greater than for nanorods with the same PR. This agrees with the theoretical estimate of the bipyramids' PR shift being more sensitive to variations in the refractive index of the external medium or the dielectric shell thickness than that of gold nanospheres and nanorods. The high efficiency of the bipyramids as thermosensitizers for converting laser radiation into heat in photothermal therapy is experimentally and theoretically demonstrated. Effective photothermal killing of E. coli was shown upon irradiation with a laser at the plasmon resonance wavelength using nanobipyramids or nanorods.

Manipulating materials properties with light drives advances in materials science and photonics. Hyperbolic metamaterials are promising candidates as next-generation quantum optical media. They support Bloch plasmon polaritons, which are characterized by potentially infinite wave-vectors and long lifetimes, but cannot be excited through direct light illumination due to momentum mismatch. Here, we experimentally show that a transient grating, formed via interference of fully coherent seeded free-electron laser pulses in a thin insulator film, enables the excitation of Bloch plasmon polaritons in an underlying hyperbolic metamaterial. Finite element simulations confirm the role of the transient grating in facilitating phase-matching and mode excitation. Our findings demonstrate a route to spatiotemporally excite Bloch plasmon polaritons modes, offering an alternative to permanently nanostructured gratings and potentially enabling ultrafast control of optical modes excitation.

The design of structures and vehicles subject to fluid-structure interaction (FSI) often requires high-fidelity coupled analysis. While the design variables pertain to the structure, the computational cost is dominated by the fluid solver, making iterative optimization prohibitively expensive. This paper presents an adaptive multi-fidelity optimization method combining high-fidelity FSI analysis with a lightweight surrogate for fluid-induced loads and a decision model that selects between surrogate and high-fidelity fluid evaluations. During optimization, completed FSI analyses incrementally update a non-intrusive surrogate model based on nearest-neighbor search and radial interpolation. A hybrid Lagrangian-Eulerian mapping function is developed to transfer fluid loads between structural designs. The evolution of surface orientation is handled by decomposing the traction vectors into local orthonormal bases. An adaptive Gaussian process regression model is employed to predict surrogate error and quantify uncertainty, allowing risk-aware selection of when coupled analysis is required. As design evaluations cluster near the optimum, the accuracy of the surrogate model naturally improves, thereby reducing the reliance on the fluid solver. It requires no offline training, preserves the high-fidelity structural model in all design evaluations, and ensures that the final design is evaluated by high-fidelity FSI analysis. The fundamental idea is justified theoretically using a simplified model problem, which shows that the leading-order error is a monotonically increasing, concave, and bounded function of the fluid added mass. The framework is demonstrated on two benchmark problems. For shape optimization of a flexible panel under shock loading, results show an $80\%$ reduction in computational cost while maintaining accuracy within $2.3\%$ of fully high-fidelity FSI optimization.

We extend the tensor-product direct solver from the Laplacian to the Schrödinger operator $-Δ+ V$. When the potential $V_1$ is separable, the operator $-Δ+ V_1$ is inverted or exponentiated at cost $O(N^{1+1/d})$ in $d$ dimensions via per-axis eigendecomposition. On a single NVIDIA A100 GPU, this costs less than one second for $10^9$ degrees of freedom in 3D. For non-separable potentials $V = V_1 + V_2$, the same solver provides a preconditioner $(-Δ+ V_1)^{-1}$ for the preconditioned conjugate gradient (PCG) method and a propagator for operator-splitting time integrators. For bounded $V_2$, we prove that the preconditioned operator has a bounded condition number and a clustered spectrum with at most finitely many outlier eigenvalues, independently of the mesh size, and also independently of the domain size when $V_1$ is a confining potential. This explains the mesh- and domain-independent PCG iteration counts observed in practice. We apply this method to ground state computation via inverse iteration for linear problems and via the $a_u$ gradient flow for Gross--Pitaevskii energy in 3D, and also Hamiltonian simulation via the approximated qHOP and Magnus-2 splitting methods from 3D to 9D on a single NVIDIA GH200 GPU.

We present calculations of the millielectronvolt-scale x-ray scattering spectra of multilayered dynamic-compression targets comprising an unstructured ablator layer and a crystalline, textured sample layer. Our model builds on the classic formulation of x-ray thermal diffuse scattering by Warren [B. E. Warren, Acta Crystallogr. 6, 803 (1953)] and includes both elastic and first-order (single-phonon) inelastic scattering contributions to the dynamic structure factor $S(\mathbf{q},ω)$. We focus on the umklapp scattering regime (i.e., at momentum transfers outside the first Brillouin zone) where the ablator scattering that threatens to overwhelm the inelastic scattering from the crystalline layer of interest is suppressed. We show that, despite the considerably more complex structure of the inelastic scattering spectra in this intermediate-$q$ regime, it is still possible to reliably deduce the temperature of the crystal using Dornheim's Laplace-transform--based formalism [Dornheim et al., Phys. Plasmas 30, 042707 (2023)], regardless of the details of the sample's texture.

We introduce Pairwise Distance-Diffusion Analysis (PDDA), a geometric framework for estimating the Hurst exponent from distance plots of long-memory stochastic processes. A single construction yields two complementary routes: R/S-PDDA, a geometric reformulation of the classical rescaled-range definition, and MSD-PDDA, based on mean-squared-displacement scaling, classically used in anomalous diffusion. We extend PDDA to multivariate isotropic and anisotropic processes and derive an explicit link between temporal persistence, range dimension, and recurrence statistics, providing a unified distance-based foundation for Hurst analysis.

The jellyfish Clytia hemisphaerica possesses astounding regenerative capacities and is able to close even large wounds within a few hours. This rapid pace of wound closure raises the question whether tissue mechanics, rather than tissue restructuring or cell proliferation, might be underlying the process. We tested this possibility by asking if simple pre-strains within the jellyfish umbrella would be capable of initiating wound closure in a jellyfish body geometry. To this end, we employed an in silico spring lattice model, a coarse-grained model of elastic materials which has previously been established to study tissue mechanics problems. We found that, using radially contractile (but not radially extensile) strains, wound closure can indeed be initiated across a wide range of conditions. This is even true for large cut sizes and, hence, small pieces of remaining tissue material, in good agreement with the experimental findings. Finally, we derived an analytical expression for the expected amount of achievable closure as a function of the residual material angle. These results establish important foundations for further investigations of the biophysics underpinning jellyfish regeneration.

Many complex systems combine dense background structure with sparse contextual information. We introduce a diffusion-based framework for analyzing how sparse condition-specific layers reshape diffusion geometry in multilayer hypergraphs. Each layer is represented as a weighted hypergraph, layers are coupled through shared entities, and random walks on the coupled system induce multiscale diffusion distances between nodes. We apply the framework to disease-conditioned gene networks by coupling a dense MSigDB functional gene-set layer to sparse disease-specific DGIdb drug-gene hypergraphs, with disease-associated drugs selected from DDDB and HumanNet-GSP used to define external gene weights. Across Bipolar Disorder, Schizophrenia, Leukemia, and Breast Cancer, the disease-specific layer contains less than 2 percent of genes in the coupled system, yet substantially changes diffusion distances and community structure. Centrality analysis suggests that this disproportionate effect arises because DGIdb-associated genes occupy influential positions in the MSigDB-derived functional network. The resulting diffusion-derived communities are stable under subsampling and show coherent post hoc functional enrichment, including signaling and neurotransmission categories in neuropsychiatric diseases and immune, translational, and metabolic categories in cancer-associated diseases. Community-level comparisons further reveal disease similarities not reducible to direct DGIdb gene overlap, including a Breast Cancer-Schizophrenia relationship consistent with recent biomedical evidence. These results show that sparse contextual layers can induce interpretable nonlocal changes in higher-order network geometry.

Sensitive detection of terahertz (THz) radiation is fundamental to progress in spectroscopy, advanced wireless communication, and the realization of emerging quantum technologies. However, the intrinsically low photon energies in the THz range combined with thermal background radiation tend to constrain detector performance when operating at ambient temperatures. Here, we demonstrate efficient room-temperature THz detection based on nonlinear upconversion in the organic crystal N-benzyl-2-methyl-4-nitroaniline (BNA) to resolve frequencies from 1 to 7.5 THz. The system encompassing spectral filters and a single-photon counter achieves an overall detection efficiency of 2% for sum-frequency generated photons. This enables the detection of a train of 50 000 terahertz pulses carrying, on average, fewer than 0.04 photons per pulse, with a signal-to-noise ratio of unity. At a higher flux, when ~60 photons per pulse impinge on the BNA crystal, the per-pulse detection probability reaches 50%. After accounting for loss mechanisms in the setup, the nonlinear THz-to-near-infrared conversion efficiency in BNA exceeds 75%. These results demonstrate the feasibility of quantum experiments relying on single-photon-level THz detection via upconversion in nonlinear crystals in ambient conditions.

Nanomaterials stacked on-demand, such as rotationally assembled two-dimensional (2D) van der Waals (vdW) layered compounds, provides a versatile platform for quantum simulation and the exploration of exotic electronic phases. Currently, however, such nanoassemblies remain largely confined to inefficiency, manually operated process, limiting their potential for probing emergent physical phenomena. There is a pressing need in the field for high-precision, automated assembling techniques, especially for the scalable fabrication of 2D twistronic heterostructures. Here, we present an intelligent automation system dedicated to the fabrication of van der Waals stacks, following the state-of-the-art protocol for dry transfer of exfoliated 2D materials. The system further employs metadata generated from each automated stacking procedure to perform reinforcement learning, thereby continuously bettering its performances. As a concrete demonstration, we fabricate twisted bilayer graphene (TBLG) -- known for its challenging preparation -- and exhibit its unconventional superconductivity near the magic angle. Our work may pave the way for high-throughput fabrication of low-dimensional nanomaterials including twistronic heterostructures, where integrating data mining and artificial intelligence can accelerate the discovery of novel physical phenomena.

Models of opinion dynamics aim to capture how individuals' opinions change when they interact with each other. One well-known model of opinion dynamics is the Deffuant--Weisbuch (DW) model, which is a type of bounded-confidence model (BCM). In the DW model, agents have pairwise interactions, and they are receptive to other agents' opinions when their opinions are sufficiently close to each other. In this paper, we extend the DW model by studying it on networks with heterogeneous and adaptive edge weights between pairs of agents. These edge weights govern the interaction probabilities between the agents and thereby encode the idea that people are more likely to communicate with individuals with whom they have previously compromised or had other positive interactions. We prove theoretical guarantees of our adaptive edge-weighted DW model's convergence properties, the long-time dynamics of its edge weights, and the model's associated ``effective graph", which is a time-dependent subgraph that includes edges only between agents that are receptive to each other's opinions. We support our theoretical results with numerical simulations of our adaptive edge-weighted DW model on a variety of networks and find that including adaptive edge weights yields different qualitative dynamics for different types of networks. In particular, for small confidence bounds, we observe that incorporating adaptive edge weights decreases the convergence time for dense networks but increases the convergence time for sparse networks.

TiO2 ferroelectric field effect transistors (FeFETs) with HfZrO2 (HZO) ferroelectric dielectric layers and bottom gate topology are fabricated for applications in neuromorphic systems. Two sets of devices are fabricated with different gate topologies by varying the thickness of the ferroelectric gate stack. Different device architectures are studied by varying the source drain length (LSD) and gate length (LG). The devices have high on/off ratios up to 10^7 with low leakage off currents <10^-12 A. Repeated cycle testing shows high reliability and a stable memory window. The devices have large memory windows ranging from 3 to 8 V.

Driven by the growing demand for miniaturized spectrometers for in-situ analysis, and point-of-care diagnostics, conventional spectrometers are often constrained by bulky architectures and pathlength-limited spectral resolution. Achieving high-resolution, single-pixel computational spectrometers is therefore critical for the realization of compact, on-chip systems. Here, we report a single-pixel spectrometer enabled by a single 2D material; few-layer GaSe-based photodetector, in which the Schottky barrier height modulation, governed jointly by applied bias and optical excitation, provides an efficient mechanism for spectral encoding without the need for bulky dispersive elements. The device exhibits a high peak-wavelength accuracy of ~0.78 nm across a broad operational bandwidth (300-700 nm) within a compact footprint of ~100 um^2 and resolves closely spaced spectral features with separations down to ~5 nm. The device operates at low bias (+/- 4V) with an ultralow dark current density ~0.3 pA/um^2 at 4V bias. These results establish a simple, scalable route toward compact, cost-effective spectroscopic systems for on-chip spectral sensing and portable hyperspectral imaging applications.

Online, comprehensive molecular profiling of exhaled breath provides a non-invasive window into human metabolism, yet current optical platforms are restricted by narrow instantaneous spectral coverage. Here, we present a novel ultra-broadband mid-infrared spectroscopic platform that enables simultaneous, high-sensitivity detection of a comprehensive profile of breath biomarkers. By integrating an intrapulse difference-frequency generation (IDFG) supercontinuum source spanning 2.9-11.5 $μ$m (2580 cm$^{-1}$) with a custom-built Fourier transform spectrometer, we achieve a spectral resolution of 0.1 cm$^{-1}$ - surpassing current laser-based approaches. Combined with a standardized online sampling system, the platform achieves sensitivities in the tens of parts per billion over three minutes, resolving dynamic metabolic changes of ammonia, methane, isoprene, acetone, carbon monoxide, and nitrous oxide. We demonstrate the system's utility through proof-of-concept case studies tracking responses to fasting, protein intake, and smoking. This calibration-free platform establishes a powerful and versatile tool for online breath analysis, with broad potential in clinical diagnostics and exposure monitoring.

High-energy (mJ) and high-peak-power (MW) multicycle terahertz (THz) pulses are essential for nonlinear THz spectroscopy and compact accelerator technologies, yet their generation by nonlinear optical frequency conversion remains inefficient and imposes severe demands on femtosecond driving lasers. Amplifying existing THz pulses offers an appealing alternative, but no power-scalable amplifier has been realized in the sub-THz regime. Here, we demonstrate an all-optical THz amplifier operating at 0.35 THz based on the modulation of nanosecond laser pulses by a weak THz field in periodically poled lithium niobate (PPLN). The THz-induced phase modulation is converted into an amplitude modulation using controlled group delay dispersion, forming a tailored pulse train that can efficiently drive high-energy THz generation in a second crystal, thereby amplifying the THz seed. By analogy to electronic klystrons, we term this device the Phlystron, in which the electron beam carrying the power is replaced by a photon beam. In this proof-of-concept experiment, a 3.3-fold increase in THz energy is achieved with commercial crystals. Scaling analysis indicates the potential for higher gain when using large-aperture PPLN devices and multi-stage amplification. The Phlystron thus provides a scalable route to powerful multicycle THz sources driven by readily available narrowband lasers.

International scientific collaboration is organized primarily by researcher-level logic and network dynamics in which scientists seek partners at the frontier of their field with little consideration of national affiliation. Research security policies that raise the friction costs of international collaboration are often assumed to operate against this logic, aiming to produce selective withdrawal from sensitive fields to deny knowledge transfer to specific countries. This paper tests that assumption against eight years of bibliometric evidence from China's scientific output from 2018 through 2025 across 27 Scopus subject categories. China's internationally co-authored publication share declined universally across all fields after 2018, consistent with China's push for domestic capacity maturation, but the pattern of decline is inconsistent with the deterrence prediction. Fields with high dual-use proximity, including computer science, materials science, physics and astronomy, chemical engineering, and engineering, showed the least contraction (3-6 percentage points), while fields with minimal dual-use salience (psychology, nursing, dentistry, and health professions) showed the steepest declines (8-24 percentage points). The findings suggest that governments raised the friction level but did not redirect the network nor suppress collaboration in sensitive areas. Researchers practiced adaptive participation, maintaining frontier collaborations while adjusting the form and language of their engagement. This pattern matches what the invisible college theory and the Ostrom knowledge commons framework predict.

With the rapid development of information and communication technologies in recent years, the transmission capacity of single-core optical fibers has nearly reached its physical limit. Space-division multiplexing based on multi-core fibers offers an effective solution to this bottleneck. Multi-core fibers feature high integration and large transmission capacity, and their unique structural characteristics also give them special value in fiber-optic sensing applications. Among various types of multi-core fibers, coaxial dual-core fibers (CDCFs) have shown promising performance in particle trapping, signal emission, and spectral analysis. To enable reliable interconnection between different types of multi-core fibers and single-core fiber arrays, this paper presents the design and fabrication of a fan-in device for coaxial dual-core fibers with different core diameters. The proposed method relies solely on cold-processing techniques and does not require any fusion splicing or thermal processing. The device is implemented on a V-groove substrate. Through structural design, fabrication, and experimental characterization, the average insertion loss of the ring core and the central core at a wavelength of 980 nm is measured to be 2.15 dB and 1.25 dB, respectively, demonstrating the successful fabrication of a coaxial dual-core fan-in device.

The present study considers the operation of a laser that incorporates a photonic time crystal (PTC), the purpose of which is to generate a field characterised by multiple widely separated optical frequencies. This laser is the subject of both a proposal and theoretical investigation. The laser comprises an active medium and a PTC within a small cavity constructed from two photonic crystals that are positioned in an overlapping configuration. PTC is modulated by an external field. The spikes in the laser field spectrum are separated by the PTC modulation frequency. The development of a quantum model of the laser with PTC has been achieved, and the analysis of a lasing mode with multi-frequency spikes has been made. The investigation focused on the study of lasing conditions, output power, and the lasing field spectra. The experimental realization of the multi-frequency laser with PTC under realistic conditions is discussed.

High-power structured light has a wide range of applications, from material processing and high-capacity optical communications to programmable electron beams, plasmas, and nuclear states. On-demand generation of structured light and adaptive control of beam profiles are essential for many practical applications, but are difficult to achieve at high power. Here, we demonstrate reconfigurable generation of structured light from a high-power multimode-fiber laser amplifier through full-field control of a low-power seed. An efficient nonlinear beam shaping scheme based on a local linear approximation of the complex nonlinear input--output relation is developed and realized in situ. Diverse structured beams such as Gaussian, Bessel, vector and orbital angular momentum beams are directly generated from the fiber amplifier at powers exceeding 500 W. Our scheme enables real-time programmability of structured light and is readily scalable to even higher power levels. This work provides a general framework for controlling high-dimensional nonlinear systems without accurate knowledge or tractable model.

The constitutive behavior of materials is modeled through relationships between stress, strain, and possibly additional internal variables. This results in relatively high-dimensional feature spaces for machine learning models rendering the efficient generation of informative datasets essential as brute force methods suffer from the curse of dimensionality. This work introduces a diversity-aware batch-mode query-by-committee active-learning strategy to generate datasets of maximum information content at minimum cost. In contrast to existing methods, this novel method selects multiple informative, non-redundant queries per iteration, enabling concurrent generation of informative datasets and reducing the number of machine-learning retraining cycles. A central component of this method is a cosine-similarity-based metric that complements the uncertainty criterion based on committee variance by promoting within-batch diversity. The query selection is guided by committee variance and a diversity-promoting criterion. The approach is benchmarked for efficient stress-space sampling in data-driven constitutive modeling. In this setting, a committee of support vector classifiers approximates the so-called yield surface, which is a manifold dividing the six-dimensional stress space into an elastic and plastic domain. We demonstrate that the method handles different batch sizes robustly, maintains high within batch diversity, and rapidly reduces committee uncertainty. The resulting machine learning yield surfaces achieve predictive accuracy comparable to sequential active learning, while requiring substantially fewer retraining cycles. This makes the proposed approach an efficient strategy for stress space sampling in data driven constitutive modeling and for reducing time to solution via concurrent data collection in each iteration.

Antireflection coatings are ubiquitous in optical systems, where they maximize transmission and suppress undesirable reflections by impedance-matching uniform interfaces. Extending this principle to metasurfaces, however, is fundamentally more challenging because wavefront control requires a library of geometrically distinct meta-atoms, each locally imposing a prescribed phase that is tethered to its transmittance. Here, we show that vertical integration resolves this constraint by allowing bilayer meta-atoms to operate simultaneously as a phase shifter and an impedance-matching stack. Using an effective thin-film model, we derive a design rule that links the effective indices of two independently patterned layers and identifies antireflective bilayer libraries with full $0$-$2π$ transmission-phase coverage. We realize this concept in a free-standing TiO$_2$/TiO$_2$ metalens operating at 1310 nm, which suppresses reflectance below that of bare glass while preserving diffraction-limited focusing. These results establish bilayer metasurfaces as a framework for co-engineering optical impedance and wavefront response at the meta-atom level.

This algorithm is designed to perform numerical transforms to convert data from the temporal domain into the spectral domain. This algorithm obtains the spectral magnitude and phase by studying the Coefficient of Determination of a series of artificial sinusoidal functions with the temporal data, and normalizing the variance data into a high-resolution spectral representation of the time-domain data with a finite sampling rate. What is especially beneficial about this algorithm is that it can produce spectral data at any user-defined resolution, and this highly resolved spectral data can be transformed back to the temporal domain.

Scanning helium microscopy (SHeM) is attractive for imaging delicate and insulating surfaces because it combines a non-destructive neutral-atom probe with strong surface sensitivity. However, large-working-distance pinhole instruments have so far been limited in spatial resolution. Here we report sub-micron resolution in a large-working-distance pinhole SHeM, with an intrinsic beamwidth of 340nm achieved at working distances of 770 μm to 850 μm. This sixfold improvement over our previous long-working-distance configuration is enabled by constrained optimisation of the atom optics together with a redesigned high-resolution pinhole-plate, a reduced pinhole diameter, an increased source--pinhole distance and a larger detector aperture. Beamwidth measurements agree well with the modified optimisation model and show that geometric, source-size and diffraction terms now contribute on a similar footing, placing the instrument in a near-optimised regime. The resulting combination of sub-micron beam size, useful depth of field and practical sample access is demonstrated on bacterial specimens and eroded diamond. The work establishes large-working-distance pinhole SHeM as a viable sub-micron imaging platform and extends its usefulness for topographic imaging and micro-diffraction applications.

The simulation of quantum transport in nanodevices requires the solution of the Dyson and Keldysh equations, a task dominated by the inversion of massive, block-tridiagonal matrices. While the Recursive Green's Function (RGF) method has long been the standard $O(N)$ solver for quasi-1D systems, its formulation has typically been restricted to sequential execution and nearest-neighbor interactions. In this work, we carefully reformulate RGF through the lens of Domain Decomposition and Schur Complement theory. This allows us to extend the recursive formalism to block $n$-diagonal systems (handling higher-order stencils) and to derive a parallel algorithm, Domain-Decomposition based RGF (DDRGF), which stitches macroscopic domains via reduced interface systems. We explore data dependencies in DDRGF in detail, by means of block-sparse structures and tracing back to the desired output as a block tridiagonal approximation, giving a clear, reproducible and extensible formulation. We validate these algorithms using \texttt{LibNEGF.jl}, a Julia-based implementation, demonstrating that the structural insights of domain decomposition provide a robust pathway for high-performance quantum transport simulations on modern multi-core clusters. The theory presented here lays down the base for tackling the Keldysh problem, to be similarly handled in future stages of our work. Although the target here is the acceleration of kernels in the non-equilibrium Green's function method, the algorithms and the implementations presented can be immediately used in any application involving block $n$-diagonal systems.

We present an accelerated ``on-the-fly'' coupled-cluster path-integral molecular dynamics (PIMD) method for finite-temperature simulations in which electron correlation and nuclear quantum effects are treated simultaneously. The approach is based on our quantum ring-polymer contraction (qRPC) technique, in which the inexpensive Hartree-Fock potential is evaluated on the full ring-polymer, while the expensive coupled-cluster correction is evaluated on the centroid only. This qRPC decomposition is combined with a second-generation Car-Parrinello-like dynamics of the Hartree-Fock reference and a basis-consistent extrapolation of the coupled-cluster and de-excitation amplitudes. The combination of all three acceleration layers is essential for making correlated PIMD calculations feasible. We apply the method to a proton shared by water and formaldehyde. Relative to classical nuclei, nuclear quantum effects broaden covalent X--H bond-length distributions, reduce the bias of the shared proton toward formaldehyde, and shift the mean proton-transfer coordinate from 0.206 to 0.135A. The probability of finding the proton closer to formaldehyde decreases from 81.7$\%$ to 61.1$\%$. The corresponding nuclear magnetic shielding tensors show that electron correlation and nuclear quantum effects are of comparable magnitude and can act in opposite directions. These results demonstrate that predictive simulations of asymmetric hydrogen bonds require a simultaneous treatment of correlated electronic structure and nuclear quantum fluctuations.

Data-centric materials science is changing how materials are discovered, optimized, manufactured, and qualified, yet many deployment-limiting materials problems still depend on experimental, processing-rich, device-level, and field-relevant data that are difficult to capture in conventional materials databases. This perspective argues that the Great Plains and adjacent interior research corridor can make a distinctive national contribution by organizing distributed experimental assets into a trusted regional materials-data ecosystem. The proposed model emphasizes FAIR metadata, provenance, persistent sample identifiers, uncertainty-aware modeling, semi-closed-loop workflows, stackable workforce training, and tiered governance for academic, public, controlled-access, and industry-protected data. We identify five coupled barriers -- fragmented data, weak algorithm--laboratory translation, uneven access to cyberinfrastructure and technical staff, workforce gaps at the materials--data interface, and insufficient incentives for sharing and reuse -- and propose a staged roadmap for addressing them. A high-purity germanium pilot illustrates how regional strengths can be converted into reusable datasets, benchmark models, trained personnel, and decision-improving workflows. The broader message is that regional leadership in data-centric materials science will depend less on geographic concentration than on trustworthy data practices, interoperable infrastructure, cross-trained people, and application-driven materials challenges.

Bacteria sense a diverse range of environmental analytes with high sensitivity and temporal resolution. Engineering and synthetic biology approaches enabled harnessing this capability through development of whole-cell biosensors that respond to specific molecules of interest. However, converting these responses into electrical signals in real time, across different environmental conditions, in miniaturized, field-deployable microelectronic devices, remains challenging. Here we present a bioelectronic platform that directly couples engineered bacteria to an integrated circuit (IC) chip through custom on-chip microelectrodes, enabling real-time, electronic readout of analyte sensing through bacterial flagellar motor dynamics. Using non-Faradaic electrochemical impedance measurements the device resolves both the direction and speed of motor rotation with a signal-to-noise ratio (SNR) of 15 dB. The IC is further integrated with a microfluidic system that enables controlled delivery and removal of analytes, nutrients and bacteria. When combined with whole-cell biosensors engineered to detect specific analytes, this work provides a miniature, portable platform for continuous monitoring in a range of liquid environments.

Toroidal modes enable high-Q resonances, but electric toroidal excitations remain unexplored compared to magnetic ones. This work establishes electric-magnetic toroidal duality in a hexagonal metasurface. Using finite element simulations, we analyze electric and magnetic toroidal modes in a hexagonal silicon nanorod supercell under mirror-symmetry breaking via height modulation. Eigenfrequencies, Q-factors, power flow, and polarization responses are computed. We identify electric TO and ATO modes with complementary near-field topologies to magnetic analogues. Direct frequency intersections (magnetic and electric TO/ATO) yield high-Q quasi-BICs. Polarization selectivity reverses between families: 0° excites magnetic TO/electric ATO; 90° excites magnetic ATO/electric TO. A loss hierarchy (magnetic TO > magnetic ATO > electric ATO > electric TO) and protective layers compatibility are demonstrated. Electric and magnetic toroidal responses are dual manifestations of the same symmetry, providing a unified design framework for high Q metasurfaces in sensing, nonlinear optics, and loss-tolerant devices.

Optical microcavities have emerged as a powerful platform for emulating topological phases challenging to realize in conventional materials, offering precise control over dispersion, light confinement, and interactions. Among them, liquid crystal microcavities (LCMCs) offer exceptional tunability at room temperature, enabling voltage-controlled polarisation splitting, photonic spin-orbit coupling, and photonic potentials generated by self-assembled textures, such as cholesteric torons and uniform lying helix (ULH). Here, we design a LCMC hosting a dimerized ULH texture and show that the corresponding photonic potential describes two coupled Su-Schrieffer-Heeger chains with orthogonal linear polarisations, acting as an effective pseudospin degree of freedom. The applied voltage tunes the interchain coupling, enabling polarisation-dependent interactions. These results establish LCMCs as a versatile platform for tunable synthetic topological Hamiltonians.

Understanding the relationship between morphology and performance in organic solar cells is essential for developing devices that are both high performing and resilient to aging. This work introduces a unique method capable of calculating the current-voltage (JV) curve of complex heterojunction morphologies containing up to five phases (donor amorphous, donor crystalline, acceptor amorphous, acceptor crystalline, mixed amorphous) with a very low computation time using morphology-aware descriptors of light absorption, exciton dissociation, non-geminate recombination and free charge carrier mobilities. The method is validated against Monte Carlo and 3D drift-diffusion simulations and applied to P3HT:PCBM and PM6:Y6 systems, shedding light on the physical compromises encountered to optimize device performance and lifetime. Finally, we show that the morphology-performance relationship is dependent on the materials system studied.

Experiments with thin 13 microns thick Al-foils have been carried out to explain its explosion dynamics, accompanying phase transitions and its relation to formation of plasma. Fast framing cameras were used to record the foil radiation during explosion process and have been correlated with electrical diagnostics to understand the underlying process such as hot spot formation and foil radiation. The electrical explosion was driven by pulsed power for which a capacitive power supply of rating 5kV,0.93mF was used. Our experiments have obtained experimental signatures to identify phases and transitions. Twin-peaks in voltage across the electrodes are repeatedly observed corresponding to melting and vaporization of aluminium foil followed by a Novel dip in voltage across the foil. To explain the signatures a phenomenological theory has been proposed and is validated in terms of integral of specific action. The experimentally obtained specific actions are in reasonable agreement with Tucker-Toth data. The Novel dip in voltage across the foil corresponding to Arc formation with Dark, Glow and Arc regions are identified. Our experiments also show that arc formation is essential for plasma formation.

Programmable integrated photonics (PIP) has emerged as a powerful on-chip platform for optical signal processing and computing, enabling the implementation of reconfigurable N$\times$N unitary matrix transformations through meshes of tunable interferometers, which realize 2$\times$2 unitary matrices. However, the energy consumption associated with phase-shifter actuation is becoming a major limitation to the scalability of PIP platforms. Here, we introduce a geometric framework for energy optimization in PIP circuits by exploiting the representation of 2$\times$2 unitary matrices as concatenations of basic Euler rotations on the Bloch sphere. We show that equivalent implementations of the same N$\times$N unitary matrix (N $\geq$ 2) can exhibit markedly different energy costs depending on the rotation trajectories on the Bloch sphere implemented by each interferometer. Leveraging this insight, we identify minimum-energy configurations by systematically selecting the shortest rotation trajectories. We experimentally and numerically validate the proposed approach in diverse silicon PIP architectures, including feedforward and multipurpose hexagonal meshes, neural network accelerators, and photonic quantum-gate implementations. These results establish a general route toward more energy-efficient large-scale PIP processors for classical and quantum signal processing and computing applications.

Förster energy transfer underpins modern photonics, yet establishing an analogous vibrational pathway in the mid-infrared (MIR) remains highly challenging, as sub-picosecond intramolecular vibrational redistribution (IVR) suppresses intermolecular coupling. Here we demonstrate vibrational donor--acceptor transfer in the MIR and subsequent upconversion to visible luminescence enabled by sub-2 nm plasmonic nanogaps. The extreme lateral field confinement in metal--molecule--metal ring cavities defined by self-assembled molecular spacers couples efficiently to in-plane molecular dipoles. Continuous-wave MIR excitation selectively populates $-\mathrm{C}\equiv\mathrm{N}$ vibrational donors, and plasmon-enhanced near-field coupling transfers this energy to nearby electronic acceptors, generating anti-Stokes visible emission under low power densities. Upconversion efficiencies exceeding $0.3\%$ are observed, limited by competition between the plasmon-mediated transfer rate and IVR. These results show that extreme plasmonic confinement can redirect molecular vibrational relaxation pathways, opening a route toward vibrational nanophotonics, intermolecular interactions for bioimaging, and room-temperature MIR detection based on molecular degrees of freedom.

Chaotic dynamics have emerged as a versatile resource for neuromorphic and probabilistic computing, enabling high-dimensional nonlinear processing and classical analogues of quantum randomness. Exploiting chaos for computation requires task-dependent control over complexity, as demonstrated in reservoir computing, random-number generation, and probabilistic inference. Existing approaches have focused on tuning element-level parameters, leaving the collective, many-body origin of chaos largely unexplored as a design freedom. Here, we demonstrate programmable chaotic dynamics for task-specific reservoir computing. Using a continuous-time neural-circuit model, we show that tuning network topology drives an ordered-to-chaotic transition, accompanied by transitions in correlation timescales, stability characteristics, and signal propagation. By jointly controlling element-level properties and network topology, we establish a unified chaos-latency phase diagram, revealing that small-world connectivity enables low-latency on-off switching of chaos via edge rewiring. Supported by distinct reservoir-computing benchmarks across various topological regimes, our results demonstrate that network topology serves as a reconfigurable parameter for task-specific computation and tunable randomness.

Tamm plasmon-polaritons (TPPs) - optical modes localized at the interface between a metal and a photonic crystal (PhC) - offer a versatile platform for confining light in planar optoelectronic devices. However, their implementation in angle-sensitive applications such as photodetectors and solar cells is hindered by strong angular dispersion of light. In this work, we propose a strategy to overcome this limitation by tailoring the dispersive properties of a PhC through the integration of hyperbolic metamaterials (HMMs). Using the transfer matrix method and effective medium theory, we demonstrate that the HMM exhibits type-I hyperbolic dispersion in the telecommunication wavelength range. This enables a photonic bandgap whose angular dependence compensates for the intrinsic blue shift of the TPP mode, effectively anchoring the resonance at 1550 nm over a broad range of incidence angles. Device performance is evaluated using the Fowler internal photoemission model, yielding a normal-incidence responsivity of 17.5 mA/W. Notably, for TM-polarized light, the responsivity decreases by only 10% at a 60 degree incidence angle - a substantial improvement over conventional all-dielectric PhC structures, which exhibit a degradation exceeding 86%. Our findings establish HMM-engineered TPPs as a promising platform for wide-angle high-performance photodetectors and open new directions for dispersion engineering in active plasmonic and optoelectronic devices.

Manipulating nanoscale light-matter interactions on ultrafast time scales is indispensable for future polaritonic devices. Hyperbolic phonon polaritons (HPhPs) in van der Waals materials enable deep subwavelength confinement of electromagnetic fields in the infrared region and long-distance propagation of polaritonic waves. However, achieving ultrafast imaging and optical control of HPhPs remains a major challenge. Here, we demonstrate the direct observation of transient modulation of HPhPs induced by local photocarrier generation in WS$_2$/hBN heterostructures using ultrafast infrared scanning near-field optical microscopy. We implement grating-based spectral filtering of broadband near-field scattering to simultaneously achieve nanoscale and femtosecond spatiotemporal resolution together with fine spectral selectivity. This ultrafast nano-imaging technique reveals that photocarriers in WS$_2$ modulate the polaritonic field amplitudes and wavelengths of HPhPs in hBN. Theoretical simulations corroborate that these changes arise from photoinduced changes in WS$_2$ dielectric properties. This approach offers a versatile platform for exploring ultrafast polaritonic dynamics at the nanoscale.

A general mechanism for anesthetic function is not fully understood. Similarly, the mechanism by which xenon, a chemically inert noble gas, can produce anesthetic effects remains ambiguous. However, a previous study reported a surprisingly strong nuclear-spin-dependent variation in anesthetic potency in mice, although no rigorous molecular mechanism was proposed. This perspective examines that observation and explores a potential connection to the chiral-induced spin selectivity (CISS) effect, a phenomenon that can account for spin-dependent processes in chiral systems. Here we propose a mechanism that links spin-dependent charge organization with chiral molecular systems through a kinetic model that reproduces the reported nuclear spin dependence of xenon anesthesia. The model is based on the nuclear spin-dependent permeability of isotopes through homochiral media, which modulates biological function through ligand-receptor binding in analogy with the Hill-Langmuir equation. Unlike mechanisms that require long-range quantum coherence, our framework remains robust under physiological, room-temperature conditions because it relies on the intrinsic stability of the CISS effect in dissipative biological environments. Our analysis motivates further experimental investigation of spin-dependent processes, not limited to anesthesia, in complex living systems where chirality is pervasive.

Population aging has made the daily mobility of older adults an increasingly important issue for urban planning and transport research. While previous studies have examined elderly mobility in relation to accessibility, active aging, and transport inclusion, less attention has been paid to whether older adults living in different residential contexts experience equal spatial activity opportunities. This study addresses that gap by comparing elderly residents in three wards of Nagoya, namely Naka, Showa, and Moriyama, which represent different rent levels and urban opportunity contexts. Using stay events derived from GPS-based mobility data, we construct a 500 m x 500 m grid-based analytical framework and examine spatial activity opportunity fairness through four dimensions: activity space, opportunity context, opportunity exposure, and semantic structure. The results show clear inter-group differences. Naka residents display the strongest concentration in the urban core, Showa residents occupy an intermediate position, and Moriyama residents exhibit a more dispersed and corridor-oriented pattern. Citywide semantic opportunities are unevenly distributed and concentrated around the urban core. Event-level exposure also shows a clear gradient, with Naka residents encountering the highest opportunity density, followed by Showa and Moriyama. Category-specific analysis further reveals that Naka residents are more strongly embedded in Retail/Service and Food/Drink opportunity structures, whereas Showa and Moriyama show relatively stronger Transit-related components. These findings suggest that spatial activity opportunity inequality among elderly residents is not one-dimensional, but multi-dimensional and category-specific. The paper contributes an event-based perspective for examining experienced urban opportunity inequality under differentiated residential contexts.

The integrated radar and jamming (IRAJ) system provides a promising solution that meets the demands for miniaturization, integration, and multifunctionality in complex warfare environments. However, traditional electronic-domain IRAJ systems face limitations in operating frequency and bandwidth. In this paper, we propose and experimentally demonstrate a microwave photonic IRAJ system based on pseudo-random binary phase modulation and segmented frequency shifting. By modulating pseudo-random binary coding sequence and frequency-shifting signals onto linearly frequency-modulated (LFM) pulses, an IRAJ waveform is generated to achieve noise-like jamming against the adversary radar. To overcome the random π-phase jumps introduced by pseudo-random binary modulation in the de-chirped signal, a time-domain squaring operation is implemented during de-chirped reception, restoring the radar detection ability of our system and enabling accurate target sensing without prior knowledge of the coding sequence. Experimental results demonstrate that the system can generate IRAJ waveforms with a bandwidth of up to 4 GHz, covering both 10-28 GHz. The proposed system achieves effective jamming against adversary radars employing either de-chirped reception or pulse compression, with the generated jamming results exhibiting an irregular and random distribution of false targets. Meanwhile, the system maintains radar performance with a ranging error of around 5 cm and a radial velocity measurement error below 4 cm/s.

We demonstrate a high-stability laser offset-frequency locking technique based on a balanced filter discriminator. The beat note between two 852 nm external-cavity diode lasers is down-converted in two parallel arms using local-oscillator frequencies placed symmetrically around the desired offset frequency. After low-pass filtering and RMS detection, differential subtraction of the two detector outputs produces a dispersive frequency-error signal with a zero crossing primarily defined by the reference local-oscillator frequencies. This balanced configuration reduces sensitivity to common beat-power fluctuations and can improve the effective error-signal signal-to-noise ratio. The system was implemented for an 8.653 GHz offset corresponding to the cesium repumping frequency difference used in our laser-cooling setup. Measurements with different low-pass filters reveal a trade-off between discrimination sensitivity and feedback bandwidth. With an SLP-1.9+ filter, the locked beat frequency reached a fractional instability of $4\times10^{-15}$ at 10 s when referred to the 852 nm optical carrier. The residual dependence on photodetector optical power was also characterized, showing that amplitude-to-frequency conversion remains small in the optimized differential configuration. This approach provides a practical frequency-only offset-locking method for atomic-physics experiments requiring stable and tunable microwave-scale laser frequency offsets.

Amorphization of silicon is crucial to applications in photonics, microelectronics and solar cell technologies. Ultrafast lasers have been used to generate amorphous silicon from crystalline silicon using rapid nonthermal melting and solidification in room temperature. As material temperature can affect cooling rates significantly, adding temperature control in ultrafast laser modification of silicon may allow a new degree of freedom in ultrafast laser modification. In this work, we investigate the role of cryogenic temperature in governing ultrafast damage pathways via single-shot femtosecond laser irradiation of silicon from room temperature down to 24K at 1030nm. Across this temperature range, we observe a pronounced enhancement of amorphization at lower temperatures, revealed through optical microscopy, Raman spectroscopy, and Kelvin probe force microscopy (KPFM). Raman analysis identifies this ring as an amorphous surface layer, while complementary AFM and SEM imaging show temperature-dependent changes in surface morphology, including localized melt redistribution and refrozen material. To elucidate the physical origins of this behavior, we implement a carrier dependent two-temperature model (nTTM). The simulations reproduce the experimentally observed trends and indicate that reduced phonon population, modified absorption pathways, and altered lattice relaxation dynamics at cryogenic temperatures collectively promote amorphous freezing over recrystallization. This study represents the first detailed examination of silicon under ultrafast irradiation below the liquid-nitrogen regime and reveals temperature-governed mechanisms relevant for advanced silicon microstructuring.

A multiresolution technique on tessellation graphs for particle dynamics is proposed. This allows to split spatial field data given on millions of discrete particle positions into scale-dependent contributions. The Delaunay tessellation is used to define the graph, and Voronoi cell volumes are used to satisfy volume conservation. Our approach enables computation of the scale-dependent statistics of particle dynamics by leveraging a wavelet transformation of Lagrangian point particle data and is useful for characterizing particle clustering in turbulent flows. The technique is systematically verified by using synthetic data of randomly distributed particles in a two-dimensional plane. Then the applicability of the technique is demonstrated by extracting the scale-dependent particle velocity divergence of inertial particles in homogeneous isotropic turbulence from direct numerical simulation data. The result is verified by comparing the energy spectrum of the divergence with that obtained by a Fourier-based approach. Finally, the wavelet-based filtering to the particle velocity divergence is demonstrated to extract the effect of caustics in inertial particle clustering.

Whole-eye optical coherence tomography (WEOCT) has emerged as a transformative imaging modality capable of simultaneously capturing the anterior and posterior segments of the human eye. WEOCT enables comprehensive ocular biometry, which is critical for a wide range of clinical and research applications-from intraocular lens power calculation, myopia progression monitoring, and refractive surgery planning to the precise measurement of the visual and optical axes and the generation of personalized eye models for eye tracking in virtual, augmented and mixed reality(VR/AR/MR). However, existing WEOCT systems often face trade-offs between signal-to-noise ratio, imaging speed, and the ability to capture dynamic processes without motion artifacts. To address these limitations, we present a novel spectrally-multiplexed WEOCT system that utilizes two synchronized 200 kHz swept sources at 1310 nm and 1060 nm. Coupled with an automated end-to-end processing pipeline involving deep learning-based surface segmentation, 3D distortion correction, surface fitting and ray-tracing refraction correction, our system enables anatomically accurate 3D reconstruction of the segmented ocular layers. Through a 300+ participant user study and comprehensive phantom studies, we demonstrate that our system can provide simultaneous accurate measurements of cornea topography and 3D pupil center. While labeled retinal OCT data is abundantly available in open-source repositories, labeled B-scan or volumetric anterior segment data remains significantly limited. Consequently, research groups working in related domains must often acquire their own data using custom imaging systems. To help bridge this gap, we are releasing as open-source a comprehensive dataset comprising 6,621 processed volumes from 276 unique participants with corresponding segmentation and calibrated 3D anterior point clouds.

Periodic driving provides a platform to dynamically tailor quantum states of matter, yet its impact on symmetry-protected topological phases remains incompletely understood. Here, we demonstrate that periodic driving enables the realization of an odd-parity altermagnetic (AM) higher-order topological insulator (HOTI) phase in the Cr$_2$CH$_2$ monolayer. In equilibrium, Cr$_2$CH$_2$ is a 2D antiferromagnetic (AFM) HOTI protected by $\mathcal C_3$ rotational symmetry, characterized by a symmetry indicator $χ^{(3)}$ = $\{-2,1\}$ and robust corner states. Under circularly polarized light (CPL), the system develops a f-wave altermagnetic state governed by the symmetry $[C_{2}||\overline{3}_{001}]$ with odd-parity spin splitting. Despite substantial Floquet-induced band renormalization, the $\mathcal C_3$-protected corner states remain intact over a broad range of driving strengths, highlighting the altermagnetic higher-order topology under Floquet driving. As the light intensity increases, the system gradually evolves into an altermagnetic semimetallic state. These results establish a direct connection between magnetism and topology in a periodically driven AFM system, offering a route toward the control of coupled spin and topological transport.

Supercooled water is expected to exhibit a liquid--liquid phase transition between low- and high-density liquid states, possibly terminating in a liquid--liquid critical point in the experimentally difficult no man's land. Because the hydrogen atoms are light, nuclear quantum effects (NQE) may alter the structural signatures used to identify this transition. Here, we compare classical molecular dynamics and path-integral molecular dynamics simulations of a flexible q-TIP4P/F-like water model in the deeply supercooled regime. The classical simulations show a pronounced density change at 180 K between 180 and 220 MPa, whereas the path-integral simulations exhibit a smoother pressure dependence. Radial distribution functions and bond-order parameters show that NQE broaden pair correlations, reduce the tetrahedral order of the first hydration shell, and slightly increase the Steinhardt $Q_6$ parameter. These results demonstrate that NQE modify both low- and high-density liquid structures and therefore need to be included when interpreting structural signatures of the liquid--liquid transition in supercooled water.

As AI-generated problem sets gain traction in introductory physics courses, their technical correctness is well established - but the social assumptions embedded in their framing have gone largely unexamined. This study analyzes 600 introductory physics problems generated by four AI systems - Grok~4, GPT-5.2, Claude Sonnet 4.6, and Gemini 3 Flash - across structured prompts involving occupations (CEO, Physicist, High School Teacher, Nurse, Construction Worker, and Migrant Worker). Problems were coded on five dimensions: hazard presence, hazard type, agency role, cognitive role, and object ownership. While the physics content is technically sound across all platforms, our analysis reveals systematic occupational stratification in narrative framing. Hazardous scenarios were concentrated in Migrant Worker and Construction Worker problems, with exposure-related hazards (electrocution, burns, radiation, heat or chemical exposure) especially concentrated in Migrant Worker problems. Passive-accident framing - the persona as the recipient of an injury - appeared in one in eight Migrant Worker problems and never appeared for the Physicist, Teacher, or CEO. Possessive ownership language was reserved almost exclusively for the CEO. These patterns suggest that AI-generated physics problems can introduce surface-level diversity while reproducing occupational hierarchies in who acts, who owns, and who is placed at risk. We discuss implications for physics teaching and offer simple screening strategies for instructors using AI-generated problems.

Four-dimensional (4D; 3D + time) microscopic imaging has emerged as a powerful technique for investigating dynamic phenomena in complex systems, enabling direct visualization of structural evolution in space and time. However, when pushing the limits of spatiotemporal resolution, most time-resolved imaging techniques yield inherently sparse 4D datasets. While deep learning-based reconstruction methods have shown promise in reconstructing 4D from sparse spatiotemporal measurements, a practical approach for evaluating their performance in the absence of a 4D reference has, to the best of our knowledge, been lacking. Here, we present a bootstrapped cross-validation framework that estimates reconstruction performance by quantifying correlations between reconstructions generated from independently sampled subsets of the acquired data, as inspired by the 3D validation strategy in cryo-electron microscopy, where reconstructions from split datasets are compared to assess resolutions. This enables both qualitative and quantitative assessment in the absence of ground truth. We investigate two representative scenarios with sparse and ultra-sparse X-ray datasets and validate this approach using 4D-ONIX, a 4D deep-learning reconstruction method, on simulated water droplet collision experiments. The proposed approach provides a reference-free framework for performance estimation and support for better-informed experimental strategies across a wide range of ultrafast imaging applications.

Physical computing systems provide a promising route toward hardware-native machine learning, but their computational capabilities remain difficult to characterize in a principled, task-independent, and data-efficient way. We extend the Information Processing Capacity (IPC) framework to stationary physical computing systems and establish several fundamental results: individual capacities are bounded between zero and one, their sum over a complete basis is bounded by the number of readouts, and noise strictly reduces this bound. We address the finite-sample estimation of IPC and derive the asymptotic form of the systematic positive bias affecting naive estimators. Building on these results, we introduce data-efficient estimation methods based on Richardson extrapolation and Sobol quasi-random sampling. We validate the framework experimentally using a photonic computing system based on picosecond laser pulses propagating through a nonlinear optical fibre. By varying the laser power and fibre length, we observe systematic shifts of the IPC distribution toward higher-order nonlinear capacities induced by the Kerr effect. Finally, we demonstrate that the total IPC strongly correlates with performance on benchmark machine-learning tasks and provides a reliable estimate of the effective dimensionality of the system. These results establish IPC as a practical bridge between the intrinsic dynamics of physical computing systems and their machine-learning performance.

We report a low-cost method for generating cylindrical vector beams using binary holograms printed on acetate sheets and a modified Michelson interferometer incorporating a cylindrical-lens mode converter. By simply exchanging the hologram the device produces a variety of CVBs with tunable spatial-polarisation nonseparability. The transverse polarisation distributions reconstructed via Stokes polarimetry show spatial-polarisation features consistent with numerical simulations. The degree of nonseparability is further quantified using the vector quality factor (concurrence), demonstrating values in good agreement with theoretical expectations across the generated states. The use of wave-plate retarders enables continuous tuning from scalar to fully vector beams. The simplicity, robustness, and low cost of the proposed system make it an attractive alternative to programmable modulators for compact optical platforms and teaching laboratories.

The NetMob Data Challenge releases a comprehensive public transportation dataset from Niterói, addressing the lack of high-quality mobility and passenger demand data. Based on operational records from March 2026, the dataset combines four main sources: GPS telemetry from buses, approximately 7.2 million ticketing transactions, auxiliary transit data (routes, stops, and weather), and urban infrastructure and socio-demographic information. Together, these sources provide a detailed view of both transit supply and passenger demand. The data were preprocessed, cleaned, and anonymized to preserve privacy and improve reliability, including the removal of operational inconsistencies and anonymization of passenger identifiers. Access is restricted to challenge participants who accept the Terms and Conditions and sign an NDA. The paper describes the data collection and preprocessing pipeline, dataset organization, and mobility patterns observed in the system. The dataset supports research on topics such as public transportation efficiency, demand forecasting, accessibility analysis, service reliability, and the influence of external factors like weather on urban mobility.

Integrated photonics has enabled a wide class of chip-scale light sources and quantum technologies. Within this field, microresonator-based degenerate optical parametric oscillators (DOPOs) have gained prominence. Above a critical power threshold, these systems undergo spontaneous symmetry breaking to settle into one of two stable, π-phase-shifted states -- a mechanism successfully used for quantum random number generation and photonic Ising machines. Here, we show that DOPOs based on the Kerr nonlinearity host a significantly broader range of nonlinear dynamics than previously explored. Using a silicon nitride microring resonator, we experimentally identify Hopf bifurcations that trigger a transition from stationary operation to self-sustained oscillations at MHz frequencies. By adjusting pump detunings and powers, we achieve turnkey control over these oscillatory regimes, navigating the system between stable binary states and periodic limit cycles. Furthermore, we report the experimental observation of period-doubling bifurcations, which numerical simulations reveal as the precursor to a cascading instability culminating in chaos at elevated pump powers. Our results establish a framework for controlling nonlinear instabilities in chip-scale parametric oscillators, with applications in programmable photonic hardware and dynamical optical computing.

Reconnections and rotations of lines are dual descriptions of the same saddle-shaped spacetime surface. We show that a reconnection between two line occurring over time is a single line that rotates over space progression. Both rotating lines and reconnections possess the same saddle shape sheet geometry in four-dimensional space-time, with different orientations. Cyclic precessing lines occurring over time are arrays of reconnections occurring spatially. We show that a magnetic reconnection occurring over time can be seen as a single continuous line vector potential rotating spatially, where the full evolution traces a saddle shape surface. Finally, we show that a single tilted spatiotemporal optical vortex precesses with spatial progression, and as a result can be seen as two vortices reconnecting. Given the unique spatiotemporal evolution, we also analyzed the relativistic angular momentum of these electromagnetic fields.

A quantitative understanding of the processes that trigger light-induced demagnetization on ultrashort timescales is crucial for achieving an ultrafast, radiation-controlled magnetic response in materials. This milestone is essential for developing next-generation magnetic storage devices and ultrafast magnetic switches. In this theoretical study, we investigated demagnetization triggered in a single magnetic domain by light pulses ranging from a few to a few tens of femtoseconds in duration, with photon energies spanning the optical and X-ray regimes, under strongly non-equilibrium conditions. We predicted a loss of magnetization in the sub-100-fs range in all cases, primarily due to the excitation of the electronic system and the subsequent redistribution of electrons within the magneto-sensitive band. The considered timescales were too short for phonon-mediated processes or inter-site Heisenberg exchange processes to contribute significantly. These findings pave the way for highly accurate, radiation-driven magnetization control in magnetic materials at sub-100-femtosecond timescales with potential practical applications.

Plasmonic optical tweezers based on Double Nanohole (DNH) structures are an emerging tool for label-free single-molecule manipulation. However, their current performance is hindered by low signal-to-noise ratios for small proteins, fabrication variability, and thermal damage risks from high laser power requirements. To address these limitations, we present a comprehensive optimization of DNH parameters using systematic simulations and morphological characterization. We evaluate critical structural features, including gap size, gap length, gap curvature, wedged tapers, adhesion layers, and the inclusion of interior pillars. By tailoring these variables, we aim to maximize trapping stiffness, local electric field confinement, and transmission variation upon trapping (ΔTT), while minimizing the required optical power. The resulting optimized DNH design substantially outperforms reference structures, delivering an almost 3-fold increase in electric field enhancement and a 5-fold improvement in the trapping transmission signal. These refinements provide a robust framework for developing highly efficient, reproducible optical tweezers for advanced single-molecule biophysics.

Human-generated randomness is constrained by cognitive, motor, and strategic biases. This study examines how these constraints appear in individual behavior and how they may be modified through interaction with another human. We analyzed repeated rock-paper-scissors data from 9 participants, yielding 108 human-human matches and 216 individual player sequences. Using Lempel-Ziv complexity (LZC), we compared human-human sequences with the RNG-opponent condition. In the RNG-opponent condition, the maximum human LZC value was 84, which we used as an empirical reference. In the human-human condition, most sequences remained below this value, but a small number exceeded it, producing a small high-complexity tail that was not present in the RNG-opponent condition. We introduced a sensitivity measure that captures whether a player responds to the opponent's recent frequency bias by choosing the move that beats the opponent's most frequent recent move. Partial regression showed that focal-player sensitivity positively predicted future entropy in the opponent's move sequence after controlling for the opponent's current entropy. Circular-shift surrogate analyses indicated that this relation was most clearly interaction-specific when the opponent was in a low-entropy state, where the recent move distribution contained a clear frequency bias. These results suggest that human randomness is not only an isolated individual capacity, but can be shaped by interaction in a state-dependent manner. The findings identify a local mechanism by which interaction may destabilize biased behavior and increase entropy, providing a concrete basis for future causal experiments and generative models of high-complexity human behavior.

Triangular-lattice systems attract a lot of attention due to various frustration-induced and strongly correlated effects. Here, we focus on the charge-ordering phenomenon by means of investigation of the extended Hubbard model with dynamical mean-field theory (DMFT). By considering the intersite nearest-neighbor interaction we have found a very rich phase diagram that contains large number of features, phases, and phase transitions. Among them are pinball-liquid (PL) phases where we distinguish charge-transfer-driven and Mott-localization-driven PLs; phase transitions that change their order as model parameters evolve (from discontinuous to continuous); very strong particle-hole asymmetry. Various features of the phase diagram are found to be better understood by means of the simple mean-field approximation (MFA). Moreover, besides helping with interpretation of the phase diagram, the MFA results together with results for the atomic-limit model are found to be able to set rather good expectations on how the DMFT phase diagram should look like. Nevertheless, a few features were not expected and are found within the DMFT, such as a small-region intermediate metallic phase on an electron-doped side of the phase diagram.

Fringe projection profilometry (FPP) is a widely used technique for measuring object surface form and three-dimensional (3D) geometry, capable of delivering high-precision, high-resolution measurements when paired with suitable cameras and projectors. However, in practical deployments, identifying parameter configurations that maximise precision while satisfying real-world constraints remains challenging. To address this, we present an automated digital twin framework implemented in Blender, an open-source 3D software package that provides a ray-traced rendering environment that enables accurate simulation of physical systems. We replicated the physical setup in our digital twin by matching characterisation quality, gamma response, and characterisation images. Accurate system characterisation using Zhang's method [1], to obtain intrinsic and extrinsic parameters, is shown to be critical for achieving high precision. Using this digital twin, we then demonstrate systematic exploration and optimisation of key parameters, including phase-shift count, camera-projector spacing, and fringe density. These parameters span both system geometry (e.g. camera-projector positioning) and algorithmic choices, such as 2D phase-shifting and unwrapping methods [2]. Three measurement artefacts, representative of real world metrology scenarios, were used to benchmark the system. The symmetrical mean Chamfer distance (SMCD), computed between ground-truth and reconstructed meshes, was used to evaluate reconstruction quality. After optimisation within the digital twin, transferring the optimal parameters to the physical system reduced the number of required images per measurement by 48% (from 36 to 21). A reduction of 74.0% mean SMCD was also achieved for fringe pattern stripe count alteration. A 36.9% mean SMCD was obtained for adjusting the camera and projector spacing purely in the digital-twin.

We present a systematic experimental comparison of single-pass second-harmonic generation (SHG) in bismuth triborate (BiBO) and lithium triborate (LBO) nonlinear crystals, driven by a 1.3 ps, 91 kHz laser at 1030 nm with up to 57 W of average input power. Both crystals yielded 32 W of second harmonic (SH) output at 515 nm, corresponding to a conversion efficiency of 56 %, which to the best of our knowledge represents the highest SH output power reported in the green spectral region using a BiBO crystal. Power dependence, long-term stability, beam quality, pulse duration, spectral properties, thermal effects, and angular acceptance bandwidth are characterized and directly compared for both crystals. These results provide quantitative performance benchmarks to guide the selection of nonlinear crystals for high-average-power, ultrashort-pulse frequency conversion near 1030 nm.

The characteristic impedance and the propagation coefficient are among the most important parameters for evaluating the acoustic performance of porous materials. This work investigates the influence of cylindrical modes in an impermeable tube and applies multiple microphones distributed along the tube circumference within the three-microphone framework to extend the valid frequency range of characteristic impedance measurement. During the extended broadband measurements, discontinuities or phase jumps are observed in the experimentally measured propagation coefficient of the porous material under test. A Bayesian inference is applied in a sequential manner to estimate the unwrapped propagation coefficient and characteristic impedance. The results demonstrate that the inferred parameters accurately capture the behavior of the transfer function, allowing accurate parameter estimation.

Printed circuit board (PCB) modelling is an important part of the PCB production process, in which the designer aims to optimize the desired output characteristics prior to physical PCB manufacturing. Due to the specific shape of PCBs, namely, thin and highly conductive components enclosed within a relatively simply shaped dielectric host, the PCB modelling problem is amenable to solution by the so-called 2.5D Method of Moments (MoM) applied to the integral equation solution of Maxwell's equations. For this purpose, an analytic expression for the Green's function of the host medium needs to be derived. Many studies exist in which expressions are derived for the transverse Green's function components in a waveguide, used for modelling planar metallization layers in shielded layered media. Works containing the full Green's function that allows modelling of both longitudinal and transverse currents are much fewer. In this study, we propose a tool to solve the shielded PCB modelling problem involving both transverse and longitudinal currents, with the Green's function in a layered waveguide derived using the S-matrix formalism. Our approach combines a straightforward, intuitive way of calculating the complete dyadic Green's function in a layered waveguide with the inherent numerical stability of the S-matrix method. The Green's function is expressed in terms of three sets of S-matrices associated with the PCB layers in which the electric current source and the electric field observation point are located. The MoM is implemented using surface rooftop, volume pulse, and linear basis functions, for which we provide the overlap integrals, to model planar metallization layers and wire-like vertical interconnects. The validity of the method is demonstrated on two numerical examples. The method can be extended to other bases to model objects of various shapes.

We present SPARC-atomSFE, a spectral finite-element package for accurate and efficient atomic structure calculations within the framework of Kohn-Sham density functional theory. The package supports both all-electron and norm conserving pseudopotential calculations across a comprehensive hierarchy of exchange-correlation approximations, spanning local, semilocal, and nonlocal functionals. The latter includes hybrid functionals and the many-body random phase approximation, for which we implement both the generalized Kohn-Sham approach and the optimized effective potential (OEP) method, with OEP necessary for eigenvalue-dependent functionals. Spatial discretization is based on an adaptive grid with element nodes distributed according to the Legendre--Gauss--Lobatto scheme, high-order $C^{0}$-continuous Lagrange polynomial basis functions, and Gauss--Legendre quadrature for numerical integration. We present systematic convergence studies and identify the computational parameters required to achieve target accuracies. We validate the accuracy of SPARC-atomSFE through representative calculations spanning the various exchange-correlations approximations, obtaining results that generally agree with values in the literature to within $1~μ\text{Ha}$ or better.

In contrast to dyadic interactions, higher-order interactions may contain one another, with subgroups naturally embedded within larger groups. These containment patterns arise empirically in ecology, sociology, computer science and the science of science, and have been studied under the names nestedness, simpliciality, encapsulation, and inclusion. In this chapter, we review each of these measures and unify them through a mathematical object known as the encapsulation directed acyclic graph, formulating each measure as a function of its properties. We demonstrate that nested structure is prevalent in social systems across several domains, show that different measures capture complementary aspects of this structure, and find that the absence of nestedness can itself be a powerful indicator of the mesoscale organization of a system.

Presently, there is a steady state approach in Computational fluid dynamics (CFD) to obtain a steady solution directly from the steady state governing equations. Whereas, for obtaining a time-periodic flow solution, the present unsteady governing equations-based CFD approach starts from an initial condition and requires a large computational time during the initial non-periodic transient phase before reaching the periodic state. For obtaining the periodic flow directly, without transient simulations that may not be of interest, our objective is to propose a Physics Informed Neural Network (PINN)-based periodic CFD approach. The motivation is a substantial reduction in computational time by a meshless PINN-based periodic CFD solver as compared to the present mesh-based transient-to-periodic solver. Proof-of-concept, for the periodic CFD approach, is demonstrated here for 2D periodic heat diffusion and fluid flow problems. The proposed PINN-based periodic solver primarily focuses on the time-periodic state, optimizing the neural network model's trainable parameters to precisely fit a smaller time window (one time-period) rather than the temporal domain starting from the initial condition. After presenting a verification study, effect of the PINN-related various hyperparameters such as the number of collocation points, neural network architecture, and point spacing for numerical differentiation, on computational time and accuracy are presented. Our results demonstrate that the PINN-based periodic solver takes substantially less computational time to achieve almost same accuracy as that obtained by the traditional transient-to-periodic solver.

Plasma wakefield excitation driven by two color Laguerre Gaussian laser pulses carrying orbital angular momentum is investigated analytically and through quasi-cylindrical particle in cell simulations. Using a perturbative framework together with the quasistatic approximation, the influence of the transverse laser mode structure on the longitudinal and transverse wakefields in an underdense plasma is examined in the weakly relativistic regime. The results show that drivers with finite azimuthal index produce reduced and less regular on-axis longitudinal wakefields compared to conventional Gaussian drivers. However, radial longitudinal field distributions reveal that this reduction originates from a redistribution of the wakefield energy toward finite radii rather than a simple loss of wake excitation. Orbital angular momentum carrying modes generate hollow and ring shaped wake structures accompanied by strongly modified transverse electric fields and broader plasma density perturbations. Mixed Gaussian Laguerre Gaussian configurations exhibit intermediate behavior, combining weak on-axis acceleration with pronounced off axis wake excitation. The study demonstrates that structured two-color laser drivers fundamentally modify the topology of plasma wakefields and provide an additional mechanism for controlling transverse plasma dynamics, off-axis acceleration, and angular momentum mediated wakefield structures in plasma based accelerator schemes.

Dual-polarization heterodyne receivers operating at 325 GHz, 424 GHz, and 650 GHz at room temperature are presented. Polarimetric measurements are enabled by two orthogonal open-ended E-field probes, co-optimized and integrated with two subharmonic GaAs Schottky-barrier diode mixers. The down-converted signals (IF) are amplified using low-noise InP HEMT amplifiers integrated into the receiver module, along with IF matching networks, dc-bias boards, a shared local oscillator (LO) distribution network, and a single smooth-walled, conical, spline-horn antenna. Maximum cross-polarization isolation of 25 dB, 34 dB, and 25 dB was achieved at 315 GHz, 421 GHz, and 650 GHz, respectively. The measured double-sideband (DSB) receiver noise temperatures are 833 K, 835 K, and 1623 K at 315 GHz, 421 GHz, and 630 GHz, respectively. Stability measurements, with an integration Allan time of more than 10 s, were obtained for all receivers. Overall, the integrated dualpolarization receiver topology achieves excellent sensitivity in a highly compact package, offering an efficient and scalable solution for polarimetric applications in submillimeter-wave remote sensing

Self-healing -- the ability of a structured beam to reconstruct its transverse profile after partial obstruction -- has been demonstrated for diffraction-free beams, where the recovery distance varies continuously with obstruction size. Here, we investigate self-healing in the Montgomery pattern, a self-imaging of tightly localized optical fields. Using Babinet's principle, we show theoretically that the recovery distance is quantized in integer multiples of the self-imaging period -- a qualitative distinction from all previously studied self-healing beams. We confirm these predictions experimentally using a programmable holographic setup with circular disk obstructions of size up to $20\times$ of the spot size of the Montgomery pattern at the self-imaging plane, establishing the robustness of the Montgomery pattern against scatterers and obstructions in the beam path.

We test a dynamic ODE model of hierarchical asymmetry on a panel of 260 countries over 1960-2023, drawing on World Bank, Penn World Table, V-Dem and World Inequality Database sources. In cross-section the model holds partially: trade openness and bottom-of-distribution health suppress within-country asymmetry. The annual time-evolution equation fails, with out-of-sample R^2 at or below zero across five functional forms. The same state vector, augmented with market, debt and trajectory features, is much more successful as a discriminator: a four-layer leave-one-collapse-out classifier separates 29 historical collapses from 60 stable controls at a nested cross-validated AUC of 0.91. The signal splits into a chronic risk profile visible a decade before the event and an acute inflection three to five years before. Three independent tests reject the endogenous-drift reading of collapse. What remains is a candidacy-and-trigger picture in which structural variables identify the high-risk countries while collapse timing is set by shocks outside the modelled system. A separate strand documents a lagged co-movement between global fertility and global asymmetry on a single n=63 aggregate series; taken alone this would suggest a selection-pool channel. The same pattern is then tested within countries, within demographic strata, inside a two-way fixed-effects panel and through a migration-mediated cross-country interaction model, and the directional reading fails in each. The aggregate co-movement is a compositional effect rather than a causal channel. A global event-study on 7,316 peer-event observations confirms regional spillover in asymmetry and a novel post-collapse degradation of bottom-of-distribution health in regional neighbours. A pre-registered forward-look produces a top-20 / bottom-20 ranking to be evaluated over 2026-2036.

This article examines the case of two papers published in Naturwissenschaften by the physicist Max Planck that were retrospectively marked as retracted on Springer digital platform. Rather than originating in scientific fraud, these withdrawals appear to result from contemporary digitization and copyright-management procedures applied anachronistically to historical publications. Through an investigation of the circulation history of Planck 1940 and 1942 philosophical essays, the article shows that republication across multiple formats was a common and legitimate practice within the scientific publishing culture of the early 20th century. Such practices only became problematic with the later transformation of the scientific article into a countable and proprietary unit within systems of bibliometric evaluation and commercial academic publishing. This article argues that contemporary notions such as duplicate publication and self-plagiarism are historically situated categories that cannot be applied retrospectively without distorting the historical record. More broadly, the Planck case reveals how digital scholarly infrastructures controlled by large commercial publishers can limit the accessibility of the scientific past. Ironically, the original papers remain accessible today through the nonprofit digital platform Internet Archive rather than through the publisher that originally issued the journal.

Oscillator Ising machines (OIMs) are often viewed as physical systems that perform gradient descent on an energy landscape encoding Ising solutions. Here, we show that this interpretation is not generic and breaks down in a broad class of oscillator implementations. We establish that gradient-flow dynamics require a harmonic-by-harmonic quadrature relation between the oscillator waveform and its phase response. Deviations from this condition, which we term harmonic misalignment, introduce even components in the pairwise interaction function, leading to non-conservative phase dynamics and precluding a gradient-flow description. We introduce a normalized metric for this non-gradient contribution and evaluate it across representative oscillator models relevant to OIMs. This metric reveals substantial non-gradient contributions in ring oscillators and across other hardware-realistic oscillator models. These findings identify harmonic misalignment as a fundamental mechanism for the breakdown of energy-based dynamics in OIMs and motivate nonequilibrium analysis and algorithms that explicitly account for and potentially exploit non-gradient behavior.

With the rising number of interactions between autonomous or sensor-assisted vehicles -- especially in poor weather conditions -- come the need and opportunity for a new class of bicycle safety reflectors designed to enhance cyclist visibility to radars. To this effect, the first retrodirective planar metalens-based tag operating in the millimeter-wave automotive frequency range is proposed. The compact, lightweight ($0.61~\mathrm{g}$) design consists of two layers: a metalens layer and a patch antenna pixel layer. The metalens focuses incoming plane waves from different incidence angles onto corresponding patch antenna pixels on the second layer, which re-radiate the signal back through the metalens, enabling retrodirective operation. The proposed tag was thoroughly evaluated, demonstrating reliable detection beyond 70 m and a peak monostatic radar cross section (RCS) of $3.54~\mathrm{dBsm}$ with stable retrodirectivity over $\pm 40^\circ$, providing an average gain improvement of $7.58~\mathrm{dB}$ and an RCS enhancement of $15.16~\mathrm{dB}$ relative to a lens-less reference. A realistic deployment scenario on a metallic bicycle demonstrated up to a 110x improvement in its detectability at broadside. These results highlight the potential of the proposed passive tag to operate as a low-cost, lightweight, and easily integrable bicycle safety reflector for next-generation autonomous vehicle radar systems.

Dynamic line rating (DLR) is a methodology that requires timely monitoring data to determine the real-time ampacity of power lines. However, DLR monitoring devices (MD) are vulnerable to connectivity disruptions, leading to missing or delayed data. Although unmanned aerial vehicles (UAV) can enable resilient data collection from MD, their limited onboard energy challenges timely monitoring over extended transmission corridors with flight hazards. This paper proposes a cooperative UAV-based data collection framework with integrated sensing and communication (ISAC) to support timely DLR updates. In this framework, ISAC is employed to maintain the sensing and communication quality required for safe and cooperative UAV data collection. Accordingly, a joint energy minimization problem is formulated over UAV trajectories and collection scheduling under ISAC constraints. To solve it, a hybrid algorithm combining deep reinforcement learning (DRL) and semidefinite relaxation (SDR) is proposed, where DRL optimizes the trajectory and collection scheduling, while SDR is used to handle the non-convex ISAC constraints. Simulation results show that the proposed scheme reduces energy consumption by up to 34.6% compared with offline benchmarks and by about 2.2% compared with the separated sensing-and-communication baseline, while satisfying the minute-level timescale requirement of DLR.

Communication performance and channel estimation accuracy in MIMO systems are known to be limited by hardware impairments. Specifically, the presence of phase impairments, such as phase noise, makes real-time coherent transmission a challenging task. While phase impairment compensation is typically performed at the receiver, practical methods for enabling coherent transmission at the transmitter side remain underexplored. Established methods for OTA calibration of MIMO systems face several limitations such as assumptions of phase stationarity and accurate channel knowledge. In this work, a real-time local phase calibration method is experimentally compared with OTA calibration on a fully digital array of USRP X310 software-defined radios. Using RMS cycle-to-cycle jitter as a metric, it is shown that for low and high synchronization signal bandwidths, both approaches effectively eliminate phase drift and whiten the phase noise. Local calibration achieves higher phase stability and is channel-independent, whereas OTA calibration requires no additional hardware but is sensitive to multipath effects and channel-induced impairments. Practical deployment trade-offs are discussed based on the measurement results.

Digital twins (DTs) are promising for wireless deployment, optimization, and data generation, but building a propagation-faithful twin from sparse real measurements remains difficult. This paper proposes a wireless environment digital twin (WEDT) construction paradigm that evolves a reconstructed geometric DT into a propagation-consistent wireless environment representation through calibration of a scene-level electromagnetic (EM) property field. Instead of directly fitting link-specific channel responses, the proposed paradigm first constructs a geometry-prior Bayesian channel map (BCM) to convert sparse position-labeled channel state information (CSI) into dense probabilistic supervision with uncertainty estimates. It then embeds the learnable EM property field into differentiable ray tracing (RT) based channel computation, thereby enabling calibration through an explicit propagation chain. Experiments in both public and real-world scenes show that WEDT achieves accurate channel prediction, generalizes to unseen transceiver topologies, and remains effective across different sampling conditions. WEDT also offers utility for material-related environment sensing, more reliable physical-layer planning, and higher-quality synthetic data generation for wireless AI. These results demonstrate the value of the proposed paradigm for propagation-consistent WEDT construction and related wireless applications.

We address joint active and passive beamforming for uplink RIS-assisted multi-user multi-stream MIMO systems with joint detection. The coupled design of the receive combiner, block-diagonal user precoders, and RIS phase vector is formulated through a third-order composite channel tensor. Exploiting this multilinear structure, we propose a multi-stream tensor alternating optimization method that updates the combiner, user precoders, and RIS coefficients via low-dimensional tensor projections. Simulations show that the proposed method approaches a multi-start alternating-optimization benchmark while reducing computational complexity and improving large-RIS scaling.

This paper reconstructs the half-century evolution of the scientific school founded by Yuriy P. Kunchenko (1939--2006) as the development of a semiparametric methodology for non-Gaussian estimation. Starting with Kunchenko's 1972/1973 dissertation applying Volterra series to estimate parameters of random processes, the trajectory is followed through 2006--2026. Kunchenko stochastic polynomials are presented as a coherent family of moment-cumulant procedures: the polynomial maximization method (PMM) for parameter estimation, polynomial criteria for hypothesis testing, and decomposition in spaces with a generating element. The paper details the school's structure: a verified genealogy of 15 defended dissertations, collaborations in Poland, Slovakia, and Germany, and the R package EstemPMM. A recent 2026 paper on Volterra-based signal processing is analyzed, showing how Kunchenko's nonlinear formulation reappears in applied radio engineering. We build a formal bridge between finite Volterra models and generalized Kunchenko polynomials, while separating the MMSE/L2 criterion from PMM: the former is a covariance projection for kernel adaptation, whereas PMM is a parameter-dependent moment procedure. PMM efficiency claims are stated conditionally: gains require that moments exist, the centered correlant matrix is nondegenerate, and the variance reduction coefficient is below one. The concluding research program operationalizes the historical reconstruction into testable statistical and signal-processing tasks.

In this paper, we investigate a multi-cell six-dimensional movable antenna (6DMA) network for enhancing downlink communication performance under inter-cell interference (ICI). Each base station (BS) is equipped with multiple 6DMA surfaces, and the 6DMA rotations affect both the desired-signal enhancement for in-cell users and the interference leakage toward neighboring cells, which makes the antenna-rotation design and transmit precoding intrinsically coupled across BSs. To address this issue, we formulate an average weighted sum-rate maximization problem for the multi-cell system by jointly optimizing the short-term downlink precoders and long-term 6DMA rotations under practical antenna geometric constraints. To tackle the resulting nonconvex problem, we propose a distributed two-timescale design based on inter-cell interference power constraint (IPC) coordination among neighboring BSs, under which each BS performs local short-term precoder optimization based on instantaneous channel state information (CSI) and long-term 6DMA rotation update according to statistical CSI with limited inter-BS information exchange. In particular, an edge-wise IPC coordination mechanism based on two-stage one-dimensional grid search and random maximal matching is developed to enable scalable distributed implementation. A centralized offline benchmark is also provided for performance comparison. Numerical results show that the proposed distributed design achieves performance close to the centralized benchmark under different interference conditions, while maintaining favorable scalability as the network size increases.

Extremely large aperture arrays (ELAAs) and millimeter-wave (mmWave) technologies are essential for achieving high data rates in future wireless communication systems. To perform precise beamforming, these systems require accurate channel estimation, in which the near-field wavefront curvature effect must be taken into account. Existing channel estimation methods rely on the spherical wavefront channel (SWC) model, which is suitable for near-field propagation with point sources, scatterers, and reflection planes. However, when a near-field curved reflecting surface exists, the wavefront of the reflected wave becomes anisotropic rather than spherical, causing the SWC model to become inaccurate. To address this problem, in this paper, we formulate a parameterized model for the anisotropic wavefront channel (AWC). Using this model, we propose a channel estimation algorithm based on physical parameter recovery for the AWC. Simulation results reveal that the AWC no longer retains sparsity in the angle-distance domain. Furthermore, the results demonstrate how different physical characteristics of the propagation scenario affect the degree of wavefront anisotropy, and confirm the effectiveness of our proposed algorithm in AWC scenarios.

Since the beam squint and near-field effects both inherently exist in upper-6 GHz (U6G) extremely large-scale multiple-input multiple-output (XL-MIMO) systems, wideband near-field channel estimation faces severe challenges, such as higher computational complexity, and higher pilot overhead particularly at hybrid architectures with fewer radio frequency (RF) chains. To precisely reduce the complexity and number of pilots, the parametric symmetry of wideband near-field channels is explored, such that the channel parameters, including angle, distance, and range, can be decoupled based on the delay variations observed by different antennas. Based on this, a distributed parametric symmetry-based (DPS) algorithm, applicable to U6G XL-MIMO, is proposed. The delays observed by different subarrays are estimated and extrapolated across the local processing units (LPUs) firstly, and then, the channel parameters are decoupled and estimated at the central processing unit (CPU), by only linearly combining the delays from different LPUs. The path gains are calculated at different LPUs, respectively, to reconstruct the channel with low complexity. Since the proposed algorithm does not rely on scanning the polar-domain dictionary, only a single pilot is required even with hybrid architectures. Furthermore, the computational complexity, multiple-path resolution, Cramer-Rao lower bound (CRLB) and lower bound (LB) of the estimates in hybrid architectures and the DPS algorithm, respectively, are analyzed, to evaluate the realizable potential of the proposed algorithm. The simulation results prove that the proposed algorithm has a higher estimation accuracy, while requiring less complexity and pilots.

This paper investigates the joint optimization of power allocation and antenna activation in sparse extremely large aperture array systems operating under power amplifier non-linearities. We first derive an analytical expression for the achievable spectral efficiency (SE) of point-to-point MIMO channels affected by non-linear distortions using the Bussgang decomposition. To address the combinatorial and non-convex nature of the energy-efficiency (EE) maximization problem, we employ an unsupervised deep neural network (DNN) that learns the non-linear mapping between the channel state information and the optimal EE operating point. The DNN jointly predicts distortion-aware power allocation, total transmit power scaling, and modular sub-array activation based on singular-value and geometric channel features. Numerical results demonstrate that the proposed DNN-based arrays achieve significant EE gains over the conventional sparse arrays.

In modern industrial systems, machinery frequently operates under dynamic environments with continuously varying loads and speeds. Consequently, deep learning-based fault diagnosis models often suffer from severe performance degradation under unseen operating conditions due to complex data distribution shifts. Since existing methods predominantly rely on static offline training, they lack the capability to dynamically adapt to these continuous variations. To address this issue, an integrated framework combining offline domain generalization (DG) and online test-time adaptation (OTTA) is proposed. Initially, a model with preliminary generalization capability is obtained offline by extracting domain-invariant features via adversarial learning. During the online phase, a dual-memory replay mechanism is developed. By selectively storing high-confidence online pseudo-labeled samples and replaying them with historical offline data, the model facilitates adaptation to changing data distributions and helps reduce forgetting of previously learned knowledge Experiments on a real-world motor dataset show that the proposed approach achieves competitive performance under the considered unseen operating conditions.

In this letter, we propose a new wireless sensing system equipped with a rotatable antenna (RA) array to enhance the sensing performance of a uniform sparse array (USA). To tackle the severe spatial undersampling issues, we propose a novel tensor decomposition-based direction-of-arrival (DOA) estimation algorithm. Specifically, we introduce a synchronous multiple rotation pattern for active target probing such that the received signals across multiple rotations to capture the diverse spatial degree of freedoms. Subsequently, we mathematically formulate the received signals across successive rotations as a third-order tensor, and leverage the canonical polyadic decomposition to obtain the factor matrices incorporating the DOA of targets. By analyzing the extrema distribution laws of array steering vector correlation (SVC) and gain SVC of RAs, we propose to combine the array and gain factor matrices via the Kronecker product, which theoretically guarantees the unambiguous DOA estimation. Simulation results demonstrate that the proposed RA-enhanced tensor decomposition-based algorithm achieves high-precision and unambiguous sensing performance compared to conventional uniform dense arrays and omnidirectional antenna systems.

Objective: Conventional urodynamics (UDS) provide critical diagnostic information, but requires invasive dual catheterization and manual labeling of clinically important events. Wireless, catheter-free bladder function tests are becoming available for home use, but only provide vesical pressure (Pves). We developed a machine learning framework that was trained and externally validated on UDS data for automated urological event classification from single-channel (Pves) recordings. Methods: We analyzed 118 annotated UDS traces segmented into 0.8-second Pves intervals. Using the discrete wavelet transform, we extracted 55 statistical features per segment. Consecutive segments (233,338 segments; three classes) sharing the same class, abdominal (ABD), detrusor overactivity (DO), or voiding contraction (VOID), were grouped into events, and median feature aggregation was applied to derive event-level representations. Using an imbalanced dataset, we trained a two-stage multilayer perceptron (MLP): Stage 1 distinguished VOID vs non-VOID, and Stage 2 classified non-VOID into ABD and DO. The model was trained on two independent datasets and externally validated on a third independent dataset. Additional cross-dataset training-validation permutations were performed to assess generalizability. Performance was evaluated using accuracy, F1-macro, sensitivity, specificity, and area under the curve (AUC). Results: Stage 1 (VOID vs. non-VOID) achieved 84% accuracy (balanced accuracy 76%), F1-macro 0.74, and AUC 0.85, while Stage 2 (ABD vs. DO) reached 90% accuracy (balanced accuracy 80%), F1-macro 0.80, and AUC 0.87. Permutation feature importance indicated that most features contributed meaningfully. Conclusion: Our machine learning approach enables accurate automated detection of urological events from Pves, demonstrating feasibility for single-channel monitoring and future ambulatory applications.

Standard transformer attention computes pairwise similarity between queries and keys, treating all tokens as equally salient regardless of their intrinsic informational content. In turbulent fluid dynamics, coherent structures -- the energetically dominant, spatially organized patterns that persist amid background chaos -- carry a disproportionate fraction of total energy and govern all transport. We propose that tokens play an analogous role in transformer attention: informationally dense positions (morphological boundaries, syntactic heads, discourse markers) concentrate spectral energy and should attract proportionally more attention than background tokens (function words, repeated patterns, low-information filler). We propose Energy-Gated Attention (EGA): a simple modification that gates value aggregation by the spectral energy of key token embeddings, computed by a single learned linear projection that discovers the dominant spectral mode of the embedding field. On TinyShakespeare, EGA achieves +0.103 validation loss improvement with only 12,480 additional parameters (<0.26% overhead) and no measurable computational cost. The result is consistent on Penn Treebank (+0.101), demonstrating dataset independence. A systematic ablation across three wavelet families (fixed Morlet, Daubechies db2/db4, and a parametric Morlet) establishes that fixed structured bases are suboptimal -- the optimal energy direction is data-adaptive and non-sinusoidal -- while identifying learned wavelet packets as a promising open direction. The learned energy threshold converges to tau ~= 0.35 independently of initialization, corresponding to the fraction (~36%) of tokens carrying above-average spectral energy in English text, a stable linguistic property consistent with the fraction of content words in running English text.

Beamforming has proven to be valuable in enabling full-duplex massive MIMO base stations, but doing so effectively often requires knowledge of the self-interference channel matrix H. Estimating this high-dimensional channel is costly in practice, however, since it requires a prohibitive number of measurements, especially in fast-fading conditions. In this work, we overcome this dilemma by designing full-duplex beams using implicit channel knowledge gathered from a relatively small number of measurements across H. These measurements are collected by the base station using a sequence of beams tailored to both the deployment environment and the particular users being served. This is accomplished through site-specific training of a transformer-based deep learning model that learns to efficiently probe portions of H most relevant to the particular users being served by exploiting the underlying structure of the surrounding environment. The deep learning model then uses these probing measurements to design transmit and receive beams that couple low self-interference while delivering high gain to a pair of downlink and uplink users. For favorable multi-user scaling, a single set of probing measurements can be used by the model to serve several users throughout the coherence time of H by leveraging correlations across those users' channels. Simulation results using ray-tracing demonstrate that our proposed approach exceeds the best possible performance with explicit channel estimation across a wide range of scenarios, especially with large antenna arrays.

Near-field beamfocusing enabled by extremely large-aperture arrays (ELAA) is a promising 6G technique for massive connectivity and high spectrum efficiency. While beamfocusing concentrates energy at an intended user, the radiated field outside the focal point exhibits a structured leakage that varies with the focal-point coordinates. This paper shows that this leakage enables a new form of passive user localization in which distributed far-field sensors measuring only received power can infer the user's location by exploiting this location-dependent power signature. Using the induced noncentral chi-square statistics, we derive a Bayesian Cramér-Rao lower bound (BCRLB) that establishes the fundamental limits of this inference problem. We then evaluate a model-based grid-search estimator and an attention-based permutation-invariant deep learning regressor (DeepSet). Results under both line-of-sight (LoS) and multipath propagation confirm that reliable location inference is feasible, with accuracy improving as more sensors and snapshots are used.

Short-packet communication alters the fundamental performance limits of reconfigurable intelligent surface (RIS)-assisted systems, making conventional analyses based on the infinite blocklength regime insufficient. This work investigates RIS-assisted transmission in the finite blocklength (FBL) regime while explicitly incorporating thermal noise generated by passive RIS elements, an effect commonly neglected in existing models. A unified analytical framework is developed to characterize the block-error rate (BLER), its asymptotic behavior, and the resulting goodput under both uniform and non-uniform RIS reflection coefficients. Our results show that ignoring RIS thermal noise leads to a pronounced overestimation of reliability with the mismatch increasing as the number of reflecting elements grows. Furthermore, increasing the RIS size does not always improve performance, particularly in the low transmit power regime where accumulated noise becomes dominant. Overall, the results highlight fundamental limitations of idealized RIS models and demonstrate the need for incorporating thermal noise for accurate system evaluation.

Achieving effective uplink bistatic ISAC over an OFDM waveform gives rise to challenging interference structures. These are mostly due to unequal direct- and echo-path contributions and Doppler-induced ICI, rendering orthogonal resource separation and fixed SIC strategies inadequate. To address this problem, we propose a RS-inspired framework where the transmitter splits each communication message into a robust and a supplementary stream, which are jointly superposed over a sensing signal. Furthermore, we present the design of a staged sensing-communication receiver. Based on this framework, we derive tractable per-subcarrier SINR expressions and establish the relation between sensing accuracy and communication reliability based on the Fisher information. Building on these, we formulate a joint power-allocation problem for SE maximization under sensing-performance and power constraints. The resulting non-convex formulation is solved using convex surrogates and fractional programming. Numerical results demonstrate that, compared to NOMA-inspired baselines, the proposed framework provides more effective IFI management and improved robustness to Doppler-induced ICI.

This paper introduces a Doppler domain localized (DDL) implementation of the adaptive matched filter (AMF) for radar target detection in severely heterogeneous clutter environments with limited training data. The proposed detector uses the concept of a region of possible target detection (RPTD), a small set of Doppler bins that capture most of the target signal power. This RPTD-based DDL-AMF detector outperforms an earlier suggested DDL implementation of the generalized likelihood ratio (GLR) test, which employs the region of detection improvement (RODI) concept. Unlike the RODI-based DDL-GLR detector, the proposed DDL-AMF detector requires no information on clutter spectrum parameters and no measurements to determine the number and locations of RODIs. Moreover, the performance of the RODI-based DDL-GLR detector falls far below the optimum when the target Doppler frequency is unknown. In contrast, the RPTD-based DDL-AMF detector ensures rapid adaptive detection with near-optimum performance under unknown target Doppler frequency and multimodal clutter spectra.

This study investigates radar technology for non-invasive brain imaging and tumour detection, offering an alternative to MRI and CT scans. Using Ansys HFSS to simulate electromagnetic interactions in brain tissues, we evaluate the penetration, signal strength, and safety of Patch and Vivaldi antennas. Results show Patch antennas are optimal for tumour localization, while Vivaldi antennas suit broader scanning applications. Although promising for safer, more accessible imaging, especially in resource-limited environments, further research with diverse models and actual patient data is essential to advance this technology in non-invasive medical diagnostics.

Motor-imagery (MI) EEG can be classified using supervised machine learning techniques such as Linear Discriminant Analysis applied to features extracted by Common Spatial Patterns. Performance of these models varies widely, possibly due to MI studies commonly utilising differing post-cue time windows and frequency bands to one another. This study aims to assess how the simultaneous optimisation of both these parameters impact MI classification performance. This is done by iteratively training and testing a series of subject-specific models on different combinations of frequency bandwidth and time window options across 109 subjects. This is followed by a statistical analysis using repeated measures ANOVA to uncover significant differences between different bandwidths and time windows in terms of accuracy across the patient cohort. The resulting visualisations and statistical tests show that there are, indeed, significant differences between both specific time windows and specific bandwidths in terms of accuracy. While the comparison of classification accuracies across 23 frequency bandwidths during five different time windows demonstrates an optimal temporal and spectral scale combination of (0, 4) s at the range of (4, 12) Hz across all subjects, the subjects demonstrate similar accuracies for other parameter combinations. These findings highlight the efficacy of personalised models to detect optimal temporal and spectral parameter combinations to best classify MI EEG signals that inherently vary across subjects.

Semi-blind joint channel estimation and data detection (JCD) is a promising approach to mitigate pilot contamination in cell-free massive multiple-input multiple-output (CF-MaMIMO) networks. The effectiveness of such methods fundamentally depends on identifiability, i.e., the ability to unambiguously recover the unknown channel coefficients and transmitted data signals from the received uplink observations. In this work, we investigate the identifiability of semi-blind JCD from a large-scale system design perspective. We consider a CF-MaMIMO network in which access points (APs) and user equipments (UEs) are spatially distributed according to Poisson point processes (PPPs). The resulting network topology is modeled as bipartite random geometric graph (BRGG) that captures local connectivity induced by wireless propagation. To enable a tractable analysis, the spatially dependent graph model is approximated by a surrogate independent-edge random graph with matched degree distributions. Building on this model, we develop a recursive probabilistic analysis that characterizes the conditions under which semi-blind recovery succeeds with high probability. The proposed analysis reveals an identifiability region as a function of key system parameters, including AP and UE densities and the connectivity radius beyond which channel coefficients are assumed negligible. Monte Carlo simulations validate the predicted identifiability region and assess the accuracy of the proposed graph approximation. The proposed framework provides system level insights into how network density and connectivity affect identifiability in large-scale CF-MaMIMO systems and offers guidelines for selecting deployment parameters and pilot sequence lengths that enable reliable semi-blind recovery.

Multiple-input multiple-output (MIMO) radar has waveform diversity and large spatial degrees of freedom (DoFs), making it attractive for high-resolution sensing. Scaling MIMO radar to massive arrays can further improve sensing performance, but it also increases hardware cost, power consumption, and digital processing complexity. The microwave linear analog computer (MiLAC) can tackle these challenges by moving linear operations from the digital domain to the analog domain. MiLAC has shown promising benefits for communications in recent studies and this paper identifies its potential for radar sensing. Specifically, we consider both MiLAC-aided transmit beamforming and receiver-side two-dimensional discrete Fourier transform (2D-DFT)-based direction-of-arrival (DoA) estimation. For transmit beamforming, we formulate a weighted Cramer Rao bound (CRB) minimization problem under lossless and reciprocal MiLAC constraints and propose a penalty dual decomposition (PDD)-based iterative algorithm to address the non-convex problem. We further prove that MiLAC-aided and fully-digital beamforming achieve the same CRB. For receiver processing, we show that the 2D DFT can be implemented by a lossless reciprocal MiLAC, which enables analog-domain DoA estimation without digital optimization. Numerical results confirm the theoretical finding and show that the MiLAC-aided approach achieves the same CRB and DoA estimation performance as the fully-digital benchmark. Meanwhile, hardware cost and power consumption are reduced because only low-resolution DACs are required at the transmitter, while RF chains and ADCs are eliminated at the receiver. Moreover, performing the 2D DFT in the analog domain eliminates all digital DFT operations for DoA estimation.

Predicting Room Impulse Responses (RIRs) remains a challenge due to the high dimensionality of audio signals and the need for perceptual accuracy. This paper introduces a neural network framework that predicts multi-band Energy Decay Curves (EDCs) directly from room geometry and material properties. Unlike standard models, our framework employs a custom composite loss function that optimizes for both energy levels and decay slopes in the log-domain. This ensures the predicted curves adhere to physical decay principles while maintaining high sensitivity to reverberation time and early reflections. Results demonstrate that the model successfully approximates ground-truth acoustics with minimal error in T30 and clarity indices. The approach offers a computationally efficient alternative to traditional simulations, facilitating realistic audio rendering for interactive virtual environments.

Near-infrared spectroscopy is increasingly used as a rapid, non-destructive chemical sensing technology for the analysis of food, pharmaceutical, biological, and environmental samples. However, the practical deployment of NIR sensors still depends on calibration models able to handle high-dimensional, collinear spectra, limited sample sizes, preprocessing dependence, spectral outliers, and extrapolation beyond the calibration domain. Here, we evaluate whether tabular foundation models can provide a new calibration strategy for NIR chemical sensing. We benchmark TabPFN on 66 NIR datasets covering 54 regression and 12 classification tasks, and compare direct inference on raw spectra with preprocessing-optimized inference against PLS/PLS-DA, Ridge, Catboost, and one-dimensional convolutional neural networks. The study uses a unified validation framework in which preprocessing and model selection are performed exclusively on calibration data before external test evaluation. In regression, preprocessing-optimized TabPFN achieves the best overall average rank and significantly outperforms PLS, CatBoost, TabPFN on raw spectra, and CNN-1D, while remaining statistically comparable to Ridge. In classification, TabPFN applied directly to raw spectra provides the best average rank, with performance close to the optimized variant. Robustness analyses show that TabPFN provides strong average predictive performance but that its advantage decreases on spectral outliers and extrapolated samples, where classical chemometric models remain competitive. These results suggest that tabular foundation models can complement established chemometric workflows for NIR chemical sensing, especially in small- to medium-sized calibration settings, while highlighting the need for spectroscopy-specific priors and uncertainty-aware deployment strategies.

Estimation under model misspecification arises in many signal processing problems, where the assumed observation model deviates from the true data-generating mechanism due to errors or simplifications. The misspecified Cramér-Rao bound (MCRB) is a widely recognized mean-squared-error (MSE) lower bound for this case, which has originally been used to describe the asymptotic behavior of the misspecified maximum likelihood (MML) estimator. Despite its widespread use, the MCRB lacks a rigorous characterization of the class of estimators for which it is valid. In this paper, we revisit the theory of parameter estimation under model misspecification and re-examine the foundations of the MCRB. We first demonstrate these limitations and examine a naive version of the MCRB, which relies only on local misspecified unbiasedness. We show that this bound is generally not tight and may be unattainable. To obtain a meaningful bound, we develop a new derivation based on the concept of pointwise equivalent models. By maximizing the naive bound for these models, we recover the classical MCRB, now supported by a constructive derivation, an explicit characterization of the associated estimator class, and an equality condition. This formulation establishes a formal link between local unbiasedness conditions and achievable bounds, offering new insights into the MCRB structure and its relevance to practical estimators. Finally, we define the notion of an efficient misspecified estimator and show that if it exists, it is achieved by the MML estimator.

Flexible coupler antenna (FCA) is a new technique that aims to improve the performance of wireless communication networks by smartly translating low-cost passive couplers around fixed-position active antennas to reshape the induced currents on the passive elements for radiation. Specifically, different couplers can independently control their positions/rotations at the transceiver and thereby collaboratively achieve mechanical beamforming for directional signal enhancement or nulling. The position and/or rotation reconfiguration of passive couplers provides a new and cost-effective means of enhancing wireless communication performance, while significantly reducing the antenna and radio-frequency (RF) chain costs of conventional active arrays. The compact and low form-factor structure of the FCA makes it particularly appealing for devices with stringent size, weight, and power (SWAP) constraints. In this article, we provide an overview of FCA to reveal its promising capabilities in wireless networks, including its system modeling, practical implementation, and competitive advantages over existing techniques. We present a variety of FCA-enabled performance enhancements in terms of mechanical beamforming gain, path-loss reduction, fading mitigation, spatial multiplexing gain, interference suppression, and geometric gain. Furthermore, we elaborate on the design challenges of FCA as well as promising solutions, and discuss the key applications of FCA in wireless networks. Finally, numerical results are presented to verify the substantial capacity gains enabled by FCA-aided transmission in wireless networks.

Flexible coupler antenna systems have recently received significant research interest due to their capability to intelligently reconfigure wireless channels by controlling coupler positions and/or rotations and dynamically exploiting mutual coupling. In this paper, we investigate a new type of flexible coupler antenna, termed rotatable coupler antenna (RCA), for enabling spectrum and energy efficient wireless communication cost-effectively. Specifically, an RCA consists of one fixed active antenna and multiple low-cost passive couplers, each of which can independently rotate in three-dimensional (3D) space, so as to collaboratively achieve mechanical beamforming without requiring additional radio-frequency (RF) chains for the couplers. We study an RCA-enhanced point-to-point communication system, where one RCA is deployed at the transmitter to serve a single user equipped with a fixed antenna. Based on multi-port circuit theory, we establish the channel model and characterize the mutual coupling coefficients as a function of coupler rotations. We formulate a new problem to maximize the received signal-to-noise ratio (SNR) at the user by optimizing the 3D rotations of all couplers, subject to practical coupler rotation constraints. To tackle this nonconvex problem, we develop a spherical-cap conditional-gradient-based algorithm with cross-entropy-method initialization. Simulation results demonstrate that the proposed RCA system can significantly improve communication performance in comparison with benchmark schemes, while requiring substantially fewer active antennas and RF chains.

The paper describes a new method for estimating the poles of an ARMA model using higher-order crossings. The method involves transforming counts of crossing events into estimates of ARMA poles via the autocorrelation domain. An important advantage of the method is that the crossing counts are the only features that need to be stored from the original data. The poles of an ARMA model of a control loop correspond to the roots of the characteristic equation and are thus useful for evaluating control performance.

Global Navigation Satellite Systems (GNSS) underpin positioning, navigation, and timing (PNT), yet their low-power signals are easily blocked or disrupted, leaving gaps in PNT availability in contested environments (e.g. maritime settings) where interference, spoofing, or denial can occur. A key practical need is an independent, ubiquitous aiding signal that can be tracked passively and fused with inertial sensing to sustain full navigation-state estimation without dedicated or cooperative infrastructure. This paper presents an end-to-end LEO-aided hybrid framework that fuses GPS, Starlink downlink beacons, and an inertial measurement unit (IMU) in a 9D (3D position, 3D velocity, and 3D attitude) PNT system using an extended Kalman filter (EKF). We (i) extract Doppler-rate from Starlink downlink beacon tones by associating measurements with satellite IDs, (ii) benchmark beacon Doppler-rate against OFDM-derived range observables under a common processing/estimation pipeline, and (iii) integrate the resulting observable into inertial navigation. We evaluate GPS/IMU, Starlink/IMU, and GPS-Starlink-IMU using Fisher-information predictions, Monte Carlo simulations, and hardware measurements. Results show that Starlink Doppler-rate provides meaningful complementary PNT information, and can aid 9D estimation when GNSS is degraded or intermittently unavailable.

Blind source separation (BSS) is a natural framework for studying how latent causes may be recovered from sensory mixtures, but deriving online and biologically plausible algorithms for structured (i.e., constrained to known domains) and potentially correlated sources remains challenging. Recent work has derived neural networks for BSS from maximization of an entropy measure, yet its online implementations involve complex and nonlocal recurrent dynamics. Motivated by this perspective, we propose Predictive Entropy Maximization, which achieves competitive performance in BSS, using only local weight updates. The method employs a close approximation of an entropy measure, yielding an objective function with easily interpretable components. Minimizing this objective leads to a predictive neural architecture in which feedforward synapses follow an error-driven rule (that can be realized through dendritic mechanisms), lateral inhibitory connections are learned with local Hebbian plasticity, and source-domain constraints are enforced through simple output nonlinearities. We derive explicit spectral bounds on the surrogate error, characterizing when the approximation is accurate. Empirically, Predictive Entropy Maximization remains robust under increasing source correlation and observation noise, outperforms biologically plausible algorithms that rely on stronger independence or decorrelation assumptions, and remains competitive with exact determinant- and correlative-information-based baselines. These results show how local plasticity and adaptive lateral inhibition can emerge from maximizing a regularized second-order entropy over structured source domains. Our implementation code is available at https://github.com/BariscanBozkurt/Predictive-Entropy-Maximization.

In this paper, we theoretically analyze and experimentally demonstrate the performance gains achievable by integrating an in-house built reconfigurable intelligent surface (RIS) with a 5G new radio (NR) system implemented using the OpenAirInterface (OAI) software stack. Unlike conventional RIS-assisted systems that rely on explicit channel state information (CSI) estimation followed by RIS phase configuration optimization, we adopt a low-complexity approach in which the RIS phase states are randomly switched among predefined configurations. The resulting channel fluctuations are opportunistically exploited by the inherent proportional fair (PF) scheduling mechanism of 5G NR. We develop a theoretical framework that characterizes the interaction between RIS switching dynamics and PF scheduling. Based on this framework and the associated analysis, we provide design guidelines for selecting the RIS switching time $T_s$ and the PF throughput averaging window $T_c$ that maximize the system throughput. Experimental evaluations on the 5G NR testbed demonstrate improvements in key performance metrics, including reference signal received power (RSRP), block error rate (BLER), modulation and coding scheme (MCS) index, and throughput. Our key takeaway is that randomly configured RIS operation with appropriately chosen system parameters can achieve performance comparable to optimized RIS designs, with no additional overhead compared to a conventional 5G NR system. More importantly, it requires no coordination between the RIS and the 5G NR system.

Steganalysis models excel on benchmark datasets but struggle in the wild when analyzed images are produced by a processing pipeline unseen during training. This problem known as Cover Source Mismatch (CSM) is particularly hard in realistic settings where practitioners (1) have access to only a small, unlabeled dataset, (2) are unsure of the processing techniques applied to these images, and (3) lack information on the proportion of covers and stegos in that set. To answer this challenge, we introduce TADA (Target Alignment through Data Adaptation), a framework learning to emulate the unknown processing pipeline from a small unlabeled target set. This architecture is trained with a loss combining residual covariance alignment, residual distribution matching, and a $\ell^2$ loss constraining the emulator to produce realistic images. Across toy and operational targets, TADA yields substantial gains in robustness to CSM and improves operational generalization compared to strong holistic and atomistic baselines. Additional resources are available at this link: https://github.com/RonyAbecidan/TADA

Automotive radars are increasingly susceptible to mutual interference from neighboring radar systems, which can lead to false target detections and the masking of valid targets. While current interference levels remain manageable due to the relatively low penetration of radar-equipped vehicles, this assumption is expected to break down as radar adoption and per-vehicle radar density continue to increase. This paper presents a comprehensive analysis of automotive radar performance in high-density interference environments. A realistic end-to-end simulation framework is developed at the intermediate frequency (IF) level, incorporating analytical interference modeling and detailed radar signal processing. The study evaluates the impact of interference across a range of future scenarios characterized by increased radar density and multiple radar configurations per vehicle. Conventional interference mitigation techniques are systematically assessed to validate the simulation results, controlled experiments were conducted using a host radar exposed to up to 30 interfering radars in both anechoic and real-world environments. The results demonstrate significant performance degradation under high interference conditions, with substantial reductions in detection probability and effective range. Among the evaluated techniques, time-frequency coding consistently provides the most robust performance, maintaining high detection probability even at elevated radar penetration rates. These findings highlight the limitations of current mitigation approaches and emphasize the need for coordinated and scalable interference management strategies in future automotive radar systems.

We develop a bottom-up open effective field theory (EFT) for non-Abelian gauge theories within the Schwinger--Keldysh formalism. Instead of integrating out the environment completely and starting from a nonlocal influence functional, we retain the slow environmental response variables explicitly and construct a local system-environment EFT. The environmental sector is described by a dynamical color-frame variable, Stückelberg-like field, and an associated color-current sector, which gives the nontrivial interactions and dissipation between the system and the environment. The resulting construction provides a gauge-covariant Markov embedding of nonlocal and non-Markovian color response. After integrating out the retained environmental variables with retarded boundary conditions, the reduced system theory acquires nonlocal dissipative kernels and stochastic sources. We show that the hard thermal loop response arises naturally as a particular realization of the retained environmental response. Our framework provides a local open-EFT description of color transport, memory effects, and fluctuation-dissipation structure in non-Abelian plasmas, and offers a systematic starting point for dissipative Yang--Mills EFTs with dynamical environments.

Quantum processes with indefinite causal order -- so-called causally nonseparable processes -- can exhibit various advantages over quantum circuits with a fixed or a well-defined causal structure. A natural question is how much nonclassicality is required for a process to display causal nonseparability. Here we address this by investigating how many systems can be dephased (or decohered) before this property vanishes. First, for bipartite processes with open past and future we show that if all systems are dephased, or if only the future system is kept undephased, then the process becomes causally separable. However, if any single system other than the future system remains undephased, then there exist processes that retain causal nonseparability. Next, we demonstrate a similar behaviour in the multipartite case, when restricted to the physically motivated class of quantum circuits with quantum control (QC-QCs). Namely, dephasing all systems or keeping only the future system undephased renders any QC-QC causally separable; while causal nonseparability can persist if any non-future system is left undephased.

We investigate the weak-field regime of generalized hybrid metric-Palatini theories, described by a generic function \(f(R,\mathcal{R})\), where \(R\) is the metric Ricci scalar and \(\mathcal{R}\) is constructed from an independent torsionless connection. Linearizing the field equations about Minkowski spacetime, we show, without using the scalar-tensor representation, that the theory propagates the usual massless spin-2 mode and two massive scalar modes, with an effective gravitational coupling. The absence of tachyonic and ghostlike instabilities at the linearized level, together with the nondegeneracy of the scalar sector, is shown to impose algebraic restrictions on the derivatives of \(f(R,\mathcal R)\) evaluated on the Minkowski background, which generalize previously obtained conditions. The Newtonian limit for an extended static source is derived, yielding a gravitational potential with two Yukawa corrections whose amplitudes are fixed by the scalar residues, while finite-size effects are encoded in source-dependent form factors. We determine the conditions under which the usual Newtonian limit is recovered and derive the effective post-Newtonian parameter \(γ_Σ\) governing light propagation. Finally, we compute the radial epicyclic frequency and the corresponding anomalous periapsis advance, and compare it with planetary precession data to constrain the parameters of a viable hierarchical scalar-mass regime.

We construct charged wormhole solutions with an even number of asymptotically flat regions in the four-dimensional Einstein-Maxwell-massless phantom scalar system via the Harrison transformation. The solutions are characterized by five parameters: the mass $M$, the electric charge $Q_\mathrm{e}$, the magnetic charge $Q_\mathrm{m}$, the scalar charge $P$ and the number of sheets $2n$. The regularity condition then determines the throat radius. Although the Harrison transformation directly generates the solutions only in the parameter region $Q_{\mathrm{e}}^2 + Q_{\mathrm{m}}^2 < M^2$, we show that regular solutions exist in a wider parameter region beyond this bound. In addition, we introduce a spheroidal coordinate system that covers one complete asymptotically flat region and its adjacent ones, and allows the solution to be expressed in a simple form.

We consider the problem of single-photon transmission through an atomic medium, using quantum channel fidelity to describe the resulting information loss. We find that the normalized fidelity decreases monotonically with coupling strength, establishing a performance bound for quantum communication through such media. Our results hold for several channel types and for deterministic and random media.

We establish that the non-adiabaticity parameter has a direct geometric interpretation as the instantaneous evolution speed of a driven quantum state in projective Hilbert space under the Fubini Study metric. In contrast to conventional asymptotic approaches, the proposed framework provides a strictly local geometric criterion that allows non-adiabatic instability and its nonlinear suppression to be evaluated continuously at each stage of the driven evolution. We further show that an occupation-dependent nonlinear regulator Usuppresses the effective geometric evolution speed, leading to bounded low-occupancy dynamics. The resulting crossover parameter provides a compact criterion for self-limited non-adiabatic instability in driven nonlinear bosonic systems.

We study the mass function of primordial black holes (PBHs) within the excursion-set theory, in which the response of the stochastic density contrast to the variation of the coarse-graining scale is described by colored noises. For several window functions often used in the literature, we investigate how this choice affects the formation probability as well as the resultant mass function of PBHs. It is found that the low-mass tail of the mass function differs from the one predicted from Carr's formula. The difference comes from the prevalence of correlated noises, by which degeneracy of the formation probabilities ceases to exist. Nevertheless, Carr's formula still provides a practical estimation in the vicinity of the characteristic mass scale, as long as a smooth window function in Fourier space is used.

Quantum phase estimation (QPE) is a central algorithmic primitive that estimates eigenvalues of a Hamiltonian up to precision $ε$ in Heisenberg-limited time $T=Θ(1/ε)$. Standard gate-based implementations of QPE require deep controlled time-evolution circuits and are not native to analog hardware. Here, we present a simple adiabatic protocol for QPE that achieves (up to logarithmic factors) the optimal Heisenberg-limited scaling $T = O\left( \frac{1}ε \log\left(δ^{-1}\right)\right)$ in both the precision $ε$ and failure probability $δ$. By encoding eigenvalues in populations of computational basis states rather than complex phases, our approach is naturally robust against certain dephasing errors. The adiabatic protocol only requires the ability to couple a single ancilla qubit to the system Hamiltonian as well as pairwise couplings within the ancilla register.

We identify a sharp interaction-degree threshold for the classical simulation of QAOA with $2$-local cost functions. At degree $3$, classical sampling from depth-$1$ QAOA with small multiplicative error would collapse the polynomial hierarchy to its third level. At degree $2$, exact classical sampling from depth-$p$ QAOA on $n$ qubits runs in time $n^{O(1)}$ whenever $p = O(\log n)$. The hard degree-$3$ instances have trivially optimizable cost functions, so sampling hardness does not by itself imply a quantum optimization advantage.

We introduce a novel software-oriented model of quantum computation motivated by the practical constraints of near-term quantum hardware. In this model, gates are specified by constraints expressed in terms of Pauli observables, with each disjoint layer of gates accompanied by a pairwise or $k$-local quantum state tomography of the device. We prove that the model is equivalent to the coupling-graph-restricted circuit model and hence universal for BQP, with a polynomial overhead: simulating a depth-$D$ circuit on $N$ qubits requires at most $O(D^2 N \log N)$ complexity. The model formalizes an idiom shared by existing work that ranges from quantum imaginary time evolution for the study of quantum systems to the use of quantum computers for procedural generation in games. It therefore provides a natural interface for designing quantum software entirely in terms of physically observable quantities, relevant for the NISQ era and into fault-tolerance.

We consider bipartite exact entanglement embezzlement with a catalyst state vector $ψ$ in a Hilbert space $\mathcal{H}$ using unitaries (or more generally, contractions). If $\mathcal{M} \subseteq \mathcal{B}(\mathcal{H})$ is a von Neumann algebra and $U \in M_d \otimes \mathcal{M}$ and $V \in \mathcal{M}' \otimes M_d$ are unitaries (or more generally contractions), then such a protocol is of the form $(U \otimes I_d)(I_d \otimes V)(e_0 \otimes ψ\otimes e_0)=\sum_{i=0}^{d-1} α_i e_i \otimes ψ\otimes e_i$, where each $α_i>0$ and $\sum_{i=0}^{d-1} α_i^2=1$. We show that any such protocol must arise from a unique state on the tensor product $\mathcal{O}_d \otimes \mathcal{O}_d$ of the Cuntz algebra with itself. As a result, we prove that exact entanglement embezzlement is a self-test for a collection of $d$ Cuntz isometries for each party and a unique quasi-free state on the Cuntz algebra $\mathcal{O}_d$ in the sense of \cite{Iz93}. Moreover, we use modular theory to show that the von Neumann algebra generated by the copy of $\mathcal{O}_d$ is the unique separable approximately finite-dimensional Type $\text{III}_λ$ factor for some $0<λ\leq 1$, where $λ$ can be determined by an algebraic condition on the Schmidt coefficients of the state $\varphi=\sum_{i=0}^{d-1} α_i e_i \otimes e_i$.

We investigate photon-axion conversion in the vicinity of rotating Kerr black holes where strong gravity traps photons on near-circular trajectories, effectively enhancing the path length. We explore the observable signatures of such a conversion near the photon region. The process, driven by ambient magnetic fields, is significantly more efficient around supermassive black holes such as M87*, since the luminosity of photons increases with the mass of the BH. By numerically evaluating photon path lengths (on which the conversion depends), we analyze how key parameters-photon frequency, axion mass, photon-axion coupling, magnetic field strength, plasma density, and black hole spin-affect the conversion probability and the resultant dimming of photon spectral luminosity. We find that the conversion is most efficient at high frequencies (X-rays and gamma rays), while the frequency window associated with efficient conversion widens with an increase in the photon-axion coupling and a decrease in the electron density and the axion mass. The magnitude of dimming of the photon spectral luminosity depends primarily on the magnetic field, the photon-axion coupling and the BH spin. Our study reveals that rotating black holes generally exhibit enhanced dimming compared to static ones. Thus, if future telescopes achieving a resolution $\sim 10^{-5}$ arcsec in the X-ray/gamma-ray band detect a dimming of the photon spectral luminosity, then they can provide interesting constraints on the axion mass and its coupling with photons.

Neves and Saa introduced a two parameter spacetime that includes the Hayward, Bardeen, and Simpson-Visser geometries as particular cases. In this work, we employ the generalized off-shell Helmholtz free energy method to investigate the thermodynamic properties of the generalized Bardeen black hole within a topological framework. We construct the associated vector field and analyze its zeros, whose winding numbers allow us to classify the thermodynamic branches and identify critical points associated with phase transitions. The regular black hole configurations exhibit two topological defects with opposite winding numbers, resulting in a vanishing total topological charge, while the Schwarzschild case contains a single unstable branch. Our results demonstrate how the regularization parameters affect the thermodynamic stability and phase structure of the spacetime.

We study if there is an opportunity to describe quantum particles in the vicinity of three types of cosmological singularities, big bang-big crunch, big rip and big brake. Writing down the Dirac equation for spinors, and choosing a convenient parametrization for basis functions of the spinor field, we show that the corresponding second-order differential equation has two independent solutions which are non-singular in the case of all three types of singularities. That permits us to construct the Fock space for the spinor particles and to interprete this fact as their opportunity to cross these cosmological singularities. We show also that this is impossible to do for scalar particles and changing the parametrization does not help. Thus, fermions look more resilient to the passage of the cosmological singularities than bosons.

Local Markovian noise cannot bring entanglement back, but it can bring magic back. Unlike separability, stabilizer membership is not preserved by local channels, allowing dissipation to push states out of the stabilizer polytope as well as in. Under local amplitude damping, the $n$-qubit GHZ family $α|0^n\rangle+β|1^n\rangle$ ($0<α<β$) loses its magic at a lower damping strength $γ_-$ and regains it at a higher one $γ_+$, while entanglement is irreversibly lost at $γ_e$. This magic-entanglement complementarity, $γ_e+γ_+=1$ for every $n$, reflects a system-environment duality of amplitude damping and persists for a broader class of dissipative channels. For small $α$, the reborn magic resides in a fully separable state with all proper marginals stabilizer, yet parity-syndrome extraction concentrates it onto a single qubit for magic-state distillation. Local dissipation further divides pure stabilizer states into magic-generators and magic-insulators: at two qubits, the Bell state $|Φ^+\rangle$ generates magic immediately, while its Bell-state partner $|Ψ^+\rangle$ remains stabilizer. Together, magic and entanglement reveal a symmetry invisible to either alone.

Measurement-based quantum heat engines have attracted significant interest as alternatives to conventional thermal engines, as they replace the hot thermal reservoir with quantum measurements, thereby offering greater controllability and simpler implementation. Motivated by these advantages, we investigate a measurement-driven quantum Otto engine with a qubit working substance and study the optimal work extractable from such engines, including whether their performance can surpass that of conventional quantum Otto cycles. We analyze the engine in both the infinite-time (adiabatic) and finite-time (non-adiabatic) regimes, considering two distinct implementations obtained through optimization over all projection-valued measurements (PVMs) and over all two-outcome positive operator-valued measurements (POVMs). We show that measurement-based engines can outperform conventional quantum Otto engines within specific parameter regimes and that POVM-based engines can yield higher optimal work extraction than PVM-based ones. Furthermore, by incorporating the thermodynamic cost associated with resetting the auxiliary system required for POVM implementation, we demonstrate that the resulting net work output can still exceed that of PVM-based engines under suitable conditions on the spectral gaps and cold bath temperature. We also identify regimes in which non-adiabatic implementations can yield higher work output and efficiency than their adiabatic counterparts. Our study provides operational guidelines for designing improved measurement-driven quantum Otto engines.

We investigate the solid-state implementation of a Dicke-like quantum battery consisting of a two-dimensional material-based Josephson junction inductively coupled to a resonator, using graphene as a representative example. In this configuration, Andreev bound states naturally act as non-interacting, energetically non-degenerate two-level systems, and the setup allows for both single-photon and two-photon resonant processes. The coupling between the LC-circuit flux and the supercurrent through the junction gives rise to peculiar longitudinal interaction terms that have no counterpart in the conventional Dicke model. These additional couplings can enhance energy storage for a proper range of parameters. The proposed architecture also enables an alternative, but equivalent, charging protocol that relies on tuning the superconducting phase difference across the junction.

We demonstrate a practical countermeasure against a well-known class of attacks on quantum key distribution (QKD) systems that exploit detection efficiency mismatch, where the receiver's detectors do not exhibit identical responses to incoming photons across all degrees of freedom. This class of quantum hacking strategies is broad and significantly includes the time-shift attack, which targets an arrival-time-dependent side channel at the receiver. The four-state countermeasure, previously only proven to be secure in theory, is implemented here on a GHz-clocked prototype QKD system and evaluated for its security and performance. We show that its presence enables almost complete recovery of the system's ideal secret key rate. Our results provide strong justification for adopting this countermeasure as a standard component in future scalable and practical QKD systems.

An adversary copies your encrypted traffic today and waits for a quantum computer to decrypt it later. How exposed are you? We show that the functional form of the answer is not merely a calibration choice -- it is structurally justified by three assumptions about adversarial production and value-decay dynamics. Under those assumptions, the HNDL compromise probability factorises into a temporal hazard, a multiplicative cryptographic-vulnerability and operational-exposure term, and a saturation denominator governed by the defense-attack intensity ratio; the marginal sensitivity to each dimension is endogenous to the organisation's position in the vulnerability-exposure plane, not a fixed global constant. Additive scoring frameworks cannot reproduce this structure because the interaction between cryptographic vulnerability and operational exposure is absent by construction, regardless of calibration. The resulting framework provides a structurally grounded basis for operational HNDL exposure prioritisation under partial observability.

We compute the entanglement dynamics across a monitored quantum point contact, where particle losses are recorded on a given site, and demonstrate how this single-site local monitoring substantially reshapes the entanglement production. Contrary to the unitary case, where entanglement entropy grows logarithmically in time, here we find first a linear growth, up to a maximum value displaying volume-law scaling, and then a slow decay to zero, as the system empties out. We capture this crossover using a quasiparticle picture, where the first linear growth arises due to an emergent bias voltage established by the losses, which eventually decays away as the system depletes. We connect our results to studies of the Page curve and to experimentally relevant probes, via full counting statistics of charge transfer across a subregion, with only a single channel to unravel leading to a favorable scaling of the postselection overhead. Natural platforms for this setting include mesoscopic systems and ultracold atoms.

We investigated the possibility that a single measurement run with a definite outcome is a joint unitary evolution of all the participating systems, and measurement runs with different definite outcomes correspond to different unitary maps. With reasonable assumptions, we derived a lower bound of the dependence of the environment after measurement on the state of the system before measurement, conditioned on the same measurement outcome. An experimental test of this dependence relation can either serve as evidence that the unitary dynamics and the definite outcome in the orthodox sense cannot be true together or suggest a deviation from the von Neumann measurement model plus a "conditioning" interpretational step.

We study the dynamics of a binary orbiting a supermassive black hole (SMBH), focusing on both binary scattering in unbound orbits and eccentric von Zeipel-Lidov-Kozai (vZLK) oscillations in bound orbits. The motion is described in a local inertial frame in Kerr spacetime, where tidal effects are encoded in the Riemann curvature. For unbound (parabolic and hyperbolic) orbits, we identify four scattering regimes-adiabatic, tidally affected, chaotic, and disruptive-depending on the binary semi-major axis. As the binary becomes softer, tidal interactions near periapsis lead to strong eccentricity excitation, large changes in the orbital parameters, and eventually chaotic behavior or tidal disruption, with a sensitive dependence on the argument of periapsis. For eccentric bound (elliptic) orbits, the vZLK mechanism differs qualitatively from the standard one, although the $z$-component of the angular momentum in the local inertial frame remains approximately conserved. The evolution proceeds on a dynamical timescale and exhibits step-like changes driven by repeated periapsis passages, which can be interpreted as a sequence of scattering events. We refer to this behavior as scattering-type vZLK oscillations. The rotation of the SMBH also modifies the oscillation profiles, although its effect is less significant than the dependence on the initial orbital parameters. These results suggest a unified picture of periapsis-driven tidal dynamics in galactic nuclei.

We scrutinize properties of electrical charges bounded to visible and dark matter sectors, in the vicinity of a magnetic poles of both sectors. It turns out that the considered system has an angular momentum despite the charges are at rest. On the other hand, investigation the behavior of electric charges of visible and hidden sectors held at rest outside a magnetically charged black hole, discloses that even if the electric charge are regarded as perturbations on a spherically symmetric magnetic static black hole in dark photon theory, at large distances it looks like a stationary axisymmetric magnetically charged black hole.

Scalable trapped-ion quantum computing is commonly realized with modular chips that feature distinct zones with specific functionalities, such as storage, state preparation, and gate execution. To execute a quantum circuit, the ions must be transported between these zones. This process is called ion shuttling. To achieve reliable computation results, the shuttling process must be optimized. However, as the number of ions increases, this becomes a high-dimensional optimization problem where optimal solutions cannot be computed efficiently. We demonstrate, to the best of our knowledge, the first use of reinforcement learning (RL) for the optimization of ion shuttling. RL is well-suited for such scenarios, as it enables learning a strategy through direct interaction with the problem. We show that our RL approach outperforms current state-of-the-art heuristic techniques, yielding a reduction in shuttling operations of up to 36.3 %. Furthermore, we show that our method is easily applicable to various chip architectures. Our approach offers a versatile method to study shuttling efficiency during chip design and, therefore, a highly relevant tool for future, more complex architectures.

We present a streamlined implementation of a computational framework for constructing and analyzing reduced dynamical maps for complex system--bath models at finite temperature. The methodology is based on three established ingredients of quantum dynamics: the Choi--Jamiołkowski isomorphism for the representation of quantum channels, thermofield (TFD) purification of thermal environments, and tensor-train (TT) propagation of the resulting enlarged pure state. The reduced map is obtained from a single unitary propagation in a thermofield-doubled Hilbert space and represented in matrix form through the Choi--Jamiołkowski isomorphism. The TFD evolution is implemented in the TT representation, enabling efficient propagation of high-dimensional purified thermal states. We illustrate the methodology for exciton transfer in the Fenna--Matthews--Olson complex with site-dependent structured spectral densities represented by discretized bosonic environments. The resulting maps are used to analyze decoherence, relaxation, and finite-memory effects, and to assess the crossover to an effectively time-local description. The proposed approach provides a route to compute reduced propagators and to post-process them into memory kernels, transfer tensors, and effective kinetic rate descriptions for complex molecular systems.

We study permutation-invariant quantum codes in the symmetric subspace $\mathrm{Sym}^n(\mathbb{C}^q) $ of $n$ qudits of local dimension $q$. For every integer $q\geq 2$, we construct a permutation-invariant code with parameters $((4,q,2))_q$. Thus four physical qudits suffice to encode one logical qudit with distance two in the symmetric sector for every local dimension. We also show, using linear-programming constraints for permutation-invariant quantum codes, that no permutation-invariant code of dimension $q$ and distance at least $2$ exists in $\mathrm{Sym}^n(\mathbb{C}^q)$ for $n\leq 3$. Hence four qudits are necessary and sufficient. The construction has a simple representation-theoretic and combinatorial description. In the irreducible $\mathrm{SU}(q)$-module $\mathrm{Sym}^4(\mathbb{C}^q)$, the distance-two Knill-Laflamme conditions split into root and Cartan parts. By restricting supports to the even-entry occupation layer, all root-error conditions vanish automatically. The remaining Cartan conditions reduce to linear balancing constraints on packets of occupation vectors. These packets admit a natural graph-theoretic interpretation in terms of the vertices and edges of the complete graph $K_q$: for odd $q$, they are organized by the midpoint rule, while for even $q$, they are organized by a decomposition of $K_q$ into perfect matchings. In this way, the existence of minimal $((4,q,2))_q$ permutation-invariant codes is reduced to a parity-dependent edge-coloring problem on $K_q$.

Building on Padmanabhan's entropy functional, originally introduced to derive Einstein's equations and highlight the emergent nature of gravity, we demonstrate its robustness in a broader context. Using the same entropy density, we show that the Brown-York (BY) tensor arises naturally as the projection of the canonical momentum conjugate to the normal vectors on the relevant hypersurface, thereby providing a common construction applicable to both timelike and null hypersurfaces. This perspective also offers insight into the structural differences of the null BY tensor, including its non-symmetric character. We further extend the analysis to scalar-tensor theories, showing that the entropy-based formulation reproduces the expected equations of motion along with the corresponding BY tensor, and, clarifies its non-conservation in the presence of additional scalar field which is non-minimally coupled. Our results provide a coherent variational interpretation of quasi-local gravitational quantities and reveal a common underlying structure linking bulk dynamics and boundary momentum.

As trapped-ion quantum computing scales to larger qubit registers and more complex control protocols, classical control systems face a fundamental tradeoff: sub-microsecond board-level feedback requires tight hardware coupling, whereas maintainability and extensibility require clean, modular software abstractions. This paper presents QuCtrl-BELL (Bell), a compiler-driven software stack for trapped-ion quantum control. The design resolves this tradeoff by decoupling control flow -- including loops, branches, and synchronization -- from hardware state data. A Python-embedded domain-specific language (DSL) is lowered through a six-stage transpilation pipeline covering control flow graph (CFG) construction, static single-assignment (SSA) conversion, liveness analysis, and graph-coloring register allocation. The compiler generates deterministic distributed board-level programs and compact step-table data. A cross-board synchronization protocol supports feedback loops with latency below 700~ns without host intervention. Bell is deployed and evaluated on the QuCtrl-BELL platform (RISC-V + PXIe), demonstrating that a compiler-based infrastructure can provide programmability, deterministic timing, and modularity for scalable trapped-ion quantum control.

We study the entropy of static, spherically symmetric black holes in diffeomorphism-invariant theories with nonminimal matter--curvature couplings, using the covariant phase space formalism. For regular bifurcate Killing horizons, the Iyer--Wald construction gives the standard Wald entropy. If a matter field cannot be smoothly extended to the regular bifurcation surface, however, the horizon surface charge variation can contain finite contributions that are not included in the Wald entropy density. In the representative obtained by directly varying the action, and after ordinary work terms are subtracted, we decompose the entropy entering the first law of black hole thermodynamics as \(S_{\mathrm H}=S_{\mathrm W}+S_1+ΔS\). Here \(S_{\mathrm W}\) is the Wald entropy, \(S_1\) is the non-Wald part of the Noether charge, and \(ΔS\) is the remaining integrable part of the horizon surface charge variation. Applying this criterion to Kalb--Ramond, bumblebee, and extended Gauss--Bonnet black holes, we find that the regular Kalb--Ramond branch has \(S_{\mathrm H}=S_{\mathrm W}\), the bumblebee branches yield either \(S_1=0\) with \(ΔS\neq0\) or a cancellation between \(S_1\) and \(ΔS\), and the Weyl-vector extended Gauss--Bonnet examples require both corrections. This gives a direct test of whether the Wald entropy density is sufficient, or whether the full horizon surface charge variation has to be used.

We study long-range nonstabilizerness (LRN), namely the obstruction to remove nonstabilizerness with shallow-depth local quantum circuits. In one-dimensional settings, the mutual information between disconnected spatial regions has proven to be a powerful tool to diagnose LRN. In this work, we focus on encoded states of two-dimensional topologically-ordered systems, and explore the ability of the mutual information to serve as a diagnostic of LRN. Focusing on the concrete setting of lattice models defined on a torus, we show that information about LRN can be gained from the analysis of the mutual information between non-overlapping regions containing non-contractible loops, and of the change of such mutual information under modular real-space transformations. We exemplify this idea in the toric code and the non-abelian string-net model with doubled Fibonacci topological order. In the former case, we show that the mutual information provides a full classification, certifying LRN for all encoded non-stabilizer states. In the latter case, instead, our approach does not lead to a full classification, as it detects LRN for all states except from a finite subset with special transformation properties under the modular group. Finally, we discuss how our results on LRN constrain the logical gates that can be implemented fault-tolerantly on the torus.

This Letter discusses two retrodictions of the law of ratchet universality which explain previous numerical and experimental results concerning the diode effect in conventional superconducting tunnel-junctions in one case, and controlled suppression of electron-hole pair generation in a tunnel junction in the other, both in the presence of biharmonic driving fields. Our study demonstrates that the ratchet universal driving field maximizes the diode's efficiency while yielding a maximal rectification range for the supercurrent, on the one hand, and optimally reduces the excess quantum noise with respect to the dc noise level, thus allowing for the efficient production of nonclassical photonic states. These results suggest that the ratchet universality law seems essential for any \textit{optimal} application of the ratchet effect, particularly in the contexts of superconducting integrated power electronics, electron quantum optics, and quantum computing.

In most stabilizer-based quantum computing schemes, so-called magic states are a necessary resource for implementing non-transversal quantum gates. With the resource theory of magic, it is possible to analyze and quantify the generation of the non-stabilizer states. The relative entropy is a measure used in various resource theories. For single qubits, we characterize magic states and their closest stabilizer states by applying analytical results known from the relative entropy of entanglement and show that the magic states and their closest stabilizer states are arranged symmetrically around the states at the centers of the faces of the stabilizer octahedron. For tensor products of single-qubit states, we prove analytically that the relative entropy of magic is nonadditive in almost all cases.

Experiments performed on quantum systems often measure multitime correlation functions. When quantum systems are weakly coupled to their environment, the time evolution of such correlation functions can be reduced to that of the reduced density matrix by the quantum regression theorem (QRT). While no QRT is available for general non-Markovian open quantum systems, we show that for time-independent Hamiltonians and finite memory times $τ_c$, an exact factorization rule exists that relates higher-order multitime correlations to products of lower-order correlations. Consequently, all information needed to reconstruct $n$-time correlations is contained in a temporal volume of $\mathcal{O}(τ_c^n)$. On the example of quantum dots coupled to phonons, we demonstrate that this factorization makes numerical calculations of multitime correlations extremely efficient and even enables semianalytical solutions in systems where the standard QRT breaks down.

We study a string-motivated theoretical prior on the quintessential dark energy model with exponential potential, \( V(φ) = V_0 e^{-λφ} \), allowing for non-zero spatial curvature. First, we formulate the corresponding dynamical system and investigate its cosmological evolution numerically, illustrating the phase-space behaviour and the influence of curvature on the background dynamics. In open universes (\( Ω_k > 0 \)), it has been suggested that a curvature-related fixed point may support accelerated expansion even for relatively steep potentials compatible with swampland considerations. Next, we explicitly impose swampland-motivated priors on the slope parameter $λ$, restricting it to values consistent with the de Sitter conjecture that excludes the (curved) $Λ$CDM limit. Furthermore, we restrict our considerations to the range of field excursion that is consistent with the swampland distance conjecture. Our primary interest is the possibility that such theoretically-motivated priors may shift values of cosmological parameters inferred by observational data, compared with the standard analysis based on theory-agnostic priors such as a sufficiently wide flat prior. We examine this possibility using a combination of Planck CMB data, DESI BAO measurements, and recent Type Ia supernova samples, performing a Bayesian inference of the model parameters. Our analysis indicates that the swampland-motivated prior mildly shifts the values of $Ω_k$.

Ghost-free non-local gravity is investigated with regards to its late-time dynamics. Viable solutions in this model are confronted with the observational data including the Pantheon+ catalogue of Type Ia supernovae, the Dark Energy Spectroscopic Instrument, the measurements of baryon acoustic oscillations and the Hubble parameter estimations $H(z)$. The ghost-free non-local gravity is found to be successful in these tests in comparison to the $Λ$CDM model and can be also comparable with the generalized exponential $F(R)$ gravity scenario. However the model encounters difficulties when the data from the above observations and the cosmic microwave background radiation data are combined. In tests with the whole set of Pantheon+, DESI, $H(z)$ and CMB data, the generalized exponential $F(R)$ model is essentially more successful. This success is related with the dynamical behavior of its effective dark energy equation of state evolving from a phantom to a quintessence phase during the late-time epoch, whereas the ghost-free non-local model demonstrates only a quintessence behavior. Hence the ghost-free non-local gravity scenario is successful only when the Pantheon+, DESI and $H(z)$ data are considered. The generalized exponential $F(R)$ model satisfies the viability conditions and in tests with all observational data including CMB surpasses the $Λ$CDM model in $χ^2$ statistics and also with information criteria.

We report the demonstration of a bulk, intrinsically phase-stable source of polarization- and time-energy-entangled photon pairs at 810nm and 1550nm, directly coupled into single-mode optical fibers. This highly non-degenerate wavelength combination is well suited for hybrid quantum communication networks, enabling low-loss transmission in optical fibers at 1550nm while maintaining efficient free-space propagation and detection at 810nm. The source is based on spontaneous parametric down-conversion in a periodically poled lithium niobate crystal embedded in a polarization Sagnac interferometer, providing inherent stability and dual-degree-of-freedom entanglement. We measure a spectral brightness of B = 4800 pair/s/mW/GHz, with fiber coupling efficiencies exceeding 0.48 at both wavelengths. The entanglement quality is characterized by high-visibility two-photon interference, yielding net visibilities of 0.995 in the polarization basis and 0.991 in the energy-time basis. These performances demonstrate a compact and robust entanglement source compatible with hybrid fiber/free-space quantum key distribution architectures, and suitable for future ground-to-satellite quantum communication links.

Some time ago, we published the full count of degrees of freedom in the linearised weak gravity limit of arbitrary New GR models. We did it by considering the linear equations of motion and presented a thorough analysis with no ambiguity left. A bit later, we generalised it to linear cosmological perturbations and discussed the strong coupling issues that appear already at this level. Recently, there were claims that some dynamical modes had been missed in our work. However, the authors of the new claims did not look at the equations of motion and analysed the quadratic Lagrangian densities instead. In this paper, I take one of the most elementary cases, namely the vector modes in New GR of Type 3, and show what was their mistake that had led them to claiming that those were dynamical. The main message: Do not substitute constraint equations into a Lagrangian.

Cosmological data from the cosmic microwave background (CMB), baryon acoustic oscillations, and Type Ia supernovae suggest that the component driving the accelerated expansion of the Universe may be dynamical at the $\sim 2.5$-$3σ$ CL. The best-fit CPL model produces a level of cosmic structure similar to that of $Λ$CDM, with both models exhibiting mild tension with redshift-space distortion data. In this {\it Letter}, we parametrize possible departures of the effective gravitational coupling from Newton's constant in the late Universe, below a comoving scale $λ_c$, using two redshift bins, $0 \leq z < 1$ and $1 \leq z \leq 3$. We then determine the optimal values of $λ_c$ and the amplitude of these deviations from General Relativity, assuming a background with dynamical dark energy in CPL form. We find that, in order to achieve the required suppression of structure growth at low redshifts while remaining consistent with CMB constraints -- primarily from the late-time ISW effect at low $\ell$ and lensing at high $\ell$ -- modified gravity effects must appear on scales smaller than $λ_c \sim \mathcal{O}(10)\,\mathrm{Mpc}$. Using Planck PR4, DESI DR2, Pantheon+ (or DES-Dovekie) and redshift-space distortions data we confirm that a CPL background with standard gravity is moderately preferred over $Λ$CDM; this preference strengthens to a mildly strong level when modified gravity effects are included. This enhancement leaves the CPL parameters largely unchanged, but shifts them slightly further into the quintom region.

Modular variables serve as a striking example of quantum nonlocality, particularly in superpositions of wave packets that are spatially well separated, where the relative phase between components cannot be accessed through conventional local measurements. In this work, we explore the time evolution of Hermitian modular operators for Gaussian wave-packet superpositions under the influence of a uniform gravitational field. We consider both unitary dynamics governed by the Schrödinger equation and open-system dynamics described by the Caldeira-Leggett master equation in the high-temperature limit. Adopting the Bohmian interpretation of quantum mechanics, we compute local expectation values of these modular operators along individual particle trajectories. Our analysis shows that gravitational acceleration induces a time-varying modular signal, the expectation value of the modular observable, that remains sensitive to the relative phase between the separated wave packets. In contrast, standard local quantities such as the probability density and probability current, while modified by gravity, become insensitive to the relative phase in the regime of negligible spatial overlap. For a pair of particles coupled to a shared environment, we find that environment-induced correlations can modify the local modular expectation value observed for one particle, yielding a clear signature of environmental influence. However, the transfer of phase sensitivity via environment-generated entanglement to the modular signal of the distant particle remains negligible within the regime considered. We further demonstrate that conventional measures of coherence and entanglement do not capture the relative phase information in this non-overlapping regime.

Optically trapped ultracold polar molecules can have multiple long-lived states for coding quantum information, and can exhibit electric dipole-dipole interactions~(DDI) which enables entanglement generation. The general understanding on the quantized motion~(QM) of molecules in the traps is that it causes fluctuation of DDI. Here, we find that the molecular QM can realize an asymmetric quantum Rabi model, which is of specific importance in the study of fundamental physics. The molecular QM can also lead to an exotic trap-dipole resonance, resulting in excess population loss to uncoupled motional states, and, hence, should be avoided in a general quantum control over polar molecules. To examine the impact of QM on quantum computing based on polar molecules, we introduce two gate protocols, a fast iSWAP gate which can be realized by a global microwave pulse of pulse area smaller than $2π$, and a controlled-phase gate with an arbitrary controlled phase, and find that both gates can attain a high fidelity.

We emulate optically interconnected quantum processors in ring, star, and line topologies using a quantum computer. GHZ benchmarks show that the star provides the best trade-off between cost and fidelity under transduction and fiber noise.

This work develops a conceptual framework for the foundations of quantum physics, linking two main approaches: the algebraic formulation and quantum probability. Rather than proposing new axioms or theories, the text reorganizes and synthesizes existing models, highlighting their assumptions, conceptual structures, and operational significance. The analysis begins with von Neumann's measurement theory and its subsequent developments by Mackey, emphasizing the role of experimentally feasible procedures and the need for a statistical model grounded in laboratory practice. The work adopts an operational perspective, according to which physical quantities are defined solely through experimental measurement methods, and the corresponding probabilistic measures are derived from measurement outcomes. The introduction critically examines the limitations of purely mathematical formulations - such as the algebraic method - when separated from experimental interpretation. The text argues for a clear distinction between axioms, postulates, and presuppositions, and for a reconstruction of quantum theory that respects both empirical constraints and conceptual clarity. Overall, the goal is to provide a coherent path from operational principles to algebraic structures, offering a basis for an axiomatic reformulation of quantum mechanics that remains faithful to physical practice.

The application of the notion of `observable' from gauge theory to diffeomorphism-invariant theories -- most relevantly to general relativity -- has led to numerous conceptual and technical issues when interpreting classical theories with this symmetry and building quantum versions of them. In this article I distinguish between two senses of gauge transformation: local and global, and I argue that the notion of observable appears more naturally in the local sense of gauge transformation. Then, I argue that diffeomorphism invariance can be understood as a gauge symmetry only from a global point of view, and hence, that the concept of observable applies only in a restricted manner. This has the consequence that some popular claims in the literature, such as the claim that the physical content of diffeomorphism-invariant models is encoded in correlations, are unfounded.

Not all entangled states are useful for quantum teleportation. We present a geometric method to construct optimal teleportation witnesses, which provide operational necessary and sufficient criteria for identifying the teleportation usefulness of arbitrary two-qudit entangled states. Specifically, by developing a two-layer iterative cutting-plane algorithm to solve the shortest distance problem from the target state $ρ$ to the convex set $S$ of useless states, we obtain the projection point $σ^* \in S$ and then construct the optimal teleportation witness from the projection geometry. Moreover, the shortest distance $D(ρ)$ obtained during this construction also serves as a necessary and sufficient criterion for usefulness. We apply our method to identify the teleportation usefulness of three classes of entangled states.

I point out three ways in which the perspective of quantum information may lead to distorted claims about physics: forgetting that light does not need to be quantised to show coherence; ignoring the generators of unitary evolutions; and approaching the discovery of nature as a fight against an adversary.

The distribution of dark matter (DM) halo around supermassive black holes (BHs) may leave observable imprints on stellar dynamics near galactic centers. Motivated by this, we investigate the orbital motion of the S2 star in the spacetime of a recently derived generalized Schwarzschild BH solution embedded in a Dehnen-type $(1,4,γ)$ DM halo, considering it as a possible model for Sgr A$^{\star}$ at the center of the Milky Way. Unlike previous studies restricted to specific values of the halo parameter $γ$, the present solution describes the fully generalized case with arbitrary $γ$. We derive the corresponding equations of motion and obtain the associated perihelion shift over one orbital period. Using observational data of the S2 star, we constrain the parameters of the Schwarzschild--Dehnen BH-DM system through a Markov Chain Monte Carlo (MCMC) analysis. Our results yield the best-fit values $γ= 1.18^{+1.03}_{-0.81}$ $(1.23^{+1.01}_{-0.85})$, $ρ_s = 0.37^{+0.42}_{-0.29}$ $(0.31^{+0.44}_{-0.26})$, and $r_s = 0.05^{+0.05}_{-0.03}$ $(0.14^{+0.18}_{-0.10})$ for observational data of Do et al.~\cite{Do19} and Gillessen et al.~\cite{Gillessen17ApJ}, respectively. We further obtain the corresponding 95\% confidence upper bounds: $γ< 2.66$ $(2.67)$, $ρ_s < 0.93$ $(0.92)$, and $r_s < 0.16$ $(0.52)$. These results demonstrate that precise stellar orbit measurements can provide meaningful constraints on the DM halo distributions surrounding supermassive BHs and may offer insights into the DM environment of Sgr A$^{\star}$ at the center of the Milky Way.

We investigate timelike geodesics around Damour-Solodukhin wormholes, which are Schwarzschild-like geometries characterized by a deformation parameter $λ$ that determines the radius of the throat, $r_{\rm th}$. The radial potential admits four roots, including the throat radius itself, allowing the throat to merge with other roots and form double, triple, and quartic degeneracies. In particular, triple-root configurations associated with the throat determine the innermost stable circular orbit (ISCO), providing a potential observational distinction from Schwarzschild black holes. Using the Mino-time parametrization, we derive particle trajectories with closed-form analytical solutions in terms of incomplete elliptic integrals for both bound and unbound motion. In particular, we focus on double or triple roots are located at the throat, the azimuthal angle and coordinate time exhibit logarithmic or power-law divergences as the particle approaches the throat. By contrast, trajectories remain regular when the throat corresponds to a simple root, allowing particles to traverse smoothly between the two asymptotically flat regions. We also derive exact homoclinic solutions associated with the throat and compute the corresponding Lyapunov exponent. In addition, inspiral and plunge trajectories through the throat are analyzed. These results provide analytic insights into particle dynamics and possible observational signatures of the wormholes.

Magnetic fields observed across cosmic scales are difficult to explain within conventional physics. A primordial origin is, thus, often assumed. While a nonminimal coupling of the inflaton with the electromagnetic field could theoretically generate magnetic fields of about $10^{-13}$ G, this approach faces significant issues, including strong-coupling and backreaction problems. ``Dark photons", arising naturally in hidden-sector extensions of the Standard Model, provide a well-motivated framework for addressing various cosmic as well as particle physics issues. We demonstrate that coupling dark photons with standard ones can result in adequate magnetogenesis without the limitations of existing models. This minimal mechanism may also provide insights into unresolved cosmic mysteries.

Based on Landauer's principle, we provide a geometrical definition for the entropy of a given static, spherically symmetric spacetime. Considering a congruence of geodesics across a surface, one defines the entropy of a congruence as the surface integral of the entropy of the constituent geodesics. Under certain mild assumptions, we establish a second law for the entropy function thus defined (Landauer entropy), and relate it to Bekenstein-Hawking entropy.

Although numerous measures of entanglement have been proposed so far, the calculation of a given faithful entanglement measure is a hard work since it is always involved in some optimization process. It is, therefore, important to estimate the lower bound of a given entanglement measure for an arbitrary quantum state. This results in a subject of intensive mathematical research. In particular, along this line, the lower bounds of concurrence or other measures that are induced from concurrence have been explored a lot. Here, we investigate the lower bounds of two kinds of entanglement monotones, i.e., $q$-concurrence ($q>1$) and $α$-concurrence ($0<α<1$), or termed the parameterized entanglement monotone together. We obtain, in the light of the informationally complete ($N$, $M$)-positive operator-valued measure [($N$, $M$)-POVM], the lower bounds for the case of $\frac12<α<1$, $1<q<2$ for two-qudit states, and the case of $2\leqslant q<3$ for two-qubit states. We list several examples which show that the lower bounds based on ($N$, $M$)-POVM outperform that of GSIC-POVM and SIC-POVM, and all these measurement based bounds are better then the ones induced by positive partial transpose (PPT) and realignment criteria in literature. In addition, we obtain an analytical formula of the parameterized entanglement monotone with $\frac12<α<1$ and $1<q<2$ for the isotropic state.

The unified entropy as a promotion of the von Neumann entropy exhibits distinct diversity which contains the Tsallis entropy, the Rényi entropy, the von Neumann entropy as special cases. The unified-($r,t$) entropy entanglement with $0<r<1$ and $0< t\leq 1$ was shown to be an entanglement monotone in literature. In this paper, we explore unified-($q,s$) entropy entanglement with $q>1$ and $qs\geq1$ and show that it is also an entanglement monotone and that both of them are monogamous. Going further, we present two kinds of global multipartite entanglement measures (GlMEMs) based on the unified entropy and each kind has two subclasses which are classified by the parameters $(q,s)$ and $(r,t)$. Consequently, from the view of the complete multipartite entanglement measure theory, we show that one of them is a complete multipartite entanglement monotone and is not only completely monogamous but also tightly completely monogamous, but the other three are even not complete. We also explore the genuine entanglement measures induced by the unified entropy and the relations with the bipartite entanglement and the global entanglement are discussed, respectively.

In this work, we investigate non-interacting holographic dark energy (HDE) with the Hubble radius as the infrared cutoff in Einstein-Cartan gravity. We derive the Einstein-Cartan equations from the action principle and obtain Friedmann-like equations by introducing a torsion scalar. Considering a Weyssenhoff spin fluid, we determine the scaling behavior of the torsion scalar as $Φ\sim a^{-3}$ without introducing an ad hoc ansatz, resolving the ansatz problem of previous torsion scalar scenarios. In the absence of interactions between dark matter and dark energy, the torsion scalar shifts the equation of state for holographic dark energy toward negative values from the dust-like value obtained in HDE without torsion, making cosmic acceleration possible. In particular, the resulting equation of state can approach $ω_X \simeq -1$ and cross the phantom divide within the weak torsion regime $|Φ/H| < 1$. The model predicts a dynamical equation of state in which cosmic acceleration gradually weakens, potentially consistent with recent DESI observations. In spacetimes with torsion, the cosmic distance duality relation between the luminosity distance $d_L$ and the angular diameter distance $d_A$ is modified as $d_L = d_A (1+z)^2 (1+η)$. In the presence of the torsion scalar, we show that the standard relation between redshift and the scale factor is preserved, while the deviation parameter arising from torsion effects is determined as $η\sim \int_{t_S}^{t_O} dt a^{-3}$, where $t_S$ and $t_O$ denote the emission time at the source and the observation time at the observer, respectively. Overall, our results support the feasibility of the model and provide a theoretical framework for preparing likelihood analyses.

Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challenging under hardware and optimization constraints. Existing approaches rely on manually tuned architectures that fail to account for the collaboration between classical preprocessing, phase encoding, and photonic circuit structure, limiting both accuracy and hardware compatibility. In this paper, we propose a neural architecture search framework for hybrid photonic quantum-classical models that combines genetic algorithm-based search with learnable quantum phase encoding to systematically explore the joint design space of classical and quantum components. Our framework encodes 19 hyperparameters across six gene groups and evolves a population of hybrid architectures using group-based crossover, per-gene mutation, and elitism, evaluating each candidate on a short training budget before full retraining of the best found design. We evaluate our framework on two image classification benchmarks, Digits and MNIST, achieving final validation accuracies of 99.44% and 98.78%, respectively, with first-principles execution time estimates on the Quandela Ascella photonic QPU projecting single-image inference at 67 ms (Digits) and 149 ms (MNIST). Our quantum contribution analysis further shows that the photonic layer extracts non-redundant features orthogonal to the classical pathway, providing a measurable accuracy advantage over classical-only baselines. Our results demonstrate that automated architecture search is both practical and impactful for hybrid photonic systems, opening the way for systematic design space exploration of quantum AI on photonic devices.

We establish a correspondence between two independent entropic probes -- the variation of Rényi mutual information (RMI) across the electroweak symmetry breaking (EWSB) transition and the stabilizer Rényi entropy (SRE) -- in tree-level $2\to 2$ elastic scatterings. After angular averaging, the RMI (helicity basis) and the SRE (fixed beam basis) exhibit identical dependence on $\sin^2θ_W$ within each neutral-current channel. We trace this correspondence to a common physical origin that it's the Yukawa mass insertion acts as a $-\mathrm{i}Y$ quantum gate in chirality space. Minimizing entropies across all processes yields $\sin^2θ_W$ values matching purely axial vector-like couplings in $Z$ boson exchanged channel.

In a companion paper arXiv:2510.27676, we introduced a non-perturbative classical renormalisation group (RG) flow equation as a novel method for treating strongly interacting problems in general relativity, with a prominent application to the two-body problem. While we demonstrated that it reproduces perturbation theory, via the Post-Minkowskian (PM) expansion, and its computational efficiency in reproducing the 1PN Post-Newtonian action, its derivation was heuristic. In this work, we place this flow equation on a firm formal foundation. In particular, we demonstrate that a Legendre transform maps the classical analogue of the Polchinski equation precisely to our classical RG equation. This establishes a duality between equivalent, exact RG equations for the gravitational effective action. The result, combined with the successful applications in arXiv:2510.27676, solidifies the classical RG framework as a powerful and rigorous new approach to the general relativistic two-body problem and gravitational wave physics.

We provide a general theoretical derivation of the phase sensitivity achieved by SU(1,1) interferometers under homodyne detection. The general expressions obtained accommodate arbitrary input states and include internal and external losses. In this systematic review, both full SU(1,1) interferometers with two parametric amplifiers and the truncated interferometers with only one parametric amplifier are examined. We investigate scenarios involving both single-output ports and joint homodyne detection, and consider parametric amplifiers with equal gains or with a boosted gain second amplifier. Our analytical formulation provides physical insight and understanding of the improvements in the sensitivity, which are shown to originate from noise reduction and/or signal amplification, depending on the configurations and practical implementations. Surprisingly, the configuration with single-output mode detection and parametric amplifiers with equal gains exhibits the highest robustness to very high internal losses. We finally apply this framework to a ubiquitous $|α,0\rangle$ input two-mode coherent probe state. This approach permits the comparison of different strategies and the optimization of the interferometer performance in the presence of losses. In particular, we determine which amplification and detection configurations provide the best performance, depending on the level of losses. This exemplifies how this general analytical approach provides a powerful tool to design quantum-enhanced interferometers and achieve optimal sensitivity with selected probe states and homodyne detection.

Static spherically symmetric perfect-fluid solutions of Einstein's equations play a central role in relativistic astrophysics and stellar structure theory. While many exact solutions satisfy Einstein's equations mathematically, only a limited subset satisfies physically acceptable conditions such as regularity, positivity of matter variables, and causal sound propagation. In this work, the classical concept of physical acceptability is extended to include thermodynamic considerations. Using relativistic equilibrium thermodynamics, entropy functionals, and the Tolman temperature relation, we formulate a set of thermodynamic acceptability conditions for relativistic stellar models. The Tolman IV solution is analyzed as an explicit example. We show that this solution admits a finite and positive equilibrium entropy functional consistent with the Tolman equilibrium condition. This analysis suggests that thermodynamic consistency provides a natural extension of the Delgaty-Lake acceptability program and may constitute an essential criterion in the classification of relativistic interior solutions.

Minimising EPR consumption is the dominant objective when routing a quantum circuit on a distributed quantum computer (DQC). We present dSABRE, a SABRE-style router for multi-core processors that, on each iteration of a lookahead-driven loop, first resolves any intra-core front-layer gates by SWAP scoring and only falls back to scoring inter-core teleportation candidates when the intra-core front is empty. Three mechanisms drive the improvement over the state of the art: a five-term gate-centric teleportation score that generalises the local SWAP heuristic to the inter-core setting, whose explicit capacity-penalty term keeps the scorer from teleporting into saturated cores; a proactive congestion-relief pass that redistributes idle qubits out of high-demand cores before deadlock; and a BFS-layer construction of the inter-core extended set that respects DAG dependencies layer by layer rather than mixing wires in topological order. Across 18 MQT-Bench circuits at 25, 36, and 64 logical qubits, dSABRE reduces geometric-mean EPR consumption by 41-44% over TeleSABRE and by 16-68% over the gate-teleportation-based pytket-dqc, using standard Qiskit SabreLayout for the initial layout. A large-circuit QFT sweep at 100-360 qubits confirms scalability. Code and online appendices are available at https://github.com/ebony72/dsabre.

We demonstrate how the relative phase between the multiple time periodic driving can decide the emergence and the favorable localization direction of non-Hermitian skin modes. For the static non-Hermitian quantum chain with parity time symmetry, non-Hermitian skin effects (NHSEs) can be prohibited. As the dynamical driving is turned on, NHSEs get artificially reactivated, where the relative phase can serve as the controlling switch by breaking the temporal symmetry constraints. Meanwhile, a change of relative phase can also alter the spatial structures of the long-time averaged effective Hamiltonian, which will consequently lead to the variation of skin localization direction for systems of higher dimensions. Our formalisms can be generally realized in diverse optical and mechanical platforms, and will pave the way for realizing tunable skin density profiles.

Gravitational waves from merging compact binaries are sensitive to line-of-sight acceleration (LOSA) induced by a massive companion in their vicinity. Interestingly, the leading-order contributions of LOSA and residual orbital eccentricity to the Fourier phase of the inspiral waveform exhibit similar frequency dependence, raising the possibility that a small eccentricity could mimic LOSA effects in transient GW events such as GW190814. We perform Bayesian inference using the IMRPhenomXPHM waveform family as the baseline LIGO-Virgo-KAGRA waveform model, augmented with leading-order LOSA and residual eccentricity corrections while using 32 seconds of data associated with GW190814. For a LOSA-only analysis, we find no evidence for a non-zero LOSA effect in GW190814, with a Bayes factor relative to the baseline model of approximately 0.22, consistent with the findings of Hendriks et al. and in tension with the claim by Yang et al., who employed only 4 seconds of GW190814 data. In a joint analysis that includes both leading-order LOSA and eccentricity effects, we obtain informative posteriors for both parameters, with representative values a/c approximately -2.8 x 10^{-3} s^{-1} and e_0 approximately 0.11. However, the corresponding Bayes factor relative to the baseline model is approximately 0.64, suggesting that the 32-second data do not provide significant evidence for either LOSA or residual eccentricity in GW190814. Further, our Bayesian runs reveal a strong correlation between the LOSA and eccentricity parameters, indicating a significant degeneracy in their imprint on the inspiral phase. This finding is consistent with our theoretical arguments and most likely explains the non-zero parameter estimates obtained in the joint analysis.

Photon blockade is vital for single-photon generation, but current schemes with conventional and unconventional photon blockade face critical limitations like the purity-brightness trade-off, hindering the generation of high-performance single-photons. To overcome these limitations, we introduce a fundamentally new photon blockade mechanism by utilizing three-body interactions between a single photonic mode and two qubits. This kind of interaction intrinsically cuts off the excitation path to the two-photon state, resulting in a perfect photon blockade effect. The mechanism operates across a broad parameter range, free from the constraints of strong coupling or weak driving. Remarkably, it breaks the purity-brightness trade-off, enabling the simultaneous achievement of extreme purity and high brightness, both significantly outperforming previous mechanisms. Furthermore, this approach demonstrates robustness against thermal noise and avoids unwanted oscillations in the time-delayed correlation function. This work provides a path for generating high-purity, high-brightness, and robust single-photon sources, a key resource for quantum technologies.

We further develop the proposal in Phys.\ Rev.\ Lett.\ \textbf{136} 071501 that interprets stochastic inflation as an open quantum system, by constructing the open effective field theory for the reduced density matrix of long wavelength modes. We clarify that this open effective field theory enjoys two renormalization group flows: the conventional Wilsonian channel, and a stochastic channel arising from the openness that has no counterpart in ordinary Wilsonian effective field theory. Focusing on the stochastic channel in the hard cutoff scheme, we identify both Gaussian and non-Gaussian diffusion as effective operators in the influence functional, and show that they are required by matching onto correlators and form factors of the perturbative full theory through a method-of-region in time. Beyond Gaussian order, the matching data are no longer local Wilson coefficients but nonlocal and non-Markovian Wilson kernels. We then obtain the bare Hamiltonian density of this open effective field theory and derive its nonlocal functional master equations, including the Fokker-Planck equation for the diagonal density matrix and the Klein-Kramers equation for the Wigner functional, with their zero-modess simplifications discussed. Finally, we take a first step toward a continuum version of this open effective field theory, replacing the hard cutoff by an analytic regulator in the stochastic channel, and demonstrate stochastic renormalization using a massive scalar as an example.

Strong-field high-harmonic generation (HHG) is conventionally described semiclassically, with the driving laser treated as a classical field. This approximation becomes insufficient in nanoscale interaction geometries, where extreme spatial confinement raises the vacuum-field amplitude to the ~10^-2 level relative to the driving-field amplitude. When the quantum fluctuations of the driving field are redistributed between conjugate quadratures by squeezing, they can be directly imprinted onto macroscopic HHG observables. To model this interaction, we employ a Wigner phase-space approach that maps the quantum-optical driver onto a stochastic ensemble of time-dependent Schrodinger equation realizations. Although each realization remains classically simulable, the sub-vacuum quadrature covariance structure of squeezed states cannot be reproduced by any field admitting a non-negative Glauber-Sudarshan P-representation. Within this single-mode Gaussian framework, we show that amplitude squeezing suppresses the shot-to-shot variance of the HHG cutoff below the standard quantum limit (SQL). To leading order in the vacuum-to-driver ratio, the normalized cutoff variance decays exponentially with the squeezing parameter, independent of the absolute vacuum-field amplitude and therefore robust against uncertainties in the effective nanoscale mode volume. A subleading phase-noise contribution from the anti-squeezed quadrature produces a variance minimum near r_opt ~ 1.6, providing a concrete experimental target. These results establish the HHG cutoff variance ratio as a nonlinear, self-calibrating Heisenberg witness in which sub-SQL scaling directly reflects the redistribution of quantum uncertainty in the driving field.

We propose a three-cavity scheme to realize full control of the emitter-cavity coupling strength in cavity quantum electrodynamics (cQED). The involvement of coupled oscillators gives rise to transient dynamics comprising multiple spectral components, which significantly increases the numerical cost to resolve the fluorescence spectrum in the time domain. A generalized sensor method is hence developed to simplify the calculation process for the characterization of nonstationary quantum dynamics. Multi-modal spectroscopy reveals the emergence, splitting, and disappearance of supermodes in real time. Based on the depletion of the zero-energy supermode, ultrafast switching of Rabi oscillations is demonstrated for time-domain multi-modal spectroscopy. These results exhibit a consistent picture from the spectral control of multiple oscillators to the quantum observation in ultrafast dynamics, which establishes the sensor method as a powerful theoretical tool for the ultrafast spectroscopy of cQED systems.

Dynamic link prediction is important for modeling evolving interactions in complex systems, including social, communication, financial, and transportation networks. Classical temporal graph models capture sequential dependencies, but they may struggle to represent concurrent and rapidly changing node-edge interactions in large dynamic graphs. We propose A2QTGN (Adaptive Amplitude Quantum-Integrated Temporal Graph Network), a hybrid quantum-classical framework that combines adaptive amplitude encoding with a Temporal Graph Network backbone. The proposed mechanism represents node interaction features as quantum states and selectively refreshes amplitude embeddings based on temporal activity, preserving stable node states while emphasizing meaningful structural changes. This design reduces unnecessary quantum re-encoding and improves temporal representation for link prediction. Experiments on five Temporal Graph Benchmark datasets show that A2QTGN achieves strong predictive and ranking performance across diverse dynamic graphs. Ablation studies confirm the importance of both the quantum embedding module and the adaptive update strategy, while hardware-aware inference using a noisy backend and limited real-device execution supports the feasibility of near-term quantum-assisted temporal graph learning.

Electron-positron ($e^{+}e^{-}$) pair creation by vacuum breakdown around compact objects is believed to power high-energy astrophysical transients like gamma-ray bursts (GRBs). In this work, we focus on vacuum breakdown around a Kerr black hole (BH) immersed in an asymptotically uniform magnetic field that is inclined with respect to the BH spin axis. The dyadoregion, the region where the induced electric field exceeds the critical value $E_{\text{c}}=m_{e}^{2}c^{3}/(e\hbar)$, is identified via the electromagnetic invariants. It is found that the dyadoregion consists of several lobes whose number, size, and orientation vary with the inclination. We also estimate the electromagnetic energy available for pair creation and derive a beaming factor that allows a conversion between the intrinsic dyadoregion energy and the observed isotropic energy. The thermodynamic properties of the resulting electron-positron-photon ($e^{+}e^{-}γ$) plasma are included, revealing an initial magnetic dominance. The evaluation of the minimum magnetic field required shows that misaligned magnetic fields generally favor pair creation more than aligned ones.

Remote quantum batteries require directional and controllable energy transfer between spatially separated quantum nodes, yet most existing protocols rely on direct charger-battery Hamiltonian couplings. Here we propose a phase-tunable waveguide-QED architecture for remote quantum-battery charging, in which a driven charger and a remote battery are coupled solely via engineered waveguide-mediated interference, without any direct local interaction. We systematically compare four configurations: two-giant-emitter and giant-small-emitter hybrids, each with open or mirror-terminated waveguides. By engineering the propagation and coupling phases, the waveguide-mediated coherent exchange interaction and collective dissipation can be balanced to suppress the backward channel while retaining a finite forward channel, thereby realizing cascaded-like unidirectional charging. Our analysis shows that nonreciprocity and storage efficiency can be independently engineered, offering design flexibility for different quantum network scenarios. The giant-small-emitter mirror-terminated configuration simultaneously achieves perfect nonreciprocity and battery-dominated storage, while both giant-small-emitter configurations exhibit distance-insensitive directionality. Extending the scheme to quadratic driving, we show that anomalous second moments render the battery state non-passive, making ergotropy a performance metric distinct from stored energy. These results establish phase-tunable waveguide networks as a versatile platform for remote quantum-energy transfer and provide design principles for directional and work-extractable energy storage in quantum networks.

Spatially structured dissipation organizes driven quantum matter beyond Hamiltonian control. We show that a dissipation gradient combined with a Stark-induced detuning ramp selects a nonlinear resonance slice in a two-dimensional driven-dissipative Bose-Hubbard lattice, producing a pinned density front in generalized Gross-Pitaevskii simulations. The underlying resonance condition fixes the front position, while its Airy-like profile obeys a width scaling set by tunneling stiffness and the effective detuning slope. Treating the front as an emergent interface explains how tuning the selected resonance toward the minimum-loss side yields Peierls-Nabarro depinning steps, discrete transverse pattern locking, spatiotemporal chaos, and minimum-loss localization. Center-of-mass and generalized-imbalance diagnostics map these outcomes into a dynamical phase diagram as detuning-ramp slope and dissipation-gradient strength vary. The results suggest structured dissipation as a mechanism for reconfigurable transport barriers and nonequilibrium interfaces in programmable bosonic lattices.

Different quantum error correction schemes trade off overhead, error suppression, and hardware connectivity. Code concatenation can relax these tradeoffs by using an outer code whose non-local connectivity is supplied by logical operations of an inner code rather than directly by hardware. Prior works showed that this can reduce memory overhead for local low-rate inner codes such as the surface code. Here, we study concatenation over non-local, high-rate inner codes. Such inner codes experience correlated errors among the many logical qubits in a single codeblock. We handle this by treating each block as a single logical Galois qudit, enabling concatenation with algebraic outer codes with excellent parameters and, crucially, list decoders. In particular, we consider a memory system formed by concatenating quantum Reed-Solomon outer codes over the gross code. For fault-tolerant syndrome extraction, we develop a Galois qudit Shor scheme using "time-like" Reed-Solomon protection against measurement errors. Interestingly, a lightweight fault tolerance scheme, that would fail for qubits, works well for large-alphabet qudits, suggesting a very different theory of fault tolerance for such qudits. The whole protocol is optimised via improved bicycle instruction logical error rates, novel compilation strategies, and recent decoder post-selection rules. At uniform $10^{-3}$ physical noise, the concatenated gross code reaches the teraquop regime, which it previously could not access, with a lower space overhead than the $288$-qubit two-gross code, while offering several advantages from the engineering standpoint. Beyond our main case study, we believe the core ideas of Galois qudits, quantum Reed-Solomon outer codes, and list decoding, will prove generically powerful and highly transferable ideas across high-rate quantum architectures.

Waveguide cavity quantum electrodynamics (QED) with atomic mirrors is a growing research area of quantum optics and can be applied to quantum information processing. We here study the photon statistics of output fields from a waveguide cavity QED system, in which the waveguide is coupled to quantized mirror atoms and one driven medium atom. Our results show that the photon blockade can occur even for a bad atom cavity with large dissipation and small coupling between the medium atom and the cavity, in contrast to the small dissipation and the strong coupling of the medium atom to the cavity field for the conventional photon blockade or the quantum interference for the unconventional photon blockade in the cavity QED system. Utilizing both the master equation and scattering theories, we derive the condition under which the photon blockade occurs in weakly driven systems. We find that such photon anomalous blockade is due to the quantum Zeno effect and is robust against variations of the medium atom's position within the cavity. Our study paves a way to exploit the photon blockade and single-photon devices via the waveguide cavity QED.

This paper utilizes the {\it Black Hole Vision} smartphone application to catalyze a pedagogical shift in General Relativity education through the quantitative analysis of simulated black hole imaging. Presented here for the Schwarzschild spacetime, the investigation is designed with a hierarchical modularity suitable for undergraduate students, with an expanded version intended for graduate courses in General Relativity or Relativistic Astrophysics. By transforming the mobile device into an educational relativistic imaging tool, we triangulate the simulated Schwarzschild mass through independent probes and characterize anisotropic coordinate transformations via a Jacobian map. Global numerical consistency is investigated through integrated coordinate length, while the exponential instability of nearly bound orbits is quantified through a measurement of the simulated Lyapunov exponent. Finally, symmetry is constrained through a sub-pixel constraint on eccentricity in the simulated spacetime. By integrating this statistical framework, the paper enables students to explore the distinction between physical signatures and instrumental noise using established metrological protocols.

Device-independent quantum secret sharing (DI-QSS) provides high security by eliminating the need to trust devices, yet its practical performance is limited by channel loss and noise. This work extends advantage distillation from two-party quantum key distribution (QKD) to three-party DI-QSS, redesigning the corresponding data interaction and verification procedures. The technique is systematically applied to the basic protocol and three active improvement strategies: noise preprocessing, post-selection, and their combination. This approach enhances noise tolerance, reduces the required global detection efficiency threshold, and significantly extends the maximum secure communication distance. Numerical simulations demonstrate that for the basic protocol over fiber, the maximum secure distance increases from 0.16 km to 1.85 km, and the noise tolerance improves from 10.17% to 28.49%. The results show that generalizing advantage distillation to the three-party setting effectively strengthens the protocol's robustness and practicality, enhancing its adaptability to realistic noise and advancing the development of more reliable quantum secret sharing systems.

We prove that there are globally hyperbolic spacetimes $(X,g)$ which are refocusing but not strongly refocusing. In fact, every globally hyperbolic strongly refocusing spacetime of dimension at least $3$ admits globally hyperbolic metrics which are refocusing but not strongly refocusing. This answers a question by Chernov, Kinlaw, and Sadykov. We then prove that globally hyperbolic spacetimes which are Legendrian refocusing (a notion introduced in this paper) admit globally hyperbolic strongly refocusing metrics.

Magic state distillation is a key component of fault-tolerant quantum computation, as it enables the implementation of non-Clifford gates such as the $T$ gate and the $CCZ$ gate via gate teleportation. However, conventional distillation protocols require a large number of logical qubits and introduce substantial spatial and temporal overhead, posing a significant bottleneck for scalable fault-tolerant quantum computation. In this work, we propose a zero-level distillation protocol that efficiently generates a high-fidelity logical $CCZ$ magic state using only physical qubits on a two-dimensional square lattice with nearest-neighbor interactions. Our method leverages the transversal $T/T^\dagger$ operation of the $[[ 8,3,2 ]]$ code to fault-tolerantly encode the state $\overline{CCZ}|+++\rangle$, which is subsequently teleported to three surface-code logical qubits via lattice surgery. To enable teleportation between codes with different distances, we introduce adaptively initialized teleportation (AIT), a tailored initialization procedure for the surface code. Numerical simulations demonstrate that the logical error rate scales as $p_L \simeq 300 \times p^2$ with respect to the physical error rate $p$. For example, the proposed method improves the logical error rate by approximately one and two orders of magnitude at $p = 10^{-3}$ and $p = 10^{-4}$, respectively, compared to conventional seven-$T$-gate approaches. The distillation circuit requires only 22 physical qubits, 3 logical qubits, and a circuit depth of 24, reducing the space-time overhead by a factor of approximately 5-10 compared to previous methods. This result highlights the practicality of $CCZ$-state distillation in early fault-tolerant quantum computation and offers a new direction toward resource-efficient physical-level magic state distillation beyond conventional $T$-state generation.

We investigate the localization of fermionic fields in a five-dimensional braneworld scenario within the framework of modified teleparallel gravity described by a general $f(T,T_G)$ function. Considering a non-minimal coupling between a Dirac spinor and the torsional invariants, we derive the effective Schrödinger-like equations governing the Kaluza-Klein modes. We showed that the contribution of the teleparallel Gauss-Bonnet term significantly modifies the effective potentials and, consequently, the localization properties. The zero-mode analysis reveals that only one chiral component can be localized on the brane, with the degree of confinement depending on the chosen model. In the massive sector, the spectrum is continuous, but resonant states arise due to the internal structure of the potentials. Additionally, we employ information-theoretic measures, such as Shannon entropy and relative probability, to quantify the localization mechanism. Our results show that the torsional modifications induce a nontrivial redistribution of information, exhibiting stronger localization. These findings highlight the role of higher-order torsional terms in shaping fermionic localization and resonance structures in braneworld scenarios.

A recent Letter by Wadhia et al. reports a realization of a quantum clock using a double quantum dot (DQD) [Phys. Rev. Lett. 135, 200407 (2005)]. This Comment identifies two fundamental issues: (I) the claimed ``quantum clock" exhibits only classical behavior and lacks intrinsic temporal correlations between ticks; it is not sufficient for accurate time as a good clock. (II) the thermodynamic analysis misassigns entropy production and conflates amplification with measurement; the reported combined entropy is an engineering dissipation, not a fundamental cost of quantum timekeeping.

We study the maximal analytic extension of the Schwarzschild-like black hole solution in Lorentz gauge theory. The lapse function is $f(r)=A_0^{-2}-2\m/r$, so the horizon is located at $r_+=2\m A_0^2$ and the non-affinity coefficient of the horizon generator is $κ=1/(4\m A_0^4)$. We first analyze the radial null curves in the Schwarzschild-Droste (SD) and ingoing Eddington-Finkelstein (IEF) charts, and then construct the Kruskal-Szekeres (KS) chart adapted to the LGT geometry. The KS extension contains two exterior regions, a black-hole region and a white-hole region. We also present the standard and regular Carter-Penrose (CP) compactifications. The conformal skeleton is Schwarzschild-like, but the physical scale of the horizon, the surface gravity and the constant-radius curves remain controlled by $A_0$. Hence the solution has the same causal topology as Schwarzschild, while it is geometrically inequivalent to it when $A_0\neq1$.

Distributed Quantum Computers (DQCs) enable large system sizes by connecting smaller chips via photonic interconnects. DQCs use teleportation to relocate qubits and execute CNOTs between qubits on different chips. However, non-local CNOTs are 4.3-7.7$\times$ slower and 4$\times$ more error-prone than local CNOTs within a chip, which degrades program fidelities. Existing compilers group CNOTs with overlapping qubits into blocks and collectively optimize teleportations for each block. However, block-level scheduling has two key drawbacks. First, it lacks lookahead ability across blocks because it selects the optimal schedule for one block before proceeding to the next. As a result, it cannot assess the impact of a teleportation on future blocks. Our studies show that naively expanding the lookahead window to include subsequent blocks does not address this issue. Second, existing approaches do not schedule future block operations or the teleportations they require until preceding blocks are fully scheduled, introducing delay and latency overheads. We propose ATHENA, a DQC compiler that addresses these limitations using two key insights: Utility-driven Lookahead with Multi-Candidate Block Scheduling (UMS) and EPR-Capacity-Aware Early Scheduling (EES). UMS schedules a block by considering only useful future blocks in its lookahead window. A future block has utility if it shares overlapping qubits with the current block being scheduled. UMS also maintains multiple schedules during compilation, allowing it to defer commitment to globally sub-optimal schedules early in the compilation process. EES enables ATHENA to schedule future operations and their relocations early when EPR resources are available. Our evaluations show that ATHENA reduces teleportations by 34% on average and up to 65%, and reduces latency by 2$\times$ on average and up to 2.9$\times$ compared to the state-of-the-art.

Completeness of the Klein--Gordon oscillator eigenfunctions is proved in one and three spatial dimensions. The proofs establish the closure relations satisfied by the eigenfunctions and are based on standard properties of the Hermite and the generalized Laguerre polynomials, supplemented in three dimensions by the completeness of the spherical harmonics. The scalar nature of the Klein--Gordon field renders the argument strictly simpler than the analogous proof for the Dirac oscillator: no off-diagonal cancellation is required.

In this study, we examine an innovative framework towards implementing quantum decision trees utilizing a laser-driven four-level system. We discuss a diamond-shaped atomic configuration, in which we apply Lie-algebraic formalisms to analyze the dynamics of the system. The system is perturbed by a Stokes pulse, represented as $β_j(t)$ (for $j=1,2$), which interacts with the atomic states $|0\rangle, |3\rangle$ and $|1\rangle, |2\rangle$. In addition, a pump laser, denoted as $α_j(t)$, couples the states $|0\rangle, |1\rangle$ and $|2\rangle, |3\rangle$. By employing pulse profiles that possess identical temporal behavior but differ in amplitude, one can effectively redistribute the population from the initial ground state to the other energy levels. This technique facilitates the mimicry of a quantum decision tree. We highlight that the proposed methodology is scalable to N-level systems, enhancing its adaptability and potential utility in quantum computing and various decision-making applications. We introduce a novel framework for implementing quantum decision trees using a four-level laser-driven atomic system. Employing a diamond-shaped energy configuration, we analyze system dynamics through Lie-algebraic methods. Using pulse profiles with identical temporal structures but varying amplitudes, we achieve controlled population redistribution among energy levels, effectively simulating a quantum decision tree. This methodology is scalable to systems of \(N\) levels, offering potential applications in quantum computing and decision-making processes.

Generating usable output-entanglement in continuous variable systems can serve as a viable resource for improving applications in quantum information science. In this work, we show how to generate steady-state output-entanglement in a two-stage conversion setup between optical and microwave photon which employs resonantly coupled magnetic and mechanical excitations, as proposed in Phys. Rev. Applied 18, 044059 (2022). We show that the entanglement can be maximized for the same set of parameters which optimize the frequency-conversion efficiency, and that it can be leveraged for a teleportation-based state-transfer protocol for coherent input-states with fidelity close to unity. We propose an implementation based on an Yittrium Iron Garnet disk of micrometer scale, and use both simulation results and reasonable estimates to assess the performance under optimized conditions. We find a maximum teleportation fidelity of 0.75 for the proposed setup.

Efficiently realizing logical operations on general stabilizer codes remains a long-standing challenge in fault tolerant quantum computing. While code surgery provides a general framework with provable guarantees by joint logical measurements, existing constructions are largely theoretical and incur substantial ancilla overhead in practice. In this work, we propose GeneCS, a resource-efficient compiler for synthesizing code surgery protocols for arbitrary stabilizer codes. Our approach leverages structure-aware optimizations to eliminate redundancy in graph construction, dynamically balance expansion and congestion, and incorporate code degree constraints. Experimental results show that GeneCS achieves an average reduction of over $85\%$ in ancillary qubits and checks for both single-code and cross-code logical operations, while preserving logical error rates. Moreover, our compiler scales to codes with more than $10^4$ qubits with an amortized compilation time of about one second per instance. These results enable practical logical operations and efficient cross-code communication, thereby supporting the deployment of modern QLDPC codes and heterogeneous quantum architectures.

We present a review on quantum metrology and sensing, from its foundations to current applications. Highlights of the review include consideration of both frequentist and Bayesian approaches to parameter estimation; single as well as multiparameter estimation; estimation for different encoding processes comprising unitary as well as noisy channels, quantum thermometry, and channels involving indefinite causal order; different estimation strategies incorporating also recent advances like quantum error correction-aided methods and reservoir engineering; usefulness of quantum Fisher information to detect resources; applications of quantum metrology in diverse arenas covering quantum many-body sensors, sensing protocols in atomic ensembles, atom-photon systems, and continuous-variable systems, quantum imaging, quantum illumination, atomic clocks and atom interferometry, etc; and experimental realizations of quantum sensors in different physical platforms.

In this work, we investigate higher-derivative quantum field theories and the problem of Ostrogradsky instability within an open-system Keldysh-Lindblad framework. Coupling the ghost sector to dissipative baths generates non-perturbative effective masses and dissipative widths through self-consistent gap equations. Above a critical coupling, the nonequilibrium dynamics develops bifurcated dissipative branches, signaling the emergence of a dissipative phase transition and a nontrivial critical structure in parameter space. We find that the resulting dissipative dynamics can suppress ghost excitations through two distinct mechanisms: in one branch, a large dynamically generated effective mass preserves a quasiparticle-like excitation, while in the second branch, strong dissipative broadening destroys the quasiparticle character through overdamped dynamics. Our results suggest that dissipative effects may provide a nonequilibrium mechanism for the spectral suppression of Ostrogradsky ghosts. The comparison with the healthy sector indicates that the stabilization mechanism is intrinsically tied to the ghost-like spectral structure.

We explore the concept of antiflatness to characterize the structural fluctuations within the entanglement spectrum of a quantum state (i.e., the spectrum of its reduced density operator). As a measure of the interplay between entanglement and magic, two fundamental quantum resources, antiflatness provides second-order information about quantum correlations that standard average measures fail to capture. Recognizing that standard majorization theory fundamentally orders states by purity and is structurally blind to spectral fluctuations, we introduce a novel partial ordering known as antiflat majorization, based on the Rényi entropy spread. We define Flatness-Preserving Operations (FPOs), establishing new necessary conditions for state convertibility. Furthermore, we unify different measures of antiflatness-such as Capacity of Entanglement, Linear Rényi spread, and Logarithmic antiflatness-using the frameworks of escort distributions and Bregman divergences. We prove that the Capacity of Entanglement can be expressed as a second derivative of the Kullback-Leibler divergence along the escort trajectory, connecting it with the Quantum Fisher Information. Finally, we demonstrate that absolute maximal antiflatness is not achieved by a single universal state, but rather by a continuous Pareto frontier of extremal states with jump spectra, and we analyze the typicality of these spectral fluctuations using Haar, Bures-Hall and t-doped Clifford random state ensembles.

Frequency crowding is a fundamental limitation in superconducting quantum architectures, particularly in tunable-coupler systems. We present a framework that explicitly models both coherent spectator-induced errors and incoherent lifetime effects through an error budgeting approach. Using this model, we analyze how frequency crowding impacts gate fidelity as module size and connectivity scale, and formulate a constrained optimization problem to assign qubit and coupler frequencies under realistic separation and hardware constraints. We demonstrate scalable frequency allocation strategies that minimize spectator-induced errors. We further show that increasing qubit count and coupling density within a module leads to a fidelity-connectivity tradeoff. To explore the benefits at the system scale, we have developed a noise-aware transpilation approach called FINESSE, which minimizes error by selecting high-fidelity paths that satisfy connectivity via SWAP insertion while jointly optimizing downstream gate execution. We demonstrate this physics-informed architecture-transpilation co-design approach for a SNAIL-based third-order coupler that natively realizes the $\sqrt{iSWAP}$ basis with frequency aware gate fidelities. On SNAIL architectures, FINESSE achieves an average 8.9% reduction in log-infidelity cost and 6.8% reduction in circuit depth vs. SABRE. We also compare results on IBM Brisbane's architecture.

We provide some guidance and examples to clear up common misconceptions about special relativity. These misconceptions often come from trying to express the truths of special relativity in Newtonian terms rather than in terms more natural to special relativity itself. This conceptual stance can also help in attaining a better understanding of general relativity.

Spin squeezing in atomic ensembles enables atom interferometry with sensitivities below the shot-noise limit, but the associated entanglement is highly susceptible to loss, making imperfections in atom optics a central limitation. Bragg diffraction is an established technique for driving transitions between atomic momentum states and enables large-momentum transfer through higher-order diffraction while preserving the internal state. However, it is intrinsically limited by two competing mechanisms: short light pulses induce parasitic diffraction into off-resonant orders beyond an effective two-level description, while long pulses face velocity selectivity. We derive analytical expressions in a second-quantized framework for the atom optics and phase uncertainty of a Mach-Zehnder interferometer including these effects. We demonstrate that sub-shot-noise scaling is achieved only in a regime of intermediate pulse duration. Furthermore, we show that deleterious effects of higher-order diffraction are partially mitigated by optimizing the input quantum state.

Close hyperbolic encounters between black holes produce distinctive bursts of gravitational radiation with a time-frequency morphology that is qualitatively different from that of quasi-circular inspirals. Expected to arise in dense stellar environments through dynamical interactions, these encounters probe formation channels and mass ranges inaccessible to isolated binary evolution, making them a compelling target for current and next-generation detectors. In this work, we reanalyze \totalevents high-mass events from the LIGO-Virgo-KAGRA catalogs using the hyperbolic configuration of the~\dali~waveform model. We compare these with analyses using the quasi-circular, precessing configuration of the same model, computing Bayes factors to evaluate which description is favored by the data. We find that most events strongly to mildly favor the quasi-circular, precessing scenario, except for GW190521. For this event, we find that the signal is best fit by a dynamical capture waveform, with Bayes factor $\ln \mathcal{B}^{\rm hyp}_{\rm prec}=3.71^{+0.11}_{-0.11}$. We confirm this preference via further analyses with~\dali~in different configurations (quasi-circular, non-precessing; eccentric, non-precessing; and eccentric, precessing), as well as one using the quasi-circular, precessing numerical relativity surrogate model \nrsur. We also highlight the results we obtain for GW231123, another high-mass signal linked to evidence of strong precession, for which we find strong preference for the quasi-circular, precessing scenario, with $\ln \mathcal{B}^{\rm hyp}_{\rm prec}=-15.80^{+0.24}_{-0.24}$. The analysis of mock signals generated with the best fitting waveforms for GW190521 and GW231123 suggest that the former might belong to a region of parameter space where high-mass, bound, precessing signals can be hard to distinguish from dynamical captures in parameter estimation.

Dissipative quantum chaos is an emerging theory that is expected to extend the ideas, concepts, and methodology of conventional Hamiltonian quantum chaos from coherent evolution to open quantum dynamics. The new theory should provide a set of tools to distinguish chaotic open quantum systems from integrable ones, as well as quantitative measures of their chaoticity (or, conversely, integrability). The foundations of this theory were laid in the late 1980s, and from the very start it was clear that, like its Hamiltonian predecessor, it had to be based on the spectral properties of the operators governing open quantum evolution. After these first steps, the field remained relatively quiet for many years and it is only over the last decade that the development of dissipative quantum chaos has received a strong boost, as confirmed by a large number of publications on this topic and, very recently, the first experiments performed to test its theoretical predictions. In this chapter, we review these recent developments and outline the basic foundations of dissipative quantum chaos.

We introduce a matrix product operator (MPO) encoding of the Magnus expansion and the Dyson series for one-dimensional quantum lattice models with time-dependent Hamiltonians. The MPO construction can be made accurate up to arbitrary order in the time step, it can be applied to both finite and infinite systems, and it can handle long-range interactions. The resulting MPO can be combined with state-of-the-art time evolution algorithms based on matrix product states, allowing for drastic improvements in simulating evolution under time-dependent Hamiltonians. Our MPO construction can also be used for the optimization of quantum circuits in the context of quantum simulation of time-dependent Hamiltonians.

We propose a realizable experiment to test the response of a particle detector prepared in a superposition of locations interacting with a relativistic quantum field. Using a beamsplitter to prepare two superposed branches of a modulated laser probe, these branches are directed to intersect a pancake-shaped Bose-Einstein condensate at two separate locations. The branches are then recombined with another beamsplitter. Heterodyning one of the outputs, the response function corresponding to an Unruh-deWitt detector in a superposition of locations interacting with a (2+1)-dimensional massless scalar field is shown to appear in the difference photocurrent power spectrum. Operating beyond the standard quantum limit using squeezed light, we estimate the signal-to-noise ratio $SNR\gtrsim 10$ for extracting the response function over a broad set of baseband frequencies.

Whether intermediate-mass black holes reside in nearby star clusters has remained contested for decades. We address this question by training neural network and random forest regressors on synthetic catalogs generated with the {\sc Rapster} cluster evolution code, mapping observable cluster properties such as total mass and half-mass radius onto the mass of the heaviest black hole built up through repeated mergers. Applying these models to nearby globular and nuclear star clusters, we forecast the intermediate-mass black hole population that each system may host. Globular clusters are unlikely to contain black holes more massive than $\sim 100\,M_\odot$, with an occupation fraction near 0.02, although they can produce remnants within the upper mass gap with masses approaching $100\,M_\odot$. Among nuclear star clusters, a handful of cases, including NGC 5102 and NGC 5206, yield predicted central black hole masses above $100\,M_\odot$, which we contrast with kinematically inferred estimates. Where the observationally claimed masses exceed our predictions, the implication is that the assembly history involved processes beyond hierarchical mergers, most plausibly accretion of gas and stars. Finally, we employ a normalizing flow to quantify, for individual globular clusters, the likelihood that their initial conditions were favorable to a collisional runaway during the first few million years after formation.

We study algebraic locality principles on a 2+1D closed lattice in the presence of a Gauss law for a non-invertible symmetry. Prior work in arXiv:2509.03589 showed that when enforcing the Gauss law of an invertible symmetry, the principle of "Haag duality" is preserved exactly, and "disjoint additivity" is preserved after appropriate treatment of discreteness artifacts. Here we show that for a large class of non-invertible on-site symmetries, Haag duality is preserved exactly only for sufficiently nice, "cuspless" regions. For cusped regions, we instead have a weak form of Haag duality that requires adding a collar. Our results apply to double models with a purely magnetic constraint, and to the more general framework of constraints induced by the on-site action of a Hopf algebra. In particular, we treat a class of extended string-net models explicitly. We also demonstrate disjoint additivity for double models based on a group, and a weakened form of disjoint additivity in the setting of a general Hopf algebra.

We initiate the study of gravitational-wave lensing in the wave-optics regime within modified gravity. We consider a phenomenological setup in which the gravitational-wave amplitude obeys a curvature-coupled propagation equation. This framework reproduces the standard GR behaviour in the geometric-optics regime, while leading to qualitatively different infrared dynamics. In particular, the usual argument implying that the amplification factor approaches unity in the zero-frequency limit no longer applies. This is due to the persistence of curvature-induced interactions in the infrared, which modify the natural propagation basis itself. As a result, the standard Fresnel treatment ceases to be valid at sufficiently low frequency. The correct infrared regime is instead controlled by an interacting static Green function, with a finite-frequency completion provided by a partial-wave formulation. We show that this structure admits an equivalent distorted-wave interpretation, in which the curvature interaction is absorbed into a dressed reference propagation basis, while the residual lensing effect is encoded in finite-frequency phase shifts. We further demonstrate that these phenomena admit a natural interpretation in the language of scattering amplitudes. Wave-optics lensing can therefore probe propagation-level departures from GR that remain entirely invisible in geometric optics.

A rapid estimate of gravitational-wave (GW) detectability associated with astronomical transients is crucial for optimizing multi-messenger follow-up strategies and for constraining the physical origin of the transient itself. We introduce here the Targeted Detectability Range (TDR), designed to evaluate with minimal computational effort the detectability of compact binary coalescences under the hypothesis of association with an external messenger, such as an electromagnetic or neutrino signal. Unlike the standard GW range, which is based on averaged source parameters, the TDR incorporates prior information from observations of the external messenger, including sky localization, inclination constraints, and physically motivated bounds on component masses. We report the detectability range of all gamma-ray bursts, short and long duration, observed during the first three observing runs of the LIGO-Virgo-KAGRA collaboration. The method is validated by performing a systematic comparison with the 90$\%$ exclusion distances provided by modeled targeted GW searches.

In this work, we delve into the physics of charged black holes modified by Weyl corrections, a framework that emerges from the subtle non--minimal coupling between spacetime curvature and electromagnetism. We begin by revisiting the thermodynamics of these cases, where we derive the Hawking temperature, entropy, and heat capacity to see how the Weyl correction parameter reshapes the landscape of thermal stability and phase transitions. Then, we apply the winding number method to classify the thermodynamic states of the system from a topological perspective and show the effect of the Weyl modifications on the universal classification of the Wey--corrected black hole. Moving beyond pure theory and into the realm of astrophysics, we study the motion of massless particles affected by the Weyl correction for the two photon polarization, and by exploring the shadow, we find constraints of the black hole parameters. Also, we study the null trajectories for the two photon polarization of the Weyl--corrected black hole. Finally, we model the accretion disk around these black holes. By calculating the energy flux, spectral luminosity, and differential luminosity, we show how these corrections leave a detectable trace on the light we might observe.

Standard quantum inference converts quantum data into classical outputs. We study an alternative inference setting in which the desired output is quantum, preserving coherence. Such settings include quantum purity amplification (QPA), mixed-state approximate purification or cloning, and density matrix exponentiation. We show that such protocols can achieve exponentially lower sample complexity than incoherent, measurement-mediated protocols. For QPA with principal eigenstate targets and $d$-dimensional inputs, coherent processing achieves error $\varepsilon$ using $O(1/\varepsilon)$ copies, versus the $Ω(d/\varepsilon)$ copies required by any incoherent protocol. Together, these sharp coherent-incoherent separations seed a theory of coherent quantum inference, with an entanglement-breaking limit identifying the optimal incoherent counterpart of each coherent protocol.

Quantum purity amplification (QPA) is the task of coherently transforming $n$ copies of a mixed state into high-fidelity copies of a chosen eigenstate. We solve QPA in the general setting of $n$ input copies, $m$ output copies, arbitrary target eigenstates, arbitrary local dimension $d$, and generic input spectra. We characterize the optimal channel and derive its all-site and one-site performance laws across output regimes. For the asymptotic analysis, we use a path-graph parametrization to show that, when the target eigenvalue has a constant spectral gap $D_{k,\mathrm{min}}$, achieving all-site error $\varepsilon$ requires a number of input copies independent of $d$ and scaling as $O(m/(\varepsilon D_{k,\mathrm{min}}^2))$. When $m/n$ approaches a constant, the performance exhibits phase-like regimes, which we characterize explicitly. For the nonasymptotic analysis, we develop a theory of generalized Young diagrams that yields tight sample complexity bounds and provides the first dimension-uniform guarantee for optimal QPA. We also provide asymptotically efficient implementations of the optimal protocol. Together, these results establish QPA as a rigorous example of coherent quantum information processing with dimension-uniform sample complexity, supplying the technical foundation for the coherent-incoherent separation developed in the companion work.

Hybrid tensor networks offer a promising route to enhance the expressivity of classical tensor network methods by incorporating quantum states prepared on a quantum computer. Existing approaches are limited by the variational optimization of the quantum component of the tensor network. In this work, we introduce an alternative strategy that combines a non-parametric quantum state prepared through quantum annealing and a classical isometric tensor network. The latter is variationally optimized while the former is used as a fixed, boundary tensor resource in the form of classical shadows. We demonstrate the feasibility of this approach through extensive numerical simulations on the transverse-field Ising model, showing that the optimization procedure remains robust under statistical and hardware noise. Moreover, our results indicate that our newly proposed setup improves the accuracy of the obtained ground state approximation compared to the original quantum simulation, without increasing the depth of the applied quantum circuits. Therefore, this setup offers a practical route to scale variational quantum algorithms towards the quantum utility scale.

We develop a physics-facing version of the persistence/transition-variety framework for scalar-field cosmology, tailored to inflationary dynamics. The guiding idea is that observationally viable inflationary models are often best understood not as single asymptotic phases but as concatenations of persistent regimes separated by universal transition episodes. In this picture, slow roll appears as a robust persistent balance, ultra-slow roll as a bottleneck passage near a nonhyperbolic organising set, and oscillatory post-inflationary behaviour as a recurrent exit sector. Using the exponential model as a reference regime atlas and the massive case as a dynamical realisation of slope drift, we show how such histories may be organised and read geometrically. The resulting framework makes explicit that the relevant regime transitions are organised precisely where hyperbolicity is lost or the spectrum crosses the imaginary axis, and are therefore invisible to a purely hyperbolic or asymptotic treatment.

Quantum computing has demonstrated its significant advantage over supercomputing for specific applications and shown promising prospect, such as machine learning, cryptography, finance, etc.. Quantum oracles are very common in many quantum algorithms and oracle resource consumption directly affects algorithm performance. However, existing oracle designs often exhibit high resource overhead and limited compatibility. Moreover, structured description tools and complexity analysis methods are lacked. In this work, we introduces a Hierarchical Recursive Synthesis-Evaluation (HRSE) model, enabling formal description and precise quantum gate complexity analysis of oracles. Based on this model, we propose an Adaptive Space-depth Trade-off (ASDT) algorithm for generating oracle structures under a fixed qubit constraint. We provide a theoretical proof showing that the ASDT algorithm achieves the optimal gate count for a given number of qubits. Experimental results show that the ASDT algorithm reduces the average quantum circuit depth by 53.99% compared with the W-cycle approach, with the number of variables being 10, 15, and 20, respectively.

This thesis investigates compact astrophysical objects within modified theories of gravity, focusing on neutron stars and strange stars. The work studies their internal structure, equilibrium, and stability in gravitational frameworks based on torsion and nonmetricity, which provide the foundation for theories such as \(f(Q)\) and \(f(T)\) gravity. Charged isotropic compact star models are constructed in \(f(Q)\) gravity using conformal symmetry and the MIT Bag equation of state, with matching to the Bardeen exterior spacetime. Gravitational decoupling techniques, including minimal and complete geometric deformation methods, are employed in \(f(T)\) gravity to generate anisotropic strange star models. These approaches enable the inclusion of additional gravitational sources, dark matter effects, and spacetime deformations. Exact analytical solutions are obtained under suitable physical conditions such as regularity and vanishing complexity. The models are examined using energy conditions, causality constraints, the generalized Tolman--Oppenheimer--Volkoff equation, and Herrera's cracking criterion to ensure physical viability and stability. The influence of modified gravity parameters on stellar mass, radius, compactness, and stability is analyzed in detail. A Bayesian statistical framework is applied to constrain model parameters using observational data, including NICER mass--radius measurements. Bayes factor analysis is further used to identify viable gravitational extensions consistent with astrophysical observations. The results show that modified gravity can significantly affect the maximum mass, radius, and stability of compact stars while remaining compatible with observations. This work provides a systematic theoretical and observational study of compact stars beyond general relativity.

We develop an optimization framework for high-efficiency quantum cycles implemented with a trapped Bose-Einstein condensate, whose control parameters are the trap stiffness and the interaction strength tuned via a Feshbach resonance. Optimal driving protocols for each stroke of the cycle are obtained from a variational description of the condensate dynamics combined with Nelson's stochastic quantization, which maps the quantum evolution onto an effective Ornstein-Uhlenbeck process. The optimal protocol is obtained by minimizing a user-defined cost functional that selects the best trade-off between protocol duration and arbitrary physical constraints (such as the expended work or the proximity to an adiabatic evolution), and exhibits remarkable stability over repeated cycles. The method also provides a systematic route to optimal control for generic nonlinear Schrödinger equations, paving the way to optimal control strategies in fields as diverse as nonlinear optics, quantum fluids, and quantum plasmas.

All standard formulations of relativistic dissipative hydrodynamics, from Eckart through Israel-Stewart to the recent BDNK framework, assume that the viscous stress depends on the shear tensor $σ_{αβ}$ and the expansion scalar $θ$ but not on the vorticity $ω_{αβ}$ or the acceleration $a_α$. We derive this structure from a Lagrangian kinematic construction on Lorentzian spacetimes, extending a recent result on Riemannian manifolds. The spatial strain rate, constructed from the rate of change of spatial inner products of Lie-dragged connecting vectors, is the spatially projected Lie derivative of the projected metric $h_{αβ} = g_{αβ} + u_αu_β$. The acceleration terms drop out exactly under spatial projection, and the vorticity cancels by symmetry. We show that material frame-indifference fails for generic Killing perturbations by an amount $δ\mathfrak{h}_{αβ} = +ε(ξ_αa_β+ ξ_βa_α)$ proportional to the acceleration, and is restored only for flow-preserving isometries. We prove that the non-relativistic limit of the BDNK equations gives the deformation Laplacian universally in the viscous sector, with the BDNK parameter dependence identified by Hegade K R, Ripley, and Yunes arising entirely from the thermal (heat-flux) sector. As an application, we derive the Weinberg gravitational-wave damping formula directly from the kinematic strain rate in a perturbed FRW spacetime.

We study a family of Jacobi operators in which the diagonal entries are multiplied by a coupling parameter $λ\geq0$. Under suitable conditions, the operator is self-adjoint for every $λ>0$, while the formal limit at $λ=0$ is a symmetric Jacobi operator admitting a one-parameter family of self-adjoint extensions. A central ingredient of our analysis is the derivation of uniform bounds for square-summable generalized eigenvectors in the small-$λ$ regime, which combines discrete WKB methods with Airy-function asymptotics. Using these estimates, we analyze the limiting behavior $λ\to0$ in the strong resolvent sense, proving that for every sequence $λ_j\to0$ one can extract a subsequence along which the corresponding Jacobi operators converge to some self-adjoint extension of the limiting operator; conversely, every such extension can be obtained in this way. We call this behavior an essentially singular limit, by analogy with essential singularities in complex analysis. As an application, we study higher-order squeezing operators arising in quantum optics. Using the connection with Jacobi operators, we show that when the relative strength of the free-field term tends to zero, different self-adjoint extensions of the squeezing operator are selected along different sequences. In particular, this limit does not single out a physically distinguished self-adjoint extension, but instead identifies a distinguished subclass of extensions compatible with the underlying symmetry.

Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and under noiseless conditions, coherent processing of quantum data outperforms fixed-measurement schemes followed by classical processing. It remained uncertain whether this performance gap persists at a finite scale, and in the presence of noise that is unavoidable with current quantum devices. In this work, we present simulations and analysis of the performance of existing hardware on a learning problem known to exhibit asymptotic advantage, now subjected to noisy quantum data. Comparing coherent quantum processing directly against fixed-measurement schemes, our results demonstrate a clear performance separation at a scale of just 30 to 40 noisy qubits. Already at this scale, the fundamental bottleneck is no longer classical computation but data acquisition; matching the noisy coherent protocol with measure-first strategies would still require months or even years of measurements. By systematically evaluating hardware constraints such as state preparation, gate errors, readout errors, connectivity, and coherence times, we provide evidence that a demonstration of such a strong learning advantage is accessible on near-term devices.

Given a pair of isolated devices that accept random binary inputs and return binary outputs, a user can deduce from the observed data alone if the underlying mechanism can be explained classically. Bell's theorem further states that a classical explanation can be ruled out if the devices perform certain measurements on an entangled quantum state, underpinning the security of cryptographic protocols that are device-independent (DI). For certain protocols, such as those performed in a tight space, it might be difficult to perfectly enforce the non-signaling assumption required in Bell's theorem. This prompts the question: is quantum nonlocality robust to such imperfections? We show that if a binary channel sends a noisy copy of one party's input to the other before any measurements take place, the answer is yes. We completely characterize the vertices and facets of the local polytope in this scenario, and identify Bell inequalities that certify non-signaling quantum correlations. This is possible even when a near perfect copy of the input is sent. We go on to show that the identified inequalities are more robust to depolarizing noise than the Clauser-Horne-Shimony-Holt inequality when certifying DI randomness in this scenario. In addition, we characterize the local polytope when both parties receive a noisy copy of each other's input and make similar conclusions, leaving many new potential Bell inequalities to be explored.

Contemporary quantum computing platforms remain, in essence, programmable physical systems whose control is typically mediated through unitary gate abstractions. While such abstractions provide a uniform interface, they obscure important aspects of the underlying hardware and may limit the exploitation of its full capabilities. Direct operation at the control-pulse level offers a more expressive and physically faithful paradigm, enabling, for instance, the implementation of tailored error-mitigation and optimisation strategies. However, this increased expressivity comes at the cost of greater quantum software development complexity, necessitating structured and accessible tooling. We present a software framework, integrated within the QML-Essentials package, that extends quantum machine learning (QML) methodologies to encompass pulse-level modelling. By embedding quantum optimal control techniques within a QML setting, our approach enables the seamless combination of gate-based and pulse-level representations. The framework provides a comprehensive suite of modelling and analytical capabilities. In particular, we introduce composable ansatz constructions based on interchangeable building blocks, and support for end-to-end optimisation of pulse parameters. Motivated by the central role of quantum Fourier models, we further incorporate a range of Fourier-analytic diagnostics, complemented by extended measures of entanglement. All performance-critical components are implemented in a high-performance environment using JAX and supported by a dedicated quantum simulator. Taken together, the framework facilitates reproducible and systematic investigations, while bridging the conceptual and practical divide between abstract circuit models and hardware-aware optimisation. It provides a robust foundation for future developments at the intersection of QML and quantum control.

We report on a performance comparison between physical and logical computations on a prototypical machine-learning application: solving differential equations using quantum kernel methods. The algorithm is implemented on an atom-based logical quantum processor, both at the physical and logical levels. We show that the kernel estimated from the logical implementation performs better than its physical counterpart on relevant metrics. We observe how such performance improvement can be traced back to specific noise-induced errors detected by the chosen encoding. We apply the computed quantum kernel to the task of solving differential equations, confirming how the superior performance of a logical quantum kernel is retained also at an end-to-end applicative level. Our findings show that experimental validation of end-to-end protocols can already highlight the positive impact of fault-tolerant implementations despite their higher quantum resource count, and guide application-informed architectural choices.

While algebraic derivations establish theoretical limits for quantum cloning, practical implementations require explicit operator representations that are often unavailable analytically. We present a computational framework that reformulates cloning optimization as a search over completely positive trace-preserving maps using the Choi-Jamiolkowski isomorphism and Semidefinite Programming. The framework (i) numerically certifies global optimality through primal-dual strong duality and (ii) automatically extracts operational Kraus operators from the optimal Choi matrix via spectral decomposition. We systematically treat universal, phase-covariant, asymmetric, and entanglement cloning scenarios, providing -for the first time - a unified computational catalogue of explicit, implementable Kraus representations across all major cloning families, including higher-order processes and arbitrary input state distributions. As an application, we analyse optimal cloning attacks on BB84 under depolarizing noise, demonstrating how the extracted operators enable quantitative security analysis in realistic noisy quantum channels. An open-source implementation enables community validation and extension.

Trapped ions excited to high-lying electronic states combine strongly coupled collective vibrational and electronic degrees of freedom with long-ranged interparticle interactions. These ingredients enable the quantum simulation of biochemical processes, associated with the dynamics of excitons in non-perturbative parameter regimes. The key feature of such a quantum simulator are electronic-state-dependent molecular potential surfaces which can be strongly coupled. This allows to shed light on a variety of mechanisms underlying exciton transport. We illustrate this in a system of three trapped ions, which is amenable to an ab initio treatment. Given that ion traps can be routinely prepared with hundreds of ions, these quantum simulators can immediately realise scenarios which are inaccessible by current numerical methods.

Entanglement does not in general imply Einstein-Podolsky-Rosen steering. We identify a boundary-geometric mechanism that closes this gap on product-null boundary strata of two-qubit state space, where Bob's conditional states touch the boundary of the Bloch ball. The key obstruction is local: if a projective assemblage approaches a Bloch-sphere boundary contact with a first-order tangential displacement but only a second-order inward defect, then no finite-measure local-hidden-state model can reproduce it. For two-qubit states with a product vector in the kernel, this boundary contact is exactly the tangency of Bob's steering ellipsoid to the Bloch sphere. At such a product-null tangency, a single tangential coherence controls both partial-transpose negativity and the boundary-contact scaling obstruction. The same boundary minor gives a compact experimental witness: once the product-null contact is verified or guaranteed, the tangential coherence supplies the steering signal. Consequently, every entangled two-qubit rank-two state, and every entangled rank-three state whose null space is spanned by a product vector, is two-way projectively steerable. The same boundary idea extends to arbitrary steering cuts: the Bloch-sphere contact is replaced by a rank-deficient trusted conditional state, and support-kernel first-order coherence implies both NPT entanglement and projective steering.

It is shown how to obtain state vectors associated with measurements on the separated subystems of an entangled state, revealing how a single wavefunction encodes a set of statistical measurement outcomes. The result explains why measurements on the subsystems give definite outcomes and why measurements on one subsystem are correlated with those on the other. It is therefore concluded that the theory of quantum mechanics, without nonlinearities or \emph{ad hoc} assertions, can explain both the mechanism of state vector collapse and the reason for the paradoxical nonlocal correlations between separated subsystems.The theory also explains how quantum correlations, including correlations that violate Bell's inequality, are read out by classical measurements.

Using one-dimensional simulations analyzed through the lens of open quantum systems, we study the photoelectron's strong-field dynamics from an atom surrounded by a scattering environment stochastically structured. We theoretically investigate high-order harmonic generation from this situation. We show that local dephasing of the photoelectron wavepacket induced by elastic scattering leads to global decoherence. This drives a transition from quantum to classical behavior, as witnessed by the photoelectron probability density localizing around specific trajectories of the classical analog system: unstable periodic orbits. This phenomenon mirrors quantum scars traditionally observed in the eigenfunctions of time-independent systems, such as quantum billiards. Here, it emerges in-situ within a time-dependent framework, manifesting directly in the real-time dynamics from the ground state rather than solely through spectral analysis.

Quantum criticality is a resource for quantum-enhanced metrology, but existing schemes face intrinsic limitations. These arise because using criticality directly in the encoding dynamics restricts the accessible parameters to those explicitly supported by the critical Hamiltonian, and the requirement for critical conditions narrows the effective estimation range. To solve this, we introduce a general framework termed criticality-assisted noncommutative preparation (CANP). In this approach, critical evolution is employed as a state-preparation resource. We establish the underlying algebraic conditions and show that the intrinsic noncommutativity between the preparation and encoding operations leads to a genuine enhancement of the quantum Fisher information (QFI). Remarkably, this enhancement may be achieved at fixed total sensing time and energy cost. The effect is quantified by the Wigner-Yanase skew information, which measures noncommutativity and exhibits the same critical scaling as the QFI. We demonstrate effective use of CANP in the quantum Rabi and Lipkin-Meshkov-Glick models. Our results establish CANP as a robust technique to effectively implement criticality-enhanced quantum metrology.

In this work, we present quantum reinforcement learning (RL) as a solution strategy for process synthesis problems. Building on our prior work, we develop a generalized framework that formally poses process synthesis as a Markov decision process and introduces quantum-enhanced RL algorithms to solve it with improved scalability. Earlier implementations of quantum-based RL for process synthesis were limited by qubit requirements, which scaled poorly with problem complexity. This work overcomes this challenge by introducing state encoding algorithms to decouple qubit requirements from problem size. A classical RL-based solution strategy is used as a baseline to benchmark the quantum algorithms under identical training conditions. All algorithms are evaluated across a flowsheet synthesis problem of increasing unit counts to analyze their performance and scalability. Results show that all approaches are capable of identifying the optimal flowsheet designs in small design spaces. For moderate-scale unit counts, quantum approaches demonstrate competitive performance on a per-episode basis and improved efficiency on a per-parameter basis versus the classical RL benchmark. This work provides a foundation for future quantum computing applications within process systems engineering, establishes a controlled benchmark for comparing classical and quantum algorithms, and shows that the proposed quantum variants remain competitive for the process synthesis problem examined in this work.

Photodetection is usually treated in the frame in which the detector is at rest relative to the optical apparatus. We show that uniform motion of an electric Glauber detector changes the single-click POVM realized on two counterpropagating single-photon modes. Motion Doppler-shifts the alternatives in the detector frame; finite bandwidth then converts propagation direction into a detection bias without decohering the photon. For a Lorentzian response near one Doppler branch, the readout crosses from phase-sensitive to direction-sensitive with a quality-factor-enhanced onset. Finite-time integration adds Doppler-beat visibility loss, separating passive covariance from measurement change.

There is a growing consensus that large-scale, fault-tolerant quantum computing (FTQC) necessitates high-fidelity photonic interconnects to overcome the scaling limits of monolithic architectures. However, most current platforms were not originally designed for native photonic connectivity and require significant engineering overhead. To overcome these fundamental hardware limitations, we recently introduced a rationally designed organic molecule that serves as an ideal quantum node, featuring a robust qubit-photon interface (QPI) and a long-lived nuclear-spin register. In this work, we present PIQC (Photonic Integrated Quantum Circuits), a distributed architecture designed to scale these molecular nodes into a functional quantum computer. The PIQC framework integrates five mutually reinforcing innovations: (i) Designer molecular qubits, i.e. carbene molecules in an isosteric host that provide millisecond-coherence electron spins with high spectral stability and spin-dependent optical emission, (ii) deterministic nuclear registers made of synthetically placed $^{13}$C or $^{14}$N labels that enable fast ($\sim 1~μ$s), high-fidelity electron-nuclear gates, (iii) hybrid photonic integration, which allows molecular films to seamlessly integrate with existing mature fabrication technologies, e.g. thin-film lithium niobate (TFLN), (iv) heralded entanglement protocols that can tolerate up to 70% photon loss, and (v) stairway Floquetification, i.e. high-rate quantum low-density parity-check (qLDPC) codes that are converted into Floquet codes, reducing syndrome extraction to weight-two Bell-pair measurements that match PIQC's networked hardware. PIQC offers a hardware-efficient, commercially viable pathway toward a utility-scale quantum computer based on distributed FTQC.

Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. This imbalance often biases supervised learners toward the legitimate class, leading to high overall accuracy but weaker fraud-class recall and F1-score. This paper introduces Q-SYNTH, a hybrid classical--quantum generative adversarial framework in which a parameterized quantum circuit serves as the generator and a classical neural network serves as the discriminator. Q-SYNTH is designed for minority-class fraud synthesis in tabular data and is evaluated along two dimensions: statistical fidelity to real fraud samples and downstream performance for fraud detection. To this end, generated samples are assessed using distributional similarity measures based on Kolmogorov-Smirnov statistics and Wasserstein distances, real-vs-synthetic detectability measured by AUC-ROC, and downstream classification performance across both quantum and classical classifiers. Under the reported protocol, Q-SYNTH reduces marginal distribution mismatch relative to a classical GAN baseline while maintaining competitive downstream fraud-detection performance. Although SMOTE achieves the strongest feature-wise similarity and the classical GAN attains the highest downstream performance in several settings, Q-SYNTH offers a favorable compromise between distributional fidelity and downstream performance, supporting the feasibility of hybrid quantum augmentation for imbalanced fraud detection.

Practical quantum key distribution (QKD) systems operate under noise, but security of most protocols have been analyzed under ideal noiseless scenarios. In this work, we investigated security performance of BB84 protocol under effect of collective rotation noise. Using theoretical quantum information frameworks, we analyzed key security parameters including quantum bit error rate (QBER), mutual information and secret key rate (SKR). Security of protocol is studied under various eavesdropping scenarios based on intercept and resend attacks. Our results show that collective rotation noise has a significant impact on the information shared between the two parties. Particularly, we extended prior treatments by suggesting a noise engineering strategy where we identified a non-zero noise range where information accessed by Eve is minimized while corresponding SKR degradation remains relatively small. This analysis provide insights into robustness of BB84 protocol under realistic noisy channels and may contribute towards development of more resilient QKD systems.

The Earth-Moon tide is classically explained by the Newtonian quadrupolar tidal tensor. In its principal frame, this tensor gives the familiar 90-degree stretching-squeezing geometry and contains only the ordinary plus-type tidal channel. A projected acceleration can be evaluated along any direction, including the 45-degree direction, but this projection is not an independent cross-tidal residual. In this work, we propose a Halilsoy-inspired residual extension of the lunar tidal tensor. The motivation comes from Halilsoy's cross-polarized cylindrical gravitational waves, where an off-diagonal tidal sector naturally rotates the local tidal eigenframe. Using this relativistic mechanism as a guide, we introduce an alpha-dependent residual coefficient, chi_H(alpha,t,rho), representing a possible hidden off-diagonal tidal component beyond the diagonal Newtonian principal-frame tensor. The proposed residual does not destroy the ordinary 90-degree separation of the principal tidal axes. Instead, it rotates the whole eigenframe and produces a distinct 45-degree-type angular signature. This signature appears as an additional sin(2 beta) residual channel whose strongest directions are 45, 135, 225, and 315 degrees. The corresponding residual acceleration scale is controlled by chi_H. The model does not replace standard lunar tidal theory and does not identify the Earth-Moon system with a Halilsoy spacetime. Rather, it provides a testable residual ansatz: Newtonian gravity explains the dominant lunar tide, while the Halilsoy-inspired sector supplies an alpha-dependent off-diagonal cross channel that is absent from the diagonal Newtonian principal-frame description.

Some arguments are considered in favor of the idea that the canonical anticommutation relations for fermions should be modified in curved spacetime near the event horizon of a black hole. Such a modification is expected to lead to a change in the source term of the inhomogeneous Dirac equation describing the two-point Green's function. By introducing an {\it ad hoc} source into the Dirac equation that mimics the modification of these anticommutation relations, stationary solutions are obtained and interpreted as two-point Green's functions of fermions located near the event horizon. Owing to their stationarity, these Green's functions describe a fermion condensate near the event horizon.

We investigate a generalized entropic cosmology obtained by applying the gravity-thermodynamics conjecture to the Universe horizon using Kaniadakis statistics, namely a relativistic extension of the standard Boltzmann--Gibbs formalism. The resulting deformation of the horizon entropy naturally modifies the Friedmann dynamics and provides a phenomenologically consistent extension of the $Λ$CDM paradigm. Within this framework, we explore the implications of the modified cosmological dynamics for the physics of the early Universe, focusing in particular on primordial gravitational waves (PGWs) and slow-roll inflation in a Starobinsky-like scenario. We show that the generalized entropic corrections simultaneously affect the evolution of tensor perturbations and the inflationary slow-roll dynamics, inducing characteristic deviations in the PGW spectrum as well as nontrivial corrections to the main inflationary observables. By confronting the theoretical predictions with the latest Planck and BICEP/Keck observations, we derive stringent constraints on the Kaniadakis parameter and assess the observational viability of the model. Our results establish a direct connection between generalized horizon thermodynamics and inflationary cosmology, showing that quantum-statistical modifications of the entropy-area law can propagate into potentially observable signatures in the physics of the early Universe.

We investigate the gravitational field of an extended spherically symmetric body within the framework of Extended Relativity (ER), a Lorentz-covariant formulation of relativistic gravity on a Minkowski background. Using a relativistic superposition principle for retarded gravitational fields, we derive an explicit metric for an extended body by integrating the contributions of its mass elements. The resulting metric reproduces the standard gravitational time dilation of a point source and agrees with the classical tests of General Relativity in the appropriate limits. However, unlike the exact Newtonian shell theorem and the Schwarzschild exterior solution, the external field depends weakly on the internal mass distribution through higher-order corrections. These corrections decay rapidly with distance but become significant near compact objects. We analyze the corresponding admissible-velocity geometry, derive the motion equations for test particles, and compare the predictions of extended-body and point-source models. For neutron stars, the corrections noticeably modify the local light-velocity structure near the surface. For the Earth, the corrections are small but produce measurable differences in round-trip light travel times to the International Space Station. The formalism provides a transparent relativistic description of extended gravitational sources and offers a framework for studying relativistic corrections due to internal structure in strong-field and precision-measurement regimes.

In the theories, in which dynamic gravitational field emerges from the underlying matter fields, the gravitational field can be considered as a part of matter. Using this approach, we construct the thermodynamics of the homogeneous Universes -- the de Sitter Universe, the Bonnor-Melvin-$Λ$ Universe and the static Einstein Universe. It is demonstrated that although these three Universes have different types of matter fields (ordinary matter, magnetic field, gravitational field and vacuum energy), they have the same thermodynamic properties. Their energy densities obey the same equation, which contains the corresponding matter densities and the pairs of the thermodynamically conjugate variables. In Minkowski vacuum, where the ordinary matter and magnetic and gravitational fields are absent, this thermodynamic approach automatically leads to zero cosmological constant.

A modified gravitational model whose action is given by an arbitrary function of the Ricci scalar, the matter Lagrangian density, a scalar field, and its kinetic term is investigated as an extension of the gravitational sector including an additional dynamical degree of freedom. Within this framework, the causal structure of rotating cosmological solutions is analyzed by considering a cylindrically symmetric Pertov-type N space-times and an axially symmetric Petrov type-III with a cosmological constant as background geometries used as theoretical probes of the model consistency. In both cases, pure radiation as matter sources are examined, including a scalar-field configurations. We demonstrate that, although the considered space-times are exact solutions to the field equations of general relativity with a matter source, they are inconsistent within the modified gravity theory considered here.

We investigate the quantum properties of a nonlinear Kerr oscillator driven by a three-photon pump. We derive both exact and approximate analytical expressions for the ground state of this interacting model. The exact solution arises at an exact spectral degeneracy, while the approximate solution describes regimes of quasi-degeneracy of the energy spectrum. In both cases, the threefold (quasi)degenerate ground-state manifold consists of quantum superpositions of three macroscopically distinct states. These states differ qualitatively from conventional three-component Schrödinger's cat states due to the presence of squeezing with a distinctive parametric dependence. By varying the detuning between the oscillator and the three-photon pump, we show that the squeezing can be enhanced, suppressed, or even reversed, leading to a squeezing-to-anti-squeezing transition. We analyze the generation and stabilization of these superposition states, their robustness against perturbations and analytically quantify the leakage to excited states. Our analysis elucidates how the three-photon Kerr parametric oscillator can be used to encode a Kerr-cat qutrit protected against phase-flip errors.

We identify anomalous scale-free localization and the associated impurity-induced loss bursts in a non-Hermitian dissipative cross-stitch lattice. By a local basis rotation, the model is mapped onto an effective non-Hermitian Su-Schrieffer-Heeger lattice, where local impurities act as tunable effective boundaries. For the parameter choice considered here, tuning the impurity strength $η$ connects two effective open-boundary-condition-like limits, reached for $η\to0$ and $η\to\infty$, through generalized-boundary-condition regimes and the impurity-free periodic-boundary-condition point at $η=1$. For finite $η\notin\{0,1\}$, the spectral loops remain separated from the real-energy axis, while the eigenstates exhibit scale-free localization pinned by the impurity. Unlike conventional impurity-induced scale-free localization, the Lyapunov exponent depends explicitly on the eigenenergy, making the localization strength eigenstate dependent. We further show that this anomalous eigenmode structure produces an impurity-induced loss burst: the long-time integrated dissipation probability is strongly enhanced near an impurity-generated effective boundary even when the initial wave packet is far away. In the single-impurity case, the burst region consists of the impurity site and its adjacent effective-boundary site, and the effect occurs without imaginary-gap closing. For multiple impurities, local burst regions emerge around all impurities, while the dominant burst boundary is selected by the initial wave-packet position and the nonreciprocal drift direction. These results connect anomalous scale-free localization with controllable dissipation dynamics in non-Hermitian lattices.

We investigate entanglement-based quantum key distribution protocols, with particular emphasis on their efficiency under realistic conditions of satellite quantum communications, where performance is limited by the low power of a received signal and background radiation. We focus on scenarios where each photon pair is used to encode multiple qubits in order to optimally utilize the weak signal. By optimizing over the source intensity and the number of encoded qubits we study the theoretical information limit for the QKD efficiency. We show that the optimal efficiency is attained for finite entangled photons pair production probability which is in contrast to conventional communication efficiency maximized in the limit of vanishing signal strength. The multiqubit encoding can enhance the secret key rate by up to an order of magnitude compared to single-qubit schemes.

This study explores asymptotically flat wormhole solutions in $f(Q,T)=αQ+ βT$ gravity, expanding upon our prior work (arXiv:2602.00527v1) with matter Lagrangian density, $L_m=-P$ . Here, we examine the implications of employing $Lm=-T$ and $L_m=ρ$. The field equations, derived via action variation, share a common general structure but are fundamentally dictated by the parameters $α$ and $β$ through the coefficients $A_i$. Solutions with linear and asymptotically linear equation of state are explored. We conclude that non-exotic asymptotically flat wormhole solutions exist for all considered matter Lagrangian densities. A key outcome is the demonstration that different $L_m$ choices enable the same shape function to be supported by varied fluid configurations, or vice versa, identical fluids to yield different geometries. The energy conditions and physical characteristics of these solutions are shown to be distinct and critically dependent on the selected $L_m$.

This paper explores quantum heat engines based on qubit and qutrit working media interacting with thermal environments through generalized amplitude damping (GAD) channels. We investigate how quantum channels can be employed to model heat absorption, dissipation, and work extraction in open quantum thermal machines, and derive the conditions required for positive work extraction. The effects of quantum correlations, emission probability, population redistribution, and system--environment interactions on the thermodynamic performance of the engine are systematically analyzed across different operational regimes. In addition, we examine the ergotropy of qubit and qutrit systems under dissipative dynamics to understand how environmental effects influence the maximum extractable work. Our results demonstrate that multilevel quantum systems exhibit enhanced work extraction capability and improved robustness against decoherence compared to two-level systems, providing further insight into the role of dissipative dynamics and quantum resources in realistic quantum thermodynamic devices.

Distilling high-dimensional quantum entanglement under realistic, general asymmetric noise remains a formidable challenge. Standard entanglement purification protocols inevitably fail to satisfy convergence constraints under severe asymmetric noise. In this paper, we investigate carrier-assisted entanglement purification protocols, namely CAEPP and mCAEPP, for two-qutrit systems, demonstrating that without adaptive pre-processing, convergence is strictly bottlenecked by marginal $X$-error probabilities. To overcome this limitation, we introduce a deterministic pre-processing scheme based on mutually unbiased bases (MUBs). By actively rotating the qutrit phase space to establish primary-axis error dominance, we rigorously prove that the MUB-adapted mCAEPP deterministically yields unit asymptotic fidelity for any two-qutrit Pauli channel with initial fidelity $p_{00} > 1/3$.

Understanding how symmetry constrains dissipative relaxation in open quantum many-body systems remains a central challenge in nonequilibrium physics. Here we uncover a symmetry-selective Liouvillian mechanism that protects an isolated fast-decay channel in a long-range XXZ spin chain subject to dephasing noise. At the \(SU(2)\)-symmetric point, highly symmetric initial states couple exclusively to an exact Liouvillian eigenmode with decay rate \(λ=-2\), producing universal exponential relaxation independent of system size and interaction range. Breaking the symmetry restores overlap with slow Liouvillian modes and substantially suppresses the relaxation dynamics. This symmetry-filtered mode accessibility naturally gives rise to a strong quantum Mpemba effect, where a state farther from the steady state relaxes anomalously faster than closer thermal states. Our results establish symmetry-protected fast relaxation as a mechanism for controlling nonequilibrium pathways in open quantum systems.

We explore the symmetry properties of Stinespring dilations of single-qubit Pauli channels, addressing both the generic case and the specific examples of phase damping and depolarizing channels. For each scenario, we derive the representation of the Pauli group acting on the Hilbert space of the environment. We then focus on dilations that are continuous in time and driven by a time-independent Hamiltonian, and on collision models that generate a Pauli dynamical semigroup in the limit of fast collisions. First, we complement some recent general results on these types of dilations (M. Cattaneo, Phys. Rev. A 111, 022209 (2025)) with some additions and clarifications, including the case of covariant channels with strongly conserved quantities. Next, we show that the covariance property of Pauli channels impose strong constraints on both the dilation Hamiltonian and the initial state of the environment, and demonstrate how these constraints can be exploited to explicitly construct the time-dependent dilations in all considered cases. Our results are relevant for the quantum simulation of Pauli channels via unitary dilations and of Pauli semigroups via collision models, both in the laboratory and on quantum computers.

Optomechanical systems provide a versatile platform for precision measurements and investigations of fundamental physics, where bringing macroscopic resonators into the quantum regime is a widely pursued goal. Achieving such quantum behavior of solid-state mechanical resonators at room temperature would greatly broaden their applications by removing the need for cryogenic environments. Reaching this goal requires efficient cooling of mechanical motion, among various laser cooling methods, dynamical backaction cooling (DBC) is widely utilized in experiments but fundamentally limited when operating in the sideband-unresolved regime. Coherent feedback cooling (CFC) can overcome this limitation, while avoiding state collapse and the electronic restrictions inherent to measurement-based feedback. Here, we experimentally demonstrate CFC using an ultracoherent density phononic crystal membrane. By combining CFC with strong DBC in a relatively narrow cavity, we achieve a phonon occupation reduction from $5.5\times10^{6}$ to $166\pm7$, corresponding to a cooling factor of $3.3\times10^{4}$ at room temperature, even with current experimental limitations. Our results show the potential of CFC for approaching the ground state of high-$Q$ membranes at room temperature.

We propose a high-precision phase estimation scheme in a hybrid interferometer by synergistically combining a Kerr nonlinear phase shifter and multi-photon subtraction operations. Using a coherent state and a vacuum state as input resources, we systematically evaluate the phase sensitivity via homodyne detection and analyze the quantum Fisher information as well as the quantum Cramér-Rao bound under both ideal and lossy conditions. Our results show that the joint integration of Kerr nonlinearity and multi-photon subtraction yields remarkable advantages over either technique used alone. The proposed scheme enables the phase sensitivity to surpass the standard quantum limit, exceed the conventional Heisenberg scaling ($1/N$), and approach the super-Heisenberg scaling ($1/N^{2}$)-a direct consequence of Kerr nonlinearity. More precisely, the super-Heisenberg scaling $\propto $ $1/N^{2}$ is the ultimate precision limit permitted by the $k=2$ Kerr nonlinearity and does not violate the fundamental Heisenberg limit for linear phase accumulation. Even under moderate internal photon loss, the system maintains high precision and exhibits enhanced robustness to decoherence. The Kerr nonlinearity introduces an intensity-dependent phase shift proportional to the squared photon number, while multi-photon subtraction tailors non-Gaussian states to strengthen phase information extraction. Compared with existing schemes based on hybrid interferometers or SU(1,1) interferometers, our architecture achieves superior precision and stronger loss resilience. All components are experimentally accessible with current quantum optical technologies. This work provides a promising route for practical high-precision quantum metrology and quantum sensing.

Numerical-relativity simulations with non-trivial matter configurations require initial data that satisfy the Hamiltonian and momentum constraints of the Einstein equations. We construct constraint-satisfying scalar-field initial data using the eXtended Conformally Flat Condition (XCFC) formalism, in which the matter variables are conformally rescaled and an auxiliary vector field is introduced. In doing so, we overcome the issues of local uniqueness and convergence of the solutions that arise in the second-order elliptic equations associated with the constraints. Using an iterative solver method, we demonstrate the convergence of the XCFC approach to a solution for several scalar-field matter systems. Those include Gaussian-like profiles, topological torus configurations, and equal-mass boson star binaries. In particular, for the latter case, it is common to employ the superposition of two isolated boson star solutions in order to build the initial data. We show that our formalism significantly improves upon a superposition approach by generating genuinely constraint-satisfying initial data for boson star binaries.

Time synchronization is a crucial requirement in quantum key distribution (QKD)8 protocols, ensuring accurate key generation via the correct assignment of bits of raw key and9 enabling eavesdropping detection via the precise recording of photon statistics. State-of-the-art10 experiments typically use an extra channel to synchronize the clocks of the transmitter and receiver11 via classical signals. In this work, we study the possibility of performing clock synchronization12 via the signals used for the key generation, which are already present in decoy-state-based BB8413 protocols.14 Without altering the protocol in any way, we use the different mean photon numbers of the15 signal and decoy states for time synchronization without a dedicated physical channel capable of16 clock synchronization. The proposed method relies only on the photons sent and received for17 key generation and does not require any change to the QKD protocol. The only change in the18 experiment is on the software level, thus making it very simple to implement.19 We demonstrate clock synchronization method in a simulation of a specific fiber-based QKD20 experiment. Like other decoy-state-based BB84 protocols, it is based on weak coherent pulses.21 In this simulation, we investigate the parameter space to find limits and optimal choices of our22 proposed method.23 In addition to the non-protocol-altering clock synchronization method, we also discuss an24 approach that significantly improves performance in lossy channels by introducing an additional25 decoy state with a very high mean photon number.26 By eliminating the need for an extra channel capable of clock synchronization, both methods27 proposed potentially reduce the complexity and cost of QKD systems and improve their agility

In this work a loop quantum corrected model is obtained for spherically symmetric space-times in the vacuum. This effective model is derived by the use of the path integral method, previously employed in several models of Loop Quantum Cosmology. Our principal aim is to find explicit corrections corresponding to inverse triad and holonomy effects that commonly arise from the loop quantization procedure. These corrections modify the Hamiltonian constraint of the classical theory, adding quantum parameters that represent the length of the holonomies considered during quantization. The semiclassical theory yielded reduces to the classical case when small values of such length are taken to be small. Solutions to the effective dynamics of a simplified version of the complete corrected theory are then found and used to describe an effective geometry with inverse triad corrections. This modified space-time represents a black hole with a curvature singularity in its interior which, contrary to its classical counterpart, does not lead to null geodesic incompleteness. For the case of holonomy corrections, preliminary arguments are given in favor of a potential singularity resolution.

Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories. This paper presents Q-SpiRL, a quantum spiking reinforcement learning framework for obstacle-aware robot navigation. The framework develops and evaluates five agent families: tabular Q-learning, classical MLP, classical SNN, quantum-enhanced MLP (QMLP), and quantum-enhanced spiking neural network (QSNN). While all models are implemented under a unified training and evaluation pipeline, the QSNN is the central architecture of interest, as it combines spike-based temporal processing with variational quantum feature transformation. Experiments are conducted across three grid-world environments of increasing size, namely 20x20, 30x30, and 40x40, with both static and dynamic obstacles. Performance is assessed using success rate, success-weighted path length, path length, and turn rate under deterministic inference. Results show that QSNN achieves the strongest overall trade-off between task completion, trajectory efficiency, and motion smoothness, reaching up to 99% success rate while maintaining high path efficiency in the most challenging setting. Execution on IBM quantum hardware further demonstrates the feasibility of deploying the proposed hybrid policy under real-device conditions.

We study field-controlled spin-valley transport in monolayer MoS$_2$ through a single electrostatic barrier and a uniform off-resonant elliptically polarized irradiation. Starting from the massive Dirac Hamiltonian with intrinsic spin-orbit coupling, we use a high-frequency Floquet expansion to obtain an effective static model with a laser-renormalized mass (gap) term. We solve the scattering problem by spinor matching and derive the exact analytic expression for the transmission. The numerical results show that the drive tunes both the spin-valley-dependent propagation threshold inside the barrier and the Fabry-Pérot phase, creating controllable pass/stop bands. By varying both the laser intensity (amplitude) and the polarization shape, we show that the same junction can be switched between broadband valley filtering and resonance-selective operation, and the valley contrast remains visible in the Landauer conductance. Our findings establish an efficient route for realizing optically reconfigurable valleytronic and spintronic functionalities in MoS$_2$.

We present a quantum circuit implementation of the quantum hashing algorithm (quantum fingerprinting) for a quantum device with restrictions on the application of two-qubit gates by a qubit connectivity graph. We present an optimization technique for the shallow circuit for quantum hashing in the case of a cactus as a qubit connectivity graph. The algorithm has $O(n^3)$ complexity to build the circuit, where $n$ is the number of qubits and $m$ is the number of connections (edges) in the graph. It is improvement compared to the existing exponential-time algorithm in the case of arbitrary graphs. The algorithm uses solution for the shortest non-simple 1-covering path problem as a subroutine. We present an $O(n^3)$-time solution for this graph-theory problem in the case of a cactus. This result can be interesting independently. The algorithm also used for improving of the quantum circuit for Quantum Fourier Transform.

Spin qubits in silicon-MOS (SiMOS) quantum dots have recently demonstrated compatibility with existing industry standard CMOS fabrication techniques. These devices have routinely achieved single- and two-qubit gate fidelities above 99% and demonstrated highly entangled two-qubit Bell states in isolated double quantum dot (DQD) unit cells, however coupling between unit cells has remained challenging. In this work, we present a two unit cell, four-qubit SiMOS processor with universal controllability and fully parallelised state initialisation and readout. We use this processor to generate maximally entangled three-qubit states, including the Greenberger-Horne-Zeilinger (GHZ) state, and certify multipartite entanglement through violation of the classical Mermin-witness bound. By using a fully symmetric dynamically decoupled gate sequence to create our entangled states, we are able to preserve the lifetime of the entanglement beyond $T_2^*$, to a time limited instead by $T_2^\textrm{Hahn}$. These demonstrations pave a road to the scalable operation of larger SiMOS processors, and achieving high purity, long-lived multi-qubit entangled states in them.

The generalized quantum Stein's lemma characterizes the optimal asymptotic exponent of the type-II error in quantum hypothesis testing for an independent and identically distributed (IID) null hypothesis against a composite alternative hypothesis. Classically, a probabilistic mixture of IID sources arises as a natural generalization of IID sources, and, in the non-composite setting, the optimal type-II error exponent in hypothesis testing for such classical mixed sources is known to be characterized concisely by the worst-case component of the mixture. In this work, we extend these foundational results to composite quantum hypothesis testing where the null hypothesis is a mixed source, i.e., a probabilistic mixture of IID quantum states, and the alternative hypothesis is composite as in the generalized quantum Stein's lemma. When the type-I error vanishes asymptotically, we characterize the optimal type-II error exponent of this composite quantum hypothesis testing problem in terms of the worst-case component of the mixture, by developing techniques for the non-commutative quantum setting inspired by the classical information-spectrum analysis. We also show that the analogous characterization does not hold in general for a fixed nonzero type-I error threshold, by providing a counterexample beyond the vanishing type-I error regime. These results clarify the applicability of the generalized quantum Stein's lemma to highly non-IID null hypotheses arising from arbitrary finite probabilistic mixtures of IID quantum states.

We establish a quantum Fisher information (QFI) duality for distributed quantum sensor networks with local phase encoding. For any $N$-qubit probe state, where $N$ denotes the number of sensors, $F_Q(\boldsymbol{w}^\top \boldsymbolθ) + F_Q(\boldsymbol{v}^\top \boldsymbolθ) \leq N$ for all unit orthogonal sensing directions $\boldsymbol{w}$ and $\boldsymbol{v}$, with equality for all equatorial states when $N=2$ and for Greenberger--Horne--Zeilinger (GHZ) states when $N\geq 2$. Heisenberg-limited precision for direction $\boldsymbol{w}$, $F_Q(\boldsymbol{w}^\top \boldsymbolθ)=N$, saturates the bound and simultaneously forces zero QFI for all other independent directions. This can be interpreted as the condition for parameter privacy in distributed quantum sensing: attaining Heisenberg-limited precision for the sensing target renders all alternative privacy-intrusive estimations impossible.

We consider the problem of modeling a single qubit in contact with a one-dimensional waveguide beyond the standard perturbative and Markovian approximations. Using the recently developed input-output hierarchical equations of motion (io-HEOM), we investigate multiple examples of such waveguides, characterized by different spectral densities. Our examples highlight that the io-HEOM method can accurately capture non-Markovianity in waveguide QED from two distinct origins. The first source of non-Markovianity is spatially non-local coupling between the qubit and the waveguide. By examining two examples with non-local coupling, we show how the coupling function affects the steady-state bound photons, and demonstrate the release of these photons when the qubit energy is quenched. The second source of non-Markovianity is non-linear dispersion. We illustrate this scenario using the example of a cavity array with point-like coupling, where the non-linear dispersion leads to persistent oscillations due to Van Hove singularities in the spectral density.

Understanding how complex entanglement structures emerge is a central problem in quantum many-body physics. Recent work by Zhang et al. has considered structured initial states prepared by evolving a product state under a chaotic Hamiltonian for a finite time before quenching to the target Hamiltonian. In this setup, total entanglement entropy growth in many-body localized systems exhibits two distinct regimes, first increasing and then decreasing as the initial entanglement is tuned. In this work, we identify the physical origin of this behavior by analyzing the dynamics of both the Rényi entanglement entropy and the Wehrl-Rényi entropy in the random-field XXZ model, the latter of which characterizes multipartite entanglement. We show that a similar non-monotonic dependence on the initial entanglement also appears in the net growth of the Wehrl-Rényi entropy for product states polarized along the $z$-direction. The first regime is governed by a finite magnetization associated with local integrals of motion, while the second reflects inter-site correlations. In contrast, for product states in the $x/y$-direction, the entanglement growth exhibits a monotonic decay. Our results provide a more fine-grained picture of how distinct initial-state properties shape entanglement dynamics in many-body localized systems.

Nonlinearity is an essential ingredient for encoding quantum states with non-uniform energy spacing, implementing coherent quantum gates, reading out qubits, amplifying, and mixing electromagnetic signals. In this work, we demonstrate the nonlinear behavior of a constriction fabricated from an amorphous, high-kinetic inductance material, tungsten silicide, embedded in a three-dimensional RF-SQUID. We find that the results are consistent with the weak link behaving as a Josephson junction with a sawtooth-like current-phase relation or a quantum phase slip element. Finally, we measure relaxation times of the metastable, persistent-current states trapped in the local minima of the potential.

The Optimum-Path Forest is a graph-based framework for designing classifiers that exploit inter-sample connectivity. A particular variant constructs decision boundaries based on prototypes computed by a Minimum Spanning Tree (MST) over the training data, which might become prohibitive for large-scale datasets. In this context, Quantum Machine Learning has emerged as a promising approach to overcome the high computational burden of combinatorial problems. We propose a quantum-inspired approach for prototype selection in OPF classifiers by reformulating the MST problem as a Polynomial Unconstrained Binary Optimization (PUBO) task and further employing the Feedback-Based Quantum Optimization (FALQON) algorithm for Hamiltonian minimization. The PUBO formulation reduces the need for qubits and eliminates the need for auxiliary variables, thereby addressing scalability constraints in current quantum hardware. Experiments on real-world datasets demonstrate that the FALQON-optimized MST achieves accuracies comparable to those of the classical Prim's algorithm while maintaining prototype quality. While FALQON occasionally reached local minima, it did not significantly impact the accuracy of the prototype selection process.

The gravitational entropy proposal of Clifton, Ellis and Tavakol (CET) is based on an effective energy momentum tensor formed by the algebraic decomposition of the 4th order Bel-Robinson tensor. So far the application of the CET proposal has been limited to spacetimes of Petrov types D and N for which this algebraic decomposition is unique. To address this limitation we examine in detail the effective energy momentum tensors that result from the algebraic decomposition of the Bel-Robinson tensor in Petrov type I spacetimes. As a test case we apply these results to the Szekeres models of class II, a Petrov type I analytic solution.

Scalar-tensor-vector gravity, also known as modified gravity (MOG), has emerged as an alternative to General Relativity (GR). It aims to explain astrophysical phenomena without invoking dark matter. The S-stars orbiting the supermassive black hole at the Galactic centre provide a unique opportunity to test the predictions of MOG because the orbital measurements are highly precise. We investigate the perturbations in the orbits of S-stars under MOG, focusing on the effects on orbital elements, observables such as right ascension, declination, and radial velocity, and the potential degeneracy with dark matter scenarios. We numerically integrated the first post-Newtonian equations of motion for S-stars within the MOG framework, considering contributions from the space-time geometry and the fifth force. We analysed the time evolution of orbital elements and projected the orbits onto the plane of the sky to assess deviations from GR. Furthermore, we compared the MOG-induced effects with those expected from a dark matter distribution. We found that MOG significantly alters the orbital precession, particularly for higher values of the MOG parameter $α$. For sufficiently large $α$ or long observational baselines, the deviations in the observables can reach amplitudes comparable to current observational precision. Furthermore, we demonstrate that MOG effects can mimic those of a dark matter distribution, particularly in the argument of pericentre, and we reveal an unexplored connection between MOG and GR with electromagnetism. The effects of MOG on stellar orbits are distinct from those predicted by GR and can be tested with precise astrometric and spectroscopic measurements of the S-stars. However, a potential degeneracy with dark matter signatures necessitates careful interpretation of observational data.

In this article, we investigate the optical, thermodynamic, and scattering properties of a ModMax black hole surrounded by a cloud of strings within the framework of Einstein-bumblebee gravity. We then analyze in detail the thermodynamic properties of this black hole, including the Hawking temperature, entropy, and other relevant thermodynamic quantities, and examine the outcomes. Furthermore, we study the greybody factors (GFs) associated with the emission of various perturbative fields propagating in this black hole background. In particular, we consider spin-0 scalar fields, spin-1 electromagnetic fields, and spin-2 graviton fields, and evaluate the corresponding absorption probabilities and energy emission rates. Our analysis demonstrates how the optical features, thermodynamics and GFs depend on the underlying parameters of the system, such as the Lorentz symmetry violation parameter, the cloud of strings parameter, the ModMax parameter, the electric charge, and the black hole mass, thereby providing a comprehensive understanding of the physical effects of these parameters on the radiation and scattering processes around the black hole.

Post-Newtonian (PN) theory provides the analytic foundation for modeling the early inspiral of binary black holes. However, as an asymptotic series, successive PN orders do not necessarily improve agreement with the full nonlinear dynamics. While this has been explored in the extreme-mass-ratio limit, comparable-mass systems most relevant to current observations have not been benchmarked as systematically at high PN order. We study the convergence of the PN series for non-spinning and quasi-circular systems by comparing the PN energy flux at future null infinity to a long, high-accuracy numerical relativity (NR) simulation. To enable a gauge-consistent comparison, we place both descriptions in the same BMS frame and calibrate the intrinsic PN parameters by fitting to the NR waveform in the early inspiral. We find that for orbital velocities $v\lesssim0.45$, higher PN orders continue to reduce the PN--NR flux discrepancy, with (incomplete) 6PN providing the best agreement among the orders considered. The improvement with PN order is non-monotonic with local extrema around 2.5PN and 4PN. This implies that the optimal truncation order of the PN series cannot be identified from the first local minimum in the energy flux residuals, contrary to suggestions in earlier work. As $v$ approaches $\sim 0.5$ near the innermost circular orbit, higher PN orders no longer improve the agreement between NR and PN, indicating a loss of convergence. These results motivate continued high-order PN calculations and clarify the NR accuracy needed to validate them.

We study a two-level system coupled to two quantized electromagnetic modes within the Jaynes-Cummings framework. While the single-mode model is exactly solvable due to its conserved excitation number, yielding finite-dimensional invariant subspaces, the two-mode model extension presents a fundamental challenge: although the total excitation number remains conserved, each invariant subspace is infinite-dimensional, preventing a closed-form analytical solution. Our scheme separates the dynamics into a dominant, exactly solvable semiclassical component, the atom interacting with the mean fields of both modes, and treats the remaining quantum fluctuations through a sequence of unitary transformations that preserve essential quantum features. We validate our approach through direct comparison with numerical solutions, focusing on the non-resonant regime where multiple detunings give rise to rich interference effects and multi-timescale dynamics inaccessible to standard approximations. The method accurately reproduces atomic inversion, field observables, and fidelity over relevant timescales, while remaining computationally efficient.

Massive scalar perturbations of asymptotically de Sitter black holes in generalized Proca theory display a sharp interplay between primary hair, horizon structure, and field mass. Using high-order WKB calculations supplemented by time-domain evolution, we analyze representative black-hole backgrounds and compare the full black-hole spectrum with the exact pure de Sitter benchmark. We show that increasing the scalar mass drives the frequencies into a simple large-mass regime in which the real part grows linearly while the damping rate approaches a nonzero geometry-dependent constant, so true quasi-resonances do not occur within the regime studied here. We also identify how the spectrum shifts with black-hole size and Proca hair, derive a compact analytic large-$μ$ formula, and comment on the implications of the de Sitter-like sector for strong cosmic censorship in the charged three-horizon regime.

In the standard geometric optics approximation, null rays propagating in a spherically symmetric black hole background follow planar geodesics. This picture changes, however, when the helicity-dependent effects of light are incorporated into the dynamics. Specifically, the interaction between the helicity of light and the spacetime curvature induces a significant angular deflection out of the geodesic plane. In this paper, we employ the spinoptics formalism to study light deflection due to the helicity-curvature interaction in two spherically symmetric geometries: the Rezzolla--Zhidenko (RZ) parametrized metric, and a hairy regular black hole solution obtained via gravitational decoupling. Our results reveal clear imprints of both the RZ parametrization coefficients and the hairy black hole parameter on the deflection angle. Furthermore, we assess the viability of using the RZ parametrization to mimic the regular hairy black hole, discussing the validity and limitations of such an approximation.

The energy extraction from a magnetized Reissner-Nordström black hole is analyzed within the framework of the electric Penrose mechanism. The presence of an external magnetic field induces an axisymmetric configuration and an ergosphere (the region where energy extraction is possible) arises, allowing for negative energy states even in an otherwise static spacetime. By analyzing the decay of particles at turning points of the radial motion, we derive the general expression for the efficiency of the process in terms of the metric coefficients and the electromagnetic potential. This formulation provides a direct criterion for identifying the ergoregions and we show that the magnetic field acts as a control parameter that governs both the configuration of the ergosphere and the efficiency of the process. In particular, analytical expressions for the critical magnetic fields that determine the onset and suppression of energy extraction are determined. Our results extend previous analysis of the electric Penrose process for magnetized configurations and clarify the role of the external field in enhancing or inhibiting energy extraction from charged black holes.

Gravitational-wave detectors operate in inherently non-stationary environments, requiring robust detector characterization (DetChar) to distinguish instrumental transients from astrophysical signals. Traditional DetChar frameworks typically rely on morphological classifiers or energy-based projections, such as band-limited root-mean-square (BLRMS) metrics, which can conflate global amplitude scaling with physical reconfigurations of the spectrum. In this work, we introduce Fisher information velocity, a novel geometric channel that models the detector's power spectral density (PSD) as a point on a Riemannian manifold. By tracking the kinematic drift of the noise floor and utilizing exterior algebra to calculate tangent divergence ($\sin θ$), we mathematically decouple simple energy surges from spectral warps, or differential redistributions of power across frequency bands. Applying this framework via the sgn-drift streaming pipeline to ~40 hours of high-cadence Advanced LIGO O4a data, we evaluate N=282,080 independent manifold velocity samples. High-resolution phase space mapping reveals a bimodal taxonomy of severe instrumental non-stationarity, classifying events into structural pivots (87.2%) and isotropic surges (12.8%). Among co-detected events, the geometric channel achieves higher significance than standard BLRMS monitors in 74% of cases with a median sensitivity ratio of $Γ= 1.65$. The two channels detect largely non-overlapping populations, increasing the total anomaly catalog by 87% over BLRMS alone. Systematic validation on 10 confirmed GWTC-4.0 events and ~5,000 simulated injections demonstrates robust insensitivity to astrophysical signals, establishing this geometric channel as a sensitive, complementary, and veto-safe diagnostic for current and next-generation detector networks.

We explore a continuous-time quantum walk starting at a single vertex on the discrete path and cycle with a cubic nonlinearity. Such nonlinearities arise in Bose-Einstein condensates described by the Gross-Pitaevskii equation or by nonlinear optical waveguide arrays. We analytically prove that the nonlinear quantum walk can be trapped to arbitrary fidelity depending on the coefficient of the nonlinear term. This contrasts with linear quantum walks, which are known for spreading quickly in one dimension. We propose that this trapping can be used for timing in quantum state transfer, where a qubit is held at a node until it is ready to be transferred, and it can also be held again at the receiving node. This scheme can also be interpreted as a form of quantum memory, with the trap and transfer corresponding to the storage and release of quantum information.

Efficiently generating photon pairs with high heralding efficiency and high single photon purity that are bandwidth matched to quantum emitters, quantum memories, and other matter-based qubits is critical for quantum networking applications. However, nonlinear optics-based sources require substantial spectral engineering to overcome the orders of magnitude bandwidth mismatch between those sources and qubit systems. A popular solution is cavity-enhanced spontaneous parametric down conversion (SPDC) where the cavity sets the photon bandwidth and simultaneously enhances the spectral brightness of the SPDC. Bulk, free-space configurations are generally required to achieve the MHz-scale bandwidths required to interface with most qubit systems. Replicating these in scalable integrated photonic architectures is an ongoing challenge due to the much higher propagation losses that limit the size and linewidth of chip-based resonators. We show here how an intra-cavity slow light medium, acting as an ultra-narrow filter, would enable narrowband photon pair generation in broadband cavities with high single photon purity and without compromising the heralding efficiency. We show that such metrics can be readily realized in erbium doped thin-film lithium niobate microrings using realistic design parameters.

The recent arXiv posting [11], commenting on the paper [7], argues that the proof of Lemma 3.1 in [7] is missing the Bohm quantum potential [1, 2] of the Madelung p.d.e. [9]. This short technical note extends the proof of Lemma 3.1 to introduce a Bohm quantum potential explicitly, and then shows why this term can be assumed to be zero in the wave construction, without loss of generality. The continuity p.d.e. and the Hamilton-Jacobi p.d.e., extended by the Bohm potential, are undisputed. However, the actual action and density solutions depend on their initialization at t = 0. In [7], this initialization is motivated by the Feynman kernel [4], which is fundamentally different from the standard initialization of the Madelung solution [9]. This in turn leads to different action and density solutions, and explains why in one case the Bohm quantum potential disappears and in the other does not. The resulting overall wave, however, is independent of this computational initialization.

Variational quantum dynamics simulations (VQDS) provide a promising route to simulate real- and imaginary-time quantum dynamics on noisy intermediate-scale quantum devices using fixed-depth circuits. However, their practical performance is strongly limited by sampling noise arising from a finite number of circuit measurements. In this work, we systematically investigate the impact of sampling noise on VQDS, with a focus on ground-state preparation in one-dimensional Ising spin models using imaginary time evolution. We compare different regularization strategies for stabilizing the equations of motion and show that Tikhonov regularization provides robust performance in noisy imaginary-time evolution. We then benchmark measurement-distribution strategies that allocate shots by minimizing a cost function that characterizes the error in solving the equation of motion. Using noisy circuit simulations, we demonstrate that such optimized shot allocation can significantly improve state fidelity and reduce the total measurement cost by more than a factor of two compared to uniform shot distributions. We observe that the best results are found if a sufficiently large number of measurements is guaranteed for all circuits, suggesting that a finite fraction of shots should be distributed evenly. Our results provide practical guidelines for implementing measurement-efficient variational quantum dynamics and ground-state preparation on near-term quantum hardware.

Realistic quantum devices are inherently open and often involve environments with memory. Here, we investigate quantum resource generation in two classes of random circuits, namely, memoryless open and memoryful open random circuits, and compare their behavior with the well-explored random unitary circuit model. We show that environmental memory qualitatively alters the dynamics: while unitary and memoryful circuits exhibit sustained growth and saturation of entanglement and non-stabilizerness (magic); memoryless dynamics leads to a distinct behavior where entanglement decays to zero after transient growth, even though non-stabilizerness remains non-zero, indicating the persistence of nonclassical features beyond entanglement. Consistently, Krylov complexity reveals suppressed spreading of quantum states in memoryless circuits, in contrast to strong growth in unitary and memoryful dynamics, which saturates at the maximum value. Finally, we show that memoryful circuits more effectively approach low-order quantum-state k-designs than the other two circuits. Closed dynamics are therefore usually the most resource-generating, but are ideal; realistic dynamics are open and seem to generate less, but if they possess memory, they can sometimes even outdo closed dynamics.

We develop a simple and general post-selection strategy for high-rate quantum codes that is transferrable across decoders. After an initial baseline run, the decoder is re-run once per logical observable, and forced in these latter runs to provide a solution where the given observable has the complementary outcome. Shots are rejected that find logically complementary solutions with similar likelihoods compared to the baseline. Using the Relay-BP decoder, we benchmark the strategy on the $72$-qubit and $144$-qubit bivariate bicycle codes, as well as surgery gadgets for the latter. In comparison to previous post-selection strategies, our results offer an improved logical error rate by over a factor of $4$ on the same circuit and physical error rate, and at the same rate of post-selection. Our strategies are also lightweight, relying only on FPGA-friendly belief propagation, whereas the previous best used repeated rounds of a high-latency BP-OSD decoder.

Table lookup, often referred to as quantum read only memory (QROM), is one of the most widely used subroutines in quantum algorithms, and constitutes the majority share of algorithmic overheads in most practical applications of quantum computers. It involves the coherent loading of $N$ bitstrings of length $b$ in superposition, and naively has a non-Clifford cost of $N$ Toffolis. It is known that given access to $b\, λ$ dirty qubits, one can reduce the Toffoli cost of QROM to $2\frac{N}λ + 4b(λ- 1)$. In this work, we first present an optimization to reduce this cost to $2\frac{N}λ + 2b(λ- 1) + 2λ-6$ by replacing the ``SelectSwap" architecture with ``SelectCopy". We then provide a further optimization for the qubit-constrained regime where the Toffoli cost is typically $\sim 2\frac{N}λ$, and reduce it to $\sim (1+\frac{1}{b})\frac{N}λ$, cutting the cost by approximately $50\%$ and effectively matching the performance of clean-qubit QROM using dirty qubits for practical values of $b$. Lastly, we provide a parametric family of methods that allow the interpolation of the prefactor of the $\frac{N}λ $ term from $2$ to ($\, 1+\frac{1}{b}\,$) to obtain the best cost for different qubit availability regimes.

The preparation of quantum states is a fundamental requirement for many quantum algorithms. A native route to preparing physically structured states is based on short-time simulation of dynamical processes, such as real or imaginary time evolution. This work presents a resource-efficient framework for the approximation thereof with \textit{bowtie \ac{VarQTE}} which uses classical simulation where possible and quantum resources where necessary. We introduce a framework that leverages existing causal light-cones to minimize quantum resource requirements in the evaluation of gradient and quantum geometric tensor terms by utilizing classical simulation methods for causally relevant subcircuits. This in turn enables exact parameter updates according to McLachlan's variational principle and, thereby, improves numerical stability. We conduct a comparison with a state preparation method that is based on a tensor-network compiled Trotter algorithm: approximate quantum compilation (AQC). In recent work, this approach has shown impressive performance. However, its key-bottleneck is the necessity to have a classical (approximate) representation of the target state. Our numerical experiments indicate that bowtie VarQTE can achieve comparable fidelities without this requirement. We further illustrate how bowtie VarQTE can facilitate a state-preparation pipeline that combines the simulation of imaginary and real time evolution for a sample-based quantum algorithm. In fact, results on 2D systems show how bowtie VarQTE can reduce the quantum requirements compared to standard, sample-based Krylov diagonalization calculations. Our results indicate that VarQTE is a promising primitive for the preparation of physically structured quantum states that reduces requirements on quantum resources by leveraging existing structures and the associated possibility of enabling classical simulations.

Observation of gravitationally induced quantum entanglement is often interpreted as a direct evidence of non-classical gravity. While the form and the degree of non-classicality have been rigorously studied from a foundational perspective, classical models reproducing experimental signatures of such entanglement remain underexplored. Motivated by the experimental simplicity, nearly all existing optomechanical approaches assume Gaussian initial states, and due to the weakness of gravity the quantum Newtonian potential is truncated at the second order. However, this regime admits a classical description in terms of the Wigner-Weyl representation, including features typically associated with quantum entanglement. A clear distinction between classical and quantum predictions emerges only beyond this setting. We comprehensively analyze the possibilities and provide operational witnesses for detection of non-classicality via Wigner negativity, and detection of non-quantumness via negativity of the Weyl operator. Our results demonstrate that the experimental requirements on certifying gravitational entanglement are more stringent than previously anticipated.

We theoretically demonstrate that a superconducting circular current induced in a semiconductor results in emission of orbital-angular-momentum (OAM) entangled photon pairs upon carrier recombination. Combining the macroscopic Ginzburg-Landau theory and the microscopic Bardeen-Cooper-Schrieffer (BCS) theory, we investigate the emission of a superconducting light-emitting diode (SLED) with a spatially varying phase profile in the superconducting order parameter. We show that in the active region of the SLED with a circular supercurrent, radiative recombination processes inherit the order parameter phase and result in photon pairs emitted into modes of different OAM quantum numbers. We demonstrate that coherent superposition of superconducting qubit eigenstates can also be mapped onto a coherent superposition of emitted photon states. We also show that other recombination processes due to thermally excited quasi particles do not significantly degrade the state purity. Our results introduce an original scheme for generating OAM-entangled photons enabling a new method of transmitting superconducting qubit information to photonic channels thereby bridging the gap between solid-state and photon-based platforms for quantum communications and information processing.

The Quantum Approximate Optimization Algorithm (QAOA) is a leading candidate for demonstrating quantum advantage on near-term devices, yet the physical origins of its efficacy remain poorly understood. In this work, we study QAOA for random $k$-SAT problems within a universal-mixer $k$-local search framework, establishing a formal correspondence between adiabatic state transfer and the QAOA ansatz. This correspondence yields a rigorous performance guarantee for random instances with clause density $m=O(n^{1+ε})$ and circuit depth $Θ(n^2)$. We further investigate the NISQ regime with shallow circuits of depth $p=O(n)$. Surprisingly, the optimal parameters do not become stochastic under depth compression, but instead remain confined to a structured low-dimensional region, which we identify as a smooth adiabatic manifold. Numerical evidence indicates that this manifold persists across different circuit depths and arises from the variational suppression of adiabatic leakage. Based on this structure, we propose the smooth adiabatic-manifold parameterization (SAMP) strategy, transforming parameter optimization from an unstructured high-dimensional search into a guided refinement process. Numerical experiments on random 3-SAT instances show that SAMP achieves sublinear optimization scaling with circuit depth while providing robust zero-cost initialization for deep circuits.

Molecular spin qubits offer a versatile platform for quantum information processing due to their synthetic tunability and well-defined electronic structure. Here, a fitted-parameter-free computational framework combining density functional theory (DFT), time-dependent DFT (TD-DFT), and Redfield theory is applied to investigate the longitudinal spin-lattice relaxation time $T_1$ of the Eu nuclear spin qubit Eu(dpphen)(NO3)3. Using a single-molecule gas-phase model, the experimental long relaxation component $T_{1,\mathrm{long}} = 41.39$ s is reproduced within a factor of 1.4 (calculated: 55.88 s at 4.2 K), indicating that the slow relaxation channel is governed by intramolecular vibronic coupling. In contrast, the calculated $T_{1,\mathrm{short}}$ deviates by a factor of 66, highlighting the importance of crystal lattice and intermolecular effects absent from the model. The experimental $^5D_0 \rightarrow {}^7F_0$ optical transition is reproduced to within 1.1%, supporting the accuracy of the electronic structure description. Vibrational analysis identifies a large-amplitude dpphen rocking mode at a frequency of $332.02~\mathrm{cm}^{-1}$ as the dominant vibronic coupling channel, while electric field gradient (EFG) derivative analysis independently identifies another nitrate-rocking mode at $180.57~\mathrm{cm}^{-1}$ as the primary modulator of the nuclear spin environment via nitrate motion. These results are consistent with a near-maximal quadrupole asymmetry parameter $η= 0.941$, which creates state mixing through off-diagonal quadrupolar terms. Overall, the results establish a single-molecule relaxation baseline and suggest targeted ligand rigidification and substitution strategies to suppress decoherence.

We study the ground-state density patterns of a population-imbalanced two-component dipolar Bose-Einstein condensate confined in a circular quasi-two-dimensional box. Using a mean-field model, we map out phase diagrams as functions of the axial confinement, interaction imbalance, and population ratio. The system supports a rich sequence of stationary morphologies, including a nearly uniform pancake state, pancake-droplet and ring-droplet coexistence states, droplet arrays, and concentric rings. These patterns show a close structural correspondence to microphase-separated morphologies in diblock-copolymer systems, with the population imbalance acting as an effective volume fraction that selects the pattern topology. Analysis of the density profiles and structure factors reveals that the modulated states possess an intrinsic nonzero characteristic wave vector, which remains essentially unchanged when the box size is varied. We also find that the characteristic pattern spacing scales linearly with the axial confinement length, indicating that the transverse thickness of the condensate controls the effective in-plane length scale. In a finite circular box, this smooth scaling is interrupted by discrete steps, reflecting geometric frustration and the integer locking of the number of rings or droplets. Our results show that box-trapped dipolar mixtures provide a controllable platform for studying finite-size pattern selection and nonlocal microphase formation in quantum fluids.

This work investigates the impact of seasonal variations in seismic noise on the low-frequency performance of the Einstein Telescope (ET) at the Sardinia candidate site, focusing on implications for compact binary coalescence observations. Using seismic data collected between 2022 and 2025 in deep boreholes, we characterize monthly noise variations and identify representative best and worst case scenarios, corresponding to July and December. The measured seismic spectra are used to estimate the Newtonian noise contribution in the 2-10 Hz band and to derive modified ET sensitivity curves. These are implemented in a simulation framework to evaluate their effect on the signal-to-noise ratio (SNR) of binary neutron star and intermediate mass black hole signals, assuming the triangular ET configuration. We find that the low seismic noise of the Sardinia site results in only minor seasonal variations in detector sensitivity. The corresponding impact on SNR is limited to a few percent, even without including Newtonian noise mitigation. These results indicate that seasonal environmental fluctuation have a minor effect on the early inspired detectability of compact binaries, confirming the suitability of the Sardinia site for achieving ET low-frequency sensitivity goals.

On a mixed-frustration 12-qubit Ising instance run on two D-Wave generations, Advantage2 Zephyr and Advantage_system6.4 Pegasus, the late-time subsystem autocorrelation under cycled reverse annealing sits strictly between two equilibrium reference processes at the device-calibrated effective temperature: localized parallel tempering, and delocalized equilibrated path-integral simulated quantum annealing at a fixed Advantage2 pause-point transverse-field scale. The bracket holds on all three tested schedules and at both hardware calibrations. We obtain this result through two ingredients: a cycled reverse-anneal protocol (reinitialize_state=False, 50 cycles per submission) used as a Markov-chain probe of the device's pause-point dynamics, and a parallel-tempering falsification framework with bias-corrected and accelerated bootstrap 95% confidence intervals. Of eighteen tested (instance, schedule) combinations on Advantage2, three are PT-unmatched and correspond to two distinct Ising instances; an independent native-graph control with no minor embedding on a third mixed-frustration instance reproduces the same direction of mismatch. Among twenty random training instances, schedule shape modulates basin occupation on six of the thirteen multi-basin-in-readout instances, with dominant-configuration shifts of up to 38 percentage points including changes of the dominant configuration. A pre-registered linear predictor of schedule sensitivity from exhaustively computable landscape features fails on ten held-out instances, indicating that schedule sensitivity is not captured by simple linear functions of the tested landscape moments. The bracketing result revises an earlier two-pause-enhancement claim and reframes reverse-anneal schedules as instance-specific basin-occupation probes rather than universal quantum-enhancement knobs.

In this paper, we introduce a rotating Kaluza-Klein black hole characterized by a massive vector field and a scalar field. We begin by identifying the horizons and mapping the allowed parameter space to differentiate black hole solutions from naked singularities. The thermodynamic analysis shows a phase transition by examining Hawking temperature and heat capacity. We also conduct a topological study of the thermodynamic potentials. The Hawking temperature indicates a conventional critical point, while the off-shell generalized free energy classifies the system into a specific universal group. We further investigate the geometry of the ergosphere and how it relates to the black holes spin. Additionally, we look at astrophysical signs, such as the black hole shadow and the features of the thin accretion disk. Our results indicate that while the extra-dimensional changes significantly shift phase transition points and modify the shadow size, the essential topological class remains stable. This study provides a solid framework for distinguishing higher-dimensional gravity models through both thermodynamic and observational signs.

Its detections with pion-decay-at-rest, solar and recently with reactor antineutrinos by the CONUS collaboration render coherent elastic neutrino-nucleus scattering (CE$ν$NS) an established tool for investigations within and beyond the Standard Model (SM). The CONUS experiment located at the nuclear power plants in Brokdorf (Germany) and Leibstadt (Switzerland) operates Germanium semiconductor detectors in a compact shield at close distance to the reactor core. An observation with $3.7 σ$ significance is reported at the Leibstadt site, showing good agreement with its SM prediction. Physics investigations performed with the last datasets collected at the Brokdorf reactor and with the first data obtained at the Leibstadt site are summarized. By using the experimental analysis framework, the presented results contain the full systematics that underlie the experiment. Previously determined limits with neutrino-electron scattering on the neutrino magnetic moment and a neutrino millicharge are improved to $μ_ν <5.18\cdot 10^{-11}μ_\mathrm{B}$ and $q_ν<1.76\cdot 10^{-12} e_0$ (90% C.L). Further, the scale of new physics related to NSIs is improved to $Λ_{\rm NSI}$=145 GeV and limits on the coupling of light new mediators are lowered down to $4 \cdot 10^{-7}$ (90% C.L.) with the new data. Finally, the determination of the Weinberg angle with CE$ν$NS and reactor antineutrinos yields $\sin^{2}θ_W= 0.28^{+0.03}_{-0.04}$ at a momentum transfer of $\sim 10 \ \mathrm{MeV}$.

We consider scenarios in which a shallow bound state undergoes breakup by a probe whose energy is high compared to the binding energy. The first two scenarios, which serve as warm-up exercises, involve a single heavy particle bound to a light particle, analogous to a core nucleus bound to a neutron. We show that in quasi-free kinematics, the leading effect comes from the heavy particle being knocked out by the probe, with corrections suppressed by inverse powers of the probe momentum. This formally justifies extracting neutron form factors from high-energy deuteron breakup in quasi-free kinematics. In Scenario 1, the probe is a local current; in Scenario 2, it is hadron scattering. In Scenarios 3 and 4 we consider, respectively, a local current and hadron scattering, but now on a three-body bound state of a heavy particle and two light particles. Hard knockout of the heavy particle leaves two low-energy particles behind, which can interact with one another. In all four scenarios, we prove that the amplitude is dominated by the nearby on-shell pole of the heavy-particle propagator and derive a closed-form expression for this contribution. When two bodies are left behind, the leading amplitude is the product of the scattering of the two light particles, a dynamical function depending on the probe, and a real function related to the bound-state wavefunction. Thus, quasi-free removal of a core nucleus from a system with halo neutrons provides access to on-shell data on multi-neutron interactions. The resulting amplitudes are relativistic and satisfy unitarity for the remnant subsystem exactly. We also provide complementary non-relativistic derivations. While the derivations are for spinless particles, the generalization to spin is straightforward, since the results depend only on quasi-free knockout kinematics; we make no assumptions about the inter-particle dynamics.

We present the first complete lattice QCD calculation of the four structure-dependent form factors governing the rare charged kaon decay $K^- \to \ell^- \barν_\ell \ell'^+ \ell'^-$, with fully controlled statistical and systematic uncertainties. Our calculation is based on gauge ensembles generated by the Extended Twisted Mass Collaboration (ETMC) with $N_f = 2+1+1$ flavors of Wilson-clover twisted-mass fermions. Simulations are performed directly at the physical values of the light and strange quark masses, and include an estimate of the quark-disconnected contributions in which the virtual photon couples to sea quarks. All four form factors are determined across the kinematical region probed by experiments. The Spectral Function Reconstruction (SFR) method of Ref. [1] is employed to overcome the analytic continuation problem for dilepton invariant masses above the two-pion threshold. Finite-volume effects are investigated using ensembles with spatial extents $L\simeq [3.8,7.6]~\mathrm{fm}$, while the continuum limit is obtained from three lattice spacings in the range $a\in[0.057, 0.08]~\mathrm{fm}$. Our results for the form factors enable the evaluation of decay rates and differential observables for all four channels, $K^- \to e^- \barν_e e^+ e^-$, $K^- \to e^- \barν_e μ^+ μ^-$, $K^- \to μ^- \barν_μe^+ e^-$, and $K^- \to μ^- \barν_μμ^+ μ^-$, thereby providing first-principles Standard Model predictions against which existing and upcoming measurements can be directly compared. A detailed phenomenological analysis of the decay rates and associated observables is presented in a companion paper [2].

Weak decays of charged kaons with an additional lepton-antilepton pair, $K^- \to \ell^- \barν_\ell \ell'^{+} \ell'^{-}$ ($K_{\ell2\ell'}$), are suppressed at order $O(G_{F}^{2}α_{\rm em}^{2})$ in the Standard Model (SM) and provide sensitive probes of its flavour structure, as well as independent determinations of the Cabibbo angle $|V_{us}|$. In this Letter we present the SM predictions for all four channels with $\ell,\ell' =e,μ$, based on the first complete lattice QCD calculation of the structure-dependent form factors reported in a companion paper [1]. Using the PDG value [2] $|V_{us}|^{\rm PDG}=0.22431(85)$, we obtain branching fractions with controlled uncertainties and precisions ranging from $2\%$ to $7\%$, depending on the channel. For the three modes with published measurements, our results agree with experiment. For the $K_{\mu2μ}$ mode, for which no published experimental result is available, we compare our prediction with the preliminary NA62 result, finding agreement at the $1.4σ$ level. Conversely, the measured decay rates can be used together with our results to extract $|V_{us}|$ from these modes. A weighted average over the two most precise channels, $K_{\mu2e}$ and $K_{\mu2μ}$, yields $|V_{us}|=0.2283(42)$, corresponding to a $1.8\%$ determination. These results pave the way for using $K_{\ell2\ell'}$ decays as precision probes of the SM.

Dwarf galaxies in the Local Group offer a way to test dark matter (DM) models against stellar kinematic data. In this work, we study degenerate fermionic DM in two cases: the standard non-interacting Fermi gas, and an interacting degenerate DM fluid described by a phenomenological equation of state motivated by interacting Fermi systems. These interactions modify the compressibility of the DM fluid and, in some regions of parameter space, lead to mechanically unstable branches that must be treated through a Maxwell construction. We solve the corresponding non-relativistic hydrostatic equations consistently and compute the line-of-sight velocity-dispersion profiles using the spherical Jeans equation. We then perform MCMC fits to eight classical Milky Way dwarf spheroidal galaxies. The data favor DM fermion masses in the range $100$--$300\,{\rm eV}$. We find that the interacting and non-interacting equations of state give broadly similar posterior distributions for the fermion mass, central density, and stellar anisotropy. Current data therefore do not strongly prefer an interacting equation of state over the free degenerate Fermi-gas, thereby excluding large deviations from the non-interacting limit.

By analyzing a sample of 20.3 fb$^{-1}$ of $e^+e^-$ annihilation data collected at the center-of-mass energy of 3.773~GeV with the BESIII detector, we have made a first measurement of the absolute branching fractions of the radiative decays $D^0\toγ\bar K^{*0}$ and $D^0\toγφ$ to be $(3.81 \pm 0.18_{\rm stat.} \pm 0.20_{\rm syst.})\times 10^{-4}$ and $(2.51 \pm 0.44_{\rm stat.} \pm 0.11_{\rm syst.})\times 10^{-5}$, respectively. The statistical significances of $D^0\toγ\bar K^{*0}$ and $D^0\toγφ$ are $26.8σ$ and $7.9σ$, respectively. The obtained branching fractions are consistent with the corresponding world average values. In addition, the measured $C\!P$ asymmetry $\mathcal{A}_{C\!P}(D^0\toγ\bar K^{*0})=(-0.7\pm5.0_{\rm stat.} \pm4.1_{\rm syst.})\%$ is consistent with $C\!P$ conservation.

We investigate the emergence of approximate neutrino texture structures in the minimal scotogenic model through large-scale Casas--Ibarra parameter scans subject to lepton flavor violation and dark matter constraints. We demonstrate that approximate suppressions can dynamically emerge from phenomenological consistency conditions. The interplay between relic density requirements, radiative neutrino mass generation, and lepton flavor violating observables induces a nontrivial flavor geometry in parameter space. Particular suppressions in the $(eμ)$ and $(eτ)$ sectors arise naturally, while diagonal entries strongly resist cancellation. We further compare normal and inverted mass hierarchies, analyze reduced versus full Casas--Ibarra geometries, and identify approximate scaling relations linking dark matter and flavor observables. Our results suggest that emergent flavor structures may represent dynamical consequences of radiative neutrino mass generation rather than externally imposed flavor symmetries.

Real critical systems, such as uniaxial ferromagnets in the 3d Ising universality class, are constrained by boundaries and subject to random couplings. We consider the Wilson-Fisher fixed point in $4-ε$ dimensions subject to a random magnetic field localized on a two-dimensional surface, which becomes co-dimension 1 in the physical $ε\to1$ limit. Using the replica method for the disordered field, we find that the ordinary boundary condition is stable under disorder but also discover a non-trivial ``dirty" boundary condition which can be reached by tuning the disorder strength or the local temperature. We also investigate the logarithmic structure of the defect spectrum and how it emerges via the replica formalism.

Classical A-polynomials $A(\ell,m)$ define constraints on coordinates $\ell$ and $m$ in $SL(2,\mathbb{C})$ (a complexification of $SU(2)$) character varieties associated to knot complements $S^3\setminus K$. Quantum A-polynomials $\hat A(\hat \ell,\hat m)$ are difference operators annihilating Jones polynomials believed to represent wave functions of 3d Chern-Simons theory with gauge group $SU(2)$ on a toroidal pipe surrounding the knot $K$ strand -- a boundary of the knot complements $S^3\setminus K$. We suggest a construction of classical shaded A-polynomials $A_a(\ell_b,m_c)$ associated to Lie groups $SU(N)$. We exploit a formalism of Clebsh-Gordan (CG) chords, where indices $a$, $b$, $c$ run over $1,\ldots,N-1$. CG chords have a natural interpretation in terms of 2d CFTs of WZW type, or, alternatively, in terms of quantum group $U_q(\mathfrak{su}_N)$. In the case of $\mathfrak{su}_2$ CG chords could be associated to Reeb chords in a knot contact homology (KCH) framework. KCH suggests its own analogue of A-polynomials known as augmentation polynomials allowed to have extra spurious roots in principle. Yet the CG chord formalism could be easily extended to arbitrary $\mathfrak{su}_N$ allowing us to generalize the construction of A(ugmentation)-polynomials to arbitrary $\mathfrak{su}_N$ and arbitrary representation as well. Primarily we aim at classical A-polynomials by considering a double scaling limit when $q=e^{\hbar}$, $\hbar\to 0$ and the representations are huge, in particular, highest weight vector components $w_i\to \infty$ so that $\hbar w_i\sim m_i$ remain finite. Still we expect the presented techniques would be helpful in deriving quantum A-polynomials for arbitrary Lie (super)algebras $\mathfrak{g}$. Also we discuss explicit examples of A-polynomials for knots $3_1$, $4_1$ and $5_1$ for $\mathfrak{g}=\mathfrak{su}_3$.

The ABCStar is a mixed-signal front-end readout ASIC for the strips sensor portion of the ATLAS ITk detector being developed as part of the High-Luminosity LHC upgrade. In pre-production testing, a subtle design flaw was uncovered in the ABCStar that was reducing wafer yields in some manufactured lots from the expected 90% to as low as 2%. The root cause was determined to be a timing issue in the logic synthesized to control previously silicon proven memory blocks re-used for this ASIC. The solutions proposed included manufacturing process changes by the wafer foundry, changes to the operating parameters for the ABCStar in the detector, and the possibility that a redesign might be required. The two mitigation efforts were undertaken in parallel, with the process modification route a less desirable solution since already manufactured wafers would need to be scrapped in favour of the new ones. Based on a knowledge of the existing process, and testing done on the worst performing wafers, it was proposed that raising the core operating voltage of the ABCStar from 1.20V to 1.25V could address the timing issue by sufficiently speeding up its transistors. An extensive testing program that included the effects of temperature and radiation expected over the lifetime of the ITk detector was conducted to validate that approach. Those tests and studies proved that even the worst performing wafers would have yields over 80% with the 1.25V core voltage, and neither the modified process nor redesign would be required for ensuring reliable operation of the ITk. Based on testing, a further timing mitigation was implemented to provide an additional margin of reliability by increasing the duty cycle of the clock to the ABCStar. Testing of all ABCStar wafers has been completed and the production of the detector modules using these ASICs is now well underway as a result of the efforts detailed herein.

We discuss the role of fully heavy tetraquarks in ultraperipheral collisions $AA\to AA\, J/ψJ/ψ$ and $AA \to AA\, γγ$. Two-photon couplings to scalar and tensor tetraquarks are considered. We use relatively recent results of four-body calculation of fully heavy tetraquark wave function within the extended relativized quark model. The corresponding radiative decay widths for different tetraquark states are evaluated using NRQCD factorisation, with LDMEs extracted from the four-body wave functions at the origin. The results are collected in tables. The cross sections for production of pairs of $J/ψ$ mesons and diphotons in UPC of $^{208}Pb + {^{208}Pb}$ collisions are presented. While the couplings for $T_{4c}\left(0^{++}, 2^{++}\right) \to γγ$ are calculated based on the model wave functions, simplified couplings are used for $T_{4c}\left(0^{++}, 2^{++}\right) \to J/ψJ/ψ$. When calculating the energy dependence of the resonant $γγ\to J/ψJ/ψ$ and $γγ\to γγ$ cross section, we employ the total decay widths measured at $Γ_{\rm{tot}}=0.446\,\rm{GeV}$ for $X(6600)$ while $Γ_{\rm{tot}}=0.135\,\rm{GeV}$ for $X(6900)$ in latest CMS data. The resonant terms are compared with continuum contributions for both considered channels. While for the $J/ψJ/ψ$ channel the resonant contributions are larger than continuum ones, for the $γγ$ channels the situation is reversed. The latter result is in clear disagreement with the result obtained from the näive use of vector dominance picture.

We propose a hybrid inflation model where a pseudo-Nambu-Goldstone boson inflaton couples to $N$ waterfall scalar fields respecting a $Z_N$ symmetry. We identify the phases for the inflation and the consequent waterfall transition, concretely, in $Z_2$, $Z_3$ and $Z_4$ cases. From the Coleman-Weinberg potential for the inflaton, we show that the quadratically divergent corrections coming from the waterfall sector are cancelled due to the $Z_N$ symmetry, while the logarithmically divergent corrections are absent only for $N>2$, ensuring the radiative stability of the inflaton potential. We show the parameter space for a successful inflation with the loop-corrected inflaton potential in each model and compare the results between different discrete symmetries. We further analyze the vacuum structure of the models and the reheating process due to the $Z_N$-invariant Higgs-portal couplings for the waterfall fields. We find that the reheating temperature can be smaller than the mass of the waterfall field condensate such that the $Z_N$ symmetry is not restored after reheating and there is no domain wall problem in the models. We also comment on the possibility of multi-component dark matter from the $Z_N$ partners of the waterfall field condensate.

We study the Lorentzian Wetterich Renormalization Group (RG) flow equation for interacting quantum fields on curved backgrounds within the framework of perturbative Algebraic Quantum Field Theory (pAQFT). Specifically, we consider two classes of models: two mutually interacting scalar fields on globally hyperbolic spacetimes without boundary and, under the further assumption that the underlying background is spin, self-interacting Dirac fields. In both cases, we derive the corresponding RG flow equations within a Local Potential Approximation and compute the beta functions for the relevant couplings. For the scalar model, we also discuss an asymmetric interaction potential which is formally reminiscent of the Martin-Siggia-Rose description of a stochastic dynamics, thereby indicating a possible connection between Lorentzian algebraic RG methods [DDP+24] and stochastic field-theoretic models, [Duc25]. In addition, we address the local well-posedness of the resulting flow equations. Adapting the strategy detailed in [DP23] and based on the the Nash-Moser theorem, we prove local existence and uniqueness of solutions for both the scalar and the Dirac models.

It is known that the Minkowski vacuum appears as a thermal medium to an accelerated observer due to the renowned Unruh effect. More recently, it has been shown that at least for lower-spin fields this medium also exhibits a non-zero "entanglement" shear viscosity, which saturates the fundamental Kovtun-Son-Starinets (KSS) bound. We test the universality of this result for higher spins by computing the entanglement viscosity for spin-3/2 fields within the Rarita-Schwinger-Adler (RSA) theory. Strikingly, we obtain a negative viscosity. However, computing the entropy density using the modular Hamiltonian expansion method, we find it is also negative, and the viscosity to entropy ratio saturates the KSS bound. To clarify the origin of the negativity, we use another approach of Zubarev density operator, which gives positive entropy. We also show that RSA theory has many features of a conformal field theory.

Global fits of Beyond the Standard Model (BSM) physics often involve a two-way interplay between theory and experiment. Theoretical models provide guidance for experimental searches, while experimental results, in turn, constrain theoretical frameworks. A crucial aspect of this feedback loop is the direct inclusion of measurements and exclusion limits ``online'' global fits, i.e. during the parameter scans aspects of the global fits. However, incorporating the Large Hadron Collider (LHC) limits into such analyses has been computationally prohibitive, often due to time taken per parameter point exceeding the scales acceptable for global fit frameworks. In this study, we show that LHC limits can be incorporated ``online'' global fits by leveraging approximations derived from symbolic regression techniques. We utilize a dataset of ATLAS constraints from searches for electroweakino productions to derive a mathematical expression capable of classifying the phenomenological Minimal Supersymmetric Standard Model (pMSSM) parameter space as allowed or excluded. This is subsequently incorporated for making a global fit of the pMSSM to data, including the LHC Run-2 limits.

We give a pedagogical introduction to Linearized Soliton Perturbation Theory (LSPT), a new and efficient tool for calculations involving quantum solitons. It is a Hamiltonian approach with a focus on explicitly constructing the soliton states. These states are squeezed, coherent states plus perturbative corrections. We will describe multi-loop corrections to states and their masses. An inner product suitable for non-normalizable momentum eigenstates will be introduced and applied to kink-meson scattering. We will also discuss domain wall solitons.

Neutron star (NS) is one of the most promising astrophysical targets to probe non-gravitational interaction of dark matter (DM) with visible matter. Their compactness makes them an ideal object which can capture particle DM efficiently over its lifetime using the DM-nucleon scattering cross-section. If DM particles are bosonic, then the captured DM population may form a Bose-Einstein condensate at the center of the NS, increasing the DM density significantly. In this work, we study the phenomenology of such scenario with enhanced DM annihilation rate due to the increased density in a condensate. The enhanced DM annihilation makes the NS surface `hotter' than in the standard cooling scenario. We show that the annihilation rate is enhanced by a factor of $\mathcal{O}(10^{15}-10^{20})$ if DM forms a condensate, and DM with freeze-in value annihilation cross-section can heat up the NS to higher temperatures, bringing it within the reach of James Webb Space Telescope. It also allows us to probe DM-nucleon scattering cross section within the neutrino fog regime which will complement the terrestrial direct detection searches. Moreover, the enhanced annihilation from the condensate changes the lower limits on s-wave DM annihilation cross-section for capture-annihilation equilibrium and the formation of a black hole inside the NS. Finally, we show an example of a scalar DM model where such small annihilation and DM-nucleon scattering cross sections can generically arise.

We present a four-dimensional equation of state for strongly interacting matter at finite temperature and conserved charge densities, constructed using a deep neural network. It is designed for direct use in hybrid models of relativistic heavy-ion collisions: it reproduces hadron resonance gas thermodynamics at typical particlization scales, is consistent with lattice QCD at low baryon chemical potential, and extrapolates into the high-density region inaccessible to either approach, which is precisely the regime targeted by RHIC BES, FAIR, HADES, and CBM. Thermodynamic consistency throughout the full phase space is enforced via a physics-informed loss function. We demonstrate the developed equation of state by implementing it at zero net strangeness and fixed electric-to-baryon charge ratio within the integrated hydrokinetic model.

The recent James Webb Space Telescope (JWST) observations reported the unexpectedly large abundance of massive galaxies with stellar masses of $\sim 10^{10}~M_{\odot}$ at high redshifts $z \simeq 6.5 - 9$ compared with the prediction of the standard $Λ$CDM model. As a possible solution to the tension, we consider a blue-tilted spectrum of density perturbations with a positive running. We find that, for $α_s \simeq 0.2$ and $β_s \simeq 0.2$, a joint analysis with CMB observations shows that the tension can be resolved at the 1$σ$ confidence level. Such a blue-tilted spectrum is also plausible from the perspective of primordial black hole formation on much smaller scales in the early Universe.

Chiral EFT yields singular potentials that require regularization and renormalization when implemented in a dynamical equation such as the Lippmann--Schwinger equation. We employ two different approaches, renormalization with contact terms -- as is most commonly done in chiral EFT -- and the exact N/D method with multiple subtractions. We start with a toy model in which we can control the finite-range expansion of the potential, treating the full potential as the `exact' theory. To assess the statistical consistency of the approaches with the full theory, we use the bootstrap technique. We apply the same framework to study the consistency of chiral EFT at LO and NLO with the Granada phase-shift analysis in the $^1S_0$ two-nucleon partial wave. Our results show that the NLO potential significantly extends the energy range over which the theory remains valid.

We present an implementation of the MAcNLOPS matching prescription for $pp \to ZZ$ production in a MadGraph5_aMC@NLO + Pythia8 setup. Starting from a standard MC@NLO event sample, negative H events are removed and compensated by a veto applied to the first shower emission of the S events. The implementation is validated against MC@NLO for radiation-sensitive and inclusive diboson observables. Agreement is found up to a rather small power-suppressed contribution affecting the very low-pT region. The method removes all negative H weights with negligible additional computational cost, while negative S weights are left unchanged, showing that MAcNLOPS is a promising alternative to MC@NLO with a reduced fraction of negative weights.

In this work, a comprehensive analysis for processes related to $b\to c\bar{u}q~(q=d, s)$ transitions are carried out, including new physics contributions. In light of a recent tension between branching fractions for $B_{(s)}\to D_{(s)}^{(*)}M$ ($M$ represents a meson) decays in the QCD factorization approach and relevant experimental results, phenomenological constraints on complex-valued Wilson coeffients are discussed. Analyzed observables contain direct CP asymmetry ($A_{\text{CP}}$) in $B^-\to D^0π^-$ decays and $γ/φ_3$, one of the angles in the unitarity triangle, combined with others from $τ_{B^+}/τ_{B_d}$, $ΔΓ_{q}/Γ_q$, and $A_{\rm SL}^{q}~(q=d, s)$. We constrain the complex Wilson coefficients at $1σ$ and $2σ$ levels under color-singlet and color-rearranged scenarios. These constraints yield correlated predictions for $ΔΓ_d/Γ_d$, $A_{\rm SL}^d$ and $A_{\text{CP}}$.

We investigate semileptonic sum rules in heavy-to-light charm decays, motivated by analogous relations in $b \to c$ and $b \to u$ transitions. Focusing on the $c \to d\overline{\ell}ν$ decays, $D \to π\overline{\ell}ν$, $D \to ρ\overline{\ell}ν$, and $Λ_c \to n\overline{\ell}ν$, we examine a relation among their lepton-flavor universality ratios $R_H^{μe}$. Although the charm sum rule is less precise than the relations in bottom-hadron decays, current low-energy and high-$p_T$ constraints on new physics restrict the actual deviation from the relation to below the percent level. The relation can therefore provide a useful consistency check of charm semileptonic measurements. As an application, we derive a prediction for the yet-unmeasured ratio $R_n^{μe}$ in $Λ_c \to n\overline{\ell}ν$.

We study lepton-flavor-violating (LFV) decays of a heavy Higgs boson, $H \to μτ$, in the Type-III two-Higgs-doublet model by recasting the CMS search at $\sqrt{s} = 13$ TeV with 35.9 fb$^{-1}$ using fast detector simulation in the mass range 200-450 GeV. We develop a deep neural network (DNN) classifier trained on final-state kinematic variables that, with mass-dependent threshold optimization, reduces the expected 95% CL upper limits on the signal cross section by 42-46% in the 0-jet channel and 36-40% in the 1-jet channel relative to the standard collinear mass ($M_\mathrm{col}$) baseline. We apply SHAP interpretability analysis to identify the visible mass $m_\mathrm{vis}$ as one of the dominant discriminating feature, reflecting the characteristic neutrino momentum fraction of the $τ$ decay. We show that supplementing the $M_\mathrm{col}$ analysis with a simplified mass-dependent pre-selection, $m_\mathrm{vis} < f \cdot m_H$ with $f = 0.7$ (0-jet) and $f = 0.8$ (1-jet), consistently improves the sensitivity over the $M_\mathrm{col}$-only baseline without requiring multivariate infrastructure. In addition, a DNN regression model trained to predict the ratio $m_H/M_\mathrm{col}$ corrects the systematic prediction bias inherent in the collinear approximation, maintaining an absolute mass prediction error below 1 GeV for signals up to 400 GeV and improving the mass resolution by 12% (0-jet) and 21% (1-jet) at $m_H = 450$ GeV. These results demonstrate a clear path toward significantly enhanced sensitivity in LFV Higgs searches at the LHC.

This talk introduces a Cartan-geometric framework for generalised geometries governed by a differential graded Lie algebra. In contrast to ordinary Cartan geometry, the tangent bundle is extended and qu both a global duality group and a local gauge group. This framework provides a systematic construction of generalised connections and their torsion and curvature tensors for generic generalised geometries. We also review the realisation of these algebraic structures on the phase space of branes in M-theory.

Real-time jet tagging is critical for identifying short-lived particle decays in the high-throughput detectors of the Large Hadron Collider, where real-time trigger systems responsible for deciding which collision events to store impose strict latency and accuracy constraints. While transformer architectures achieve the highest jet tagging accuracy when compute is unconstrained, their quadratic self-attention cost makes inference restrictive on trigger budget. Existing efficient variants reduce the computational cost, but hinder the classification performance. To address this limitation, we introduce the Patch Hierarchical Attention Transformer (PHAT-JeT), which combines two mechanisms: a physics-inspired geometric message-passing module that encodes local detector-plane structure, and a hierarchical patch-based attention scheme that computes exact attention within small particle groups while preserving global context through lightweight patch-token communication. Within a restricted budget, PHAT-JeT achieves state-of-the-art accuracy and background rejection among all resource-constrained jet tagging models on four benchmarks (\textsc{hls4ml}, JetClass, Top Tagging, and Quark--Gluon). Our code is available at https://github.com/aaronw5/PHAT-JeT.

Defects are both physically rich objects and powerful tools in modern quantum field theory. They are extended operators, such as boundaries, impurities, and probe particles, embedded in many-body systems. In this dissertation, we study the universal aspects of defect dynamics from the perspective of symmetry principles. We bring together several themes, including defect renormalization group flows, effective string theory, and impurities in atomic quantum gases.

The relation $M_H^2\simeq M_ZM_t$, previously proposed as a non-trivial Higgs mass coincidence, is reconsidered with present electroweak inputs and with a scheme-consistent matching analysis. With the 2025 PDG values for $M_Z$, $M_W$ and $M_H$, and the ATLAS-CMS direct top-mass combination, the pole-level ratio is $ρ_{Zt}=M_ZM_t/M_H^2=1.00362\pm0.00261$. Thus an exact pole-level geometric relation predicts either $M_H=125.426\pm0.120\,\mathrm{GeV}$ or $M_t=171.898\pm0.302\,\mathrm{GeV}$, which is still a $1.4σ$ test rather than an exclusion. By contrast, the companion arithmetic relation gives $ρ_{Wt}=(M_W+M_t)/(2M_H)=1.00994\pm0.00159$ and is not a viable exact mass sum rule. We then evaluate the complete NNLO weak-scale $\overline{\mathrm{MS}}$ matching formulae at $μ=M_t$. In the standard convention one obtains $\widehatρ_{Zt}(M_t)=\sqrt{g_2^2+g_Y^2}\,y_t/(4\sqrt2λ)=0.96714\pm0.00361$. Consequently, the exact running-coupling boundary condition $λ=g_Zy_t/(4\sqrt2)$ at the top scale would predict $M_H=123.19\pm0.20\,\mathrm{GeV}$, or equivalently $M_t=177.81\pm0.50\,\mathrm{GeV}$ when $M_H$ is held fixed. This is incompatible with the measured point. A possible symmetry explanation must therefore act on pole-level threshold quantities, or provide a finite matching factor $κ_{\rm th}=1.0340\pm0.0039$ at the electroweak scale. We formulate this requirement as a target for custodial/top-Higgs or triality-like symmetry extensions.

We develop a framework for indirect discovery in the Standard Model Effective Field Theory (SMEFT) based on Bayesian model selection over operator subsets. We argue that SMEFT should be understood as a structured space of competing hypotheses rather than a single high-dimensional model, with each operator subset corresponding to a physically distinct low-energy realisation of new dynamics. Bayesian inference is applied at the level of model space itself, assigning posterior probabilities to operator subsets and marginal inclusion probabilities to individual operators. A genetic algorithm efficiently navigates the high-dimensional discrete model space, concentrating evaluations in the high-posterior region, while the Bayesian Information Criterion provides a tractable approximation to the Bayesian evidence. We apply this framework to a dataset comprising electroweak precision observables from LEP and Higgs, top-quark, and diboson measurements from LHC Run 2, at both linear and quadratic order in the Wilson coefficients, with one-loop renormalisation group evolution systematically included. The analysis finds no statistically significant evidence for any departure from the SM, and demonstrates that Bayesian Model Average posteriors on Wilson coefficients carry substantially improved characterisation potential compared to traditional global fits. The operator correlation matrix encodes the relational structure of the model posterior, identifying operator pairs that co-appear in high-posterior models and flat directions where additional measurements would be most valuable. The sensitivity of all results to the choice of matching scale $μ_0$ is assessed, and its promotion to a continuous parameter of inference is identified as a natural extension of the framework.

We examine the potential for a 10~TeV lepton collider to carry out precision measurements of the W boson mass and W boson couplings strength, i.e. the CKM matrix elements. We consider the several W boson production mechanisms and focus on the most copious at 10~TeV, that is effective $γW \to W$, a process viable at both opposite sign and same-sign leptonic colliders. We find that the leptonic W decay channel can hardly be competitive with present determinations, due to lack of rate. The hadronic channel has potential to improve over the current $\simeq$10~MeV from measurements at hadron colliders, motivating detector developments towards high-precision hadronic energy measurements. We find that the precision understanding of the detector response to hadrons can also lead to a determination of the CKM matrix elements. We expect determination of CKM matrix elements surpassing by far the present precision for couplings involving heavy quarks, notably $V_{cb}$, avoiding the present bottle-necks due to poor knowledge of hadronic matrix elements needed in low energy extractions of CKM matrix elements. Our findings motivate detector developments towards high-precision hadronic energy measurements and flavor tagging.

Nucleon decay searches provide uniquely sensitive probes of baryon number violation and physics beyond the Standard Model. We propose a new class of nucleon decay observables involving long-lived particles (LLPs), characterized by spatially separated but temporally correlated "echo" vertices not captured by conventional prompt searches. Focusing on vector LLPs, we construct effective operators and ultraviolet realizations, and show that Super-Kamiokande, Hyper-Kamiokande and JUNO can achieve geometric acceptances approaching 80% over a broad range of LLP decay lengths. Echo signatures could in principle arise from any visibly decaying LLP.

We revisit the computation of four-point wavefunction coefficients for external conformally coupled scalars exchanging a particle of general mass and spin. Much of the phenomenology of cosmological collider physics in the near-de Sitter limit follows from this function. Computing it in detail is a central challenge in the cosmological bootstrap. Using the cosmological Grassmannian, we write this correlator in closed form using hypergeometric functions and Legendre polynomials. We achieve this by writing the standard bootstrap differential equation using the Plücker coordinates of the Grassmannian, and using the basis of Mandelstam invariants. The correlator in the s-channel can be written in terms of a hypergeometric function of the S Mandelstam, while the spin information appears as an overall Legendre polynomial factor that also depends on the other Mandelstams. We fix the boundary conditions by first demanding the absence of unphysical singularities, and by further matching to kinematic limits of the momentum-space wavefunction. Our formulae in Grassmannian space are much simpler than their counterparts in momentum space, demonstrating another useful application of the Grassmannian as a kinematic space for cosmology.

The chiral Lagrangian is a cornerstone of modern particle physics, offering a systematic and quantitative description of low-energy pions. Using tools from the modern scattering amplitudes program, we show that consistent multiparticle dynamics impose novel constraints on the coupling constants of this theory. In the planar limit, these constraints imply that certain Wilson coefficients of the chiral Lagrangian are bounded from below by the chiral anomaly. Our results reveal a subtle connection between the anomalous and nonanomalous sectors of the underlying strong interactions, while introducing a novel formulation of multipositivity bounds that holds for any planar tree-level theory.

Irreversibility theorems -- such as the $A$-theorem -- establish a hierarchy among fixed points of the renormalization group flow. The strongest thesis of this type of theorems would be that there exists a scalar function $A$ (generally suggested by the topological Weyl anomaly) and a positive definite metric $G_{IJ}$ in the space of couplings such that the renormalization group flow satisfies a gradient equation, $\partial_I A= G_{IJ}β^J$, in which case $A$ is locally monotonic along the flow. In this paper we consider the long-range multiscalar $φ^4$ theory, a theory without a local energy-momentum tensor that is unitary in $d=2,3$ and that is believed to be conformally invariant at fixed points, and show that its renormalization group flow satisfies the gradient structure up to the third loop order in the coupling. We also show that $A$ and $G_{IJ}$ can be matched to the leading nontrivial order with the sphere free-energy $\tilde{F}$ and Zamolodchikov's metric $C_{IJ}$ of the corresponding conformal theory concentrating on the examples of the long-range vector $O(N)$ and hypercubic $H_N$ models. Our results imply a perturbative proof of the $\tilde{F}$-theorem at the leading nontrivial order. We conclude the paper discussing briefly whether this result should hold to the next orders in perturbation theory.

We present a non-perturbative multiplicative renormalization program for the massive gluon fields. This has been done within the previously formulated the mass gap approach to QCD. It is based on a new insights into its ground state true dynamical and gauge structures. Our approach makes it possible for gluons to acquire mass dynamically. The corresponding full gluon propagator has been investigated in full details. Its asymptotic properties have been analysed, including the perturbation theory limit. The peculiarities of the mass-shell structure of the full massive gluon propagator has been discussed. The inconsistency of the canonical gauge in QCD is fixed. Our approach does not allow the massive gluons to be the mass-shell objects. This prevents them to appear in the physical spectrum (confinement of massive gluon states). The massive gluons may exist in the vacuum or inside hadrons only. Expressions in Euclidean metric for the lattice simulations are also present. We have also shown that the massive solution has a correct limit to the free massless gluon propagator, when the exactly defined gluon pole mass is to be formally put zero.

We return to and refine Zwiebach's formulation of closed string field theory (CSFT) built around non-critical backgrounds [1,2], restricting our attention to genus zero. The structure involves a special string state $F$ that encodes the failure of worldsheet BRST invariance, and a metric-dependent descent operator $\mathcal{B}$ adapted to the Weyl frame. We construct the mixed moduli spaces needed for the classical BV action, prove their existence, and extend the Sen-Zwiebach background independence argument to first order off of the conformal locus. We apply the formalism to the mildest deviation away from criticality - worldsheet CFTs with nonzero central charge: we consider both D=26-$ε$ dimensional flat space and linear dilaton profiles in bosonic string theory, focusing for simplicity on building solutions that depend on only one of the D dimensions.

We propose a reformulation of the conformal perturbation theory of the correlation functions in $J\bar{J}$-deformed CFTs as a dressing on the deformed operators, that matches both bare and renormalized perturbation theory. The key is to use the Riemann bilinear identity to convert the deformation into a dressing and a large-cycle integral for higher genus. Based on the proposal, we calculate the deformation of partition functions on the torus and higher genus Riemann surfaces, which can be written as kernel integrals that preserve modular invariance or covariance. We also calculate the flow of the conformal weights and conserved charges along the deformation. Based on this flow and the modular $S$-transformation, we propose a criterion for constructing dressed operators. We test our formalism and results by studying the $O(2, 2)$ theories and strings on the TsT background.

Bayesian inference provides a natural framework for updating knowledge as new information becomes available, often in a sequential manner by incorporating datasets in stages or reusing previous posteriors as priors. In practice, this is commonly implemented using a factorized update in which datasets are treated as conditionally independent. When datasets are statistically correlated, however, this approximation becomes inconsistent with the joint likelihood and can lead to biased posterior estimates. In this work, we investigate this issue in a controlled setting using pseudo-data with a tunable covariance structure. We compare joint inference, factorized sequential updating, and a formulation based on the exact conditional likelihood. We show that factorized updates reproduce the joint posterior only in the limit of conditional independence, and otherwise lead to systematic deviations that grow with the correlation strength, while conditional updates remain consistent with the joint result. To interpret these deviations, we introduce an information decomposition that separates contributions into components that are new and components that are redundant across datasets. We show that correlations induce a structured, parameter-dependent redistribution of information, governed by the overlap of dataset sensitivities. The resulting mismatch between marginal and conditional information quantitatively explains the observed deviations. These results provide a practical diagnostic for assessing the consistency of sequential Bayesian inference with correlated datasets and highlight the need for a consistent treatment of correlations within a common probabilistic framework.

APOGEE and Gaia data have revealed that the Milky Way's structure appears to have evolved through three distinct kinematic phases. First, at early cosmic times, the Milky Way was a disordered protogalaxy, which subsequently "spun up" to a second kinematic phase marked by star formation occurring in a rotating, thick stellar disk. The thick disk phase later transitioned to a third (and final) phase with star formation occurring in a cold, thin stellar disk. In this paper, we use a suite of FIRE-2 simulations of Milky Way-mass galaxies to demonstrate that the same three phases arise in our cosmological zoom-in simulations, and study their physical origin. In all of our galaxies, the early disordered phase occurs when the rate of cool gas ($T \leq 10^4$ K) converting into stars is low, the star formation rate is bursty, and the baryonic mass "sloshes" within the host potential with respect to the center of mass motion. The gas in the galaxy begins to spin coherently after the sloshing phase ends, followed by the spin-up of young stars. The central potential of the galaxy is least concentrated just prior to gas spin-up. This second, thick disk phase coincides with a period when the rate of cool gas converting into stars is highest, even though the star formation rate remains bursty in this phase. The final transition to the thin disk phase occurs when the inner circumgalactic medium virializes. The thin disk phase is associated with a time of steady star formation and intermediate rates of cool gas converting into stars. Mergers do not appear to play a defining role in driving transitions between the three phases. The condition for the formation of a thick disk appears to be fairly minimal: a stable center of mass motion. The formation of a thin disk requires more: gas must accrete slowly enough for its angular momentum to mix and become coherent prior to joining the galaxy.

The interior crust and much of the liquid core of neutron stars is believed to be a quantum liquid mixture of neutron and proton superfluids and a relativistic electron liquid. Quantized vortices in the neutron superfluid and quantized flux lines in the proton superconductor are topological defects of these hadronic condensates. I consider the formation of the superfluid state in young neutron stars under non-equilibrium conditions imposed by the neutrino cooling rate. The nonequilibrium phase transition implies that the onset of superfluidity is accompanied by the generation of quantized vortices based on the mechanism envisioned by Kibble in the context cosmic string formation in an evolutionary models of an expanding universe, and further developed by Zurek for nonequilibrium phase transitions in quantum liquids such as \Hefour. I discuss the Kibble-Zurek mechanism (KZM) and scaling relations for topological defect formation starting from the Cooper pair fluctuation propagator for temperatures approaching $T_c$. I then calculate the predicted vortex densities based on Urca and modified Urca cooling mechanisms in the cores of neutron stars for several models of the superfluid gap and transition temperature of the interior neutron superfluid. In all cases studied the KZM leads to a large density of topological defects in the condensate phase, which in 3D form a random network of vortex lines and loops, i.e. the generation of quantum turbulence.

We employ a Minimum Spanning Tree (MST) approach to characterize the spatial distribution and mass segregation of compact millimeter continuum sources within the Central Molecular Zone (CMZ) of the Milky Way. We use a modified form of the complete version of the 1.3 mm dust continuum catalog from the CMZoom survey, which identifies 685 compact sources with typical effective radii of $\sim0.1$ pc. For 22 of 35 CMZ clouds, we calculate the thermal and turbulent Jeans lengths and masses, and determine that compact source separations, as well as compact source masses, are more consistent with thermal fragmentation at $\sim0.1$ pc size scales. We construct the mass segregation ratios for compact sources in 17 CMZ clouds and determine that 5 of the analyzed clouds display some form of mass segregation ($Λ_{MSR} > 1.5$), while the remaining clouds show either inverse mass segregation ($Λ_{MSR} < 0.75$), or no evidence of true mass segregation ($0.75 < Λ_{MSR} < 1.5$). Finally, we find that although some actively star-forming clouds do exhibit mass segregation, other similarly active clouds do not, indicating an unclear correlation with evolutionary stage for star forming clouds in the CMZ, given the current available data.

Cosmic rays (CRs) are a ubiquitous non-thermal component of the interstellar medium (ISM). A data-driven three-dimensional (3D) map of their distribution is essential for understanding CR transport and constraining the spatial distribution of their sources. In this work, we reconstructed the 3D spatial distribution of the Galactic cosmic-ray proton (CRp) density. We model the diffuse gamma-ray emission arising from inelastic hadronic interactions between CRps and interstellar gas. Using a map of dust-correlated diffuse gamma-ray emission based on ten years of Fermi-LAT observations together with a three-dimensional gas density model, we infer the spatial CRp distribution through a morphological matching approach. The logarithmic CRp density field is described by a Gaussian process defined on a spherical-times-radial grid, while both the field and its correlation structure are inferred simultaneously using Iterative Charted Refinement. The posterior distribution of the reconstructed 3D CRp density field is approximated using geometric variational inference. The reconstructed CRp density exhibits a smooth but spatially structured distribution with a limited dynamical range across the Galactic disk. We find a moderate enhancement of the CRp density toward the inner Galaxy. The inferred normalization at the Solar position is consistent with local CR measurements by the AMS-02 instrument.

The behavior of magnetic field lines in a turbulent plasma is a key property of the medium, with important consequences for plasma dynamics and charged-particle transport. We study the diffusion properties of magnetic field lines in synthetic turbulence featuring different polarization configurations for the magnetic perturbations, as prescribed by the existing magnetohydrodynamic modes (namely, Alfvénic and magnetosonic). These turbulent field realizations are then compared with the isotropic (or, random) polarization case, which is the one typically adopted in the literature. We construct polarized synthetic turbulence simulations and study the properties of field lines through the running diffusion coefficient. Our key findings can be summarized as follow: (i) field line wandering is strongly dependent on polarization configurations, (ii) we unveil that the sub-diffusive phase of field line is highly dependent on the polarization and is well reproduced by theoretical predictions based on Corrsin's hypothesis in the low turbulence level regime, (iii) in particular the scaling of the asymptotic diffusion coefficient in magnetosonic-like polarization is $(δB/B)^4$ at odd with the $(δB/B)^2$ scaling found in the quasi-linear regime for random polarization, (iv) interestingly we note that the subdiffusive phase of field line transport in the magnetosonic-like polarization follows closely the one observed in recent high resolution MHD turbulence simulations, we end giving a word of caution when FL transport is investigated in such simulations.

We present measurements of K-shell x-ray emission following charge exchange of fully ionized argon with various neutral gaseous targets at small collision energies inside an electron beam ion trap. We also resolve the principal quantum number of electron capture in extreme-ultraviolet spectra from initially bare and hydrogen-like oxygen ions held in the same trap. We analyze discrepancies between these as well as previous measurements with theoretical models based on the multichannel Landau-Zener approach.

Gravitational lensing by large-scale structure imprints secondary anisotropies on the Cosmic Microwave Background (CMB) that can be exploited to probe cosmology. In particular, cosmic voids produce a characteristic lensing signature detectable through Void x CMB cross-correlations. This signal has been robustly measured in the past but its cosmological constraining power remains limited by the incomplete knowledge of how methodological choices affect its measurement and by its uncertain dependence on cosmological parameters. Using a set of validated Roman mock catalogs, we first quantify how mock construction impacts the measured signal and then forecast the capabilities of Roman, in combination with current and upcoming CMB surveys such as Planck, SO and CMB-S4-like experiments. We analyze the signal-to-noise ratio (S/N) for different void definitions (2D and 3D), stacking approaches (rescaled versus non-rescaled profiles), CMB map filtering schemes and noise levels. In contrast to galaxy and void statistics, we find that the Void x CMB lensing signal is less sensitive to the choice of mock catalog, indicating that future tensions with data are unlikely to stem from mock inaccuracies alone. The highest S/N is achieved for 2D voids with rescaled profiles. We forecast S/N ~13$σ$ (8$σ$) for 2D (3D) Roman voids combined with Planck, increasing to 22$σ$ (13$σ$) for SO and 31$σ$ (18$σ$) for CMB-S4-like surveys. While the cosmological dependence of this observable remains to be quantified, Roman together with next-generation of LSS and CMB surveys opens a path toward the first direct cosmological constraints from Void x CMB lensing.

Particle-accelerating colliding-wind binaries (PACWBs) are multiple systems of massive stars in which strong stellar winds collide, accelerating particles to relativistic energies. This population of relativistic particles emits NT radiation, including synchrotron radiation in the radio domain. This emission is expected to be linearly polarized, but the polarization signature has not yet been detected for a PACWB. Our objective is to quantify the linear polarization of synchrotron radiation in two well-known PACWBs and to interpret our measurements within the framework of the physics of these specific NT emitters. We observed the PACWBs WR 147 and HD 167971 with the Very Large Array (VLA) radio interferometer in the frequency bands L and C (1-2 and 4-8 GHz, respectively), where synchrotron emission is expected to be more prominent. We performed polarization calibration and analyzed the resulting Stokes maps. We did not detect any polarization signature for either of the two targets in either of the two bands, even when considering narrower bands to mitigate the effect of bandpass depolarization. The most conservative upper limit on the polarization degree is on the order of 1% for both targets. The lack of linear polarization for the two targets is likely attributable to a combination of effects, including the turbulent nature of the magnetic field in the synchrotron-emitting region, and depolarization processes based on Faraday rotation that are certainly active in these sources. Their complex geometry, unresolved by the VLA at these frequencies, is most likely to lead to beam depolarization. We emphasize that, in contrast to other canonical synchrotron sources, PACWBs are also subject to thermal dilution. This is especially relevant for systems with stars whose winds are strong enough to contribute copiously to thermal emission, such as those harboring a Wolf-Rayet component.

Measurements from the Dark Energy Survey (DES) Year 3 data have shown that the Weyl potential -- the sum of the spatial and temporal distortions of the geometry -- evolves more slowly than predicted by General Relativity, assuming a $Λ$CDM background evolution. An evolving dark energy with a phantom crossing, as preferred by the Dark Energy Spectroscopic Instrument (DESI), is expected to decrease the depth of the gravitational potentials through a stronger acceleration than in $Λ$CDM, potentially solving the tension with General Relativity. In this paper, we show that $w_0w_a$CDM models indeed reduce the tension with respect to $Λ$CDM, down to a level of $1.6-2.2σ$, depending on the treatment of CMB lensing. This reduction is not due to an increase in the Weyl potential's uncertainties, but truly to the impact of the evolving background on the theoretical predictions in General Relativity. More data are needed to robustly determine if evolving dark energy fully explains the low value of the Weyl potential at intermediate redshifts, or if modifications of gravity or interactions in the dark sector are needed, which could simultaneously stabilize the phantom crossing indicated by DESI.

We show that the morphology of the core-collapse supernova (CCSN) remnant RCW 103 is very similar to the morphology of the brightest regions in the recently released JWST IR images of the jet-shaped planetary nebula (PN) PMR 1, and conclude that two energetic pairs of jets shaped RCW 103, compatible with the jittering-jets explosion mechanism (JJEM). The PN PMR 1 IR image exhibits two opposite, large, and prominent ears with a narrow, faint region connecting them through the center, a pipe. Observations and simulations have shown that a pair of jets inflates such a pair of ears in PNe. The brightest regions of PN PMR 1 form two clumpy sectors, each shaped like a wide pizza slice, with a faint region between them; the CCSN remnant RCW 103 has a very similar morphology. We identify two shells in the X-ray image of RCW 103 and suggest that two close pairs of energetic jets shaped this CCSN remnant. We find only traces of two of the four expected ears in RCW 103. The ears in RCW 103 were already dispersed and are very faint. Deeper X-ray observations might detect them. Such energetically misaligned pairs of jets are compatible with the JJEM, which predicts that a few to about 20 pairs of jets are responsible for most CCSN explosions.

The dynamical role of the magnetic field in the star formation process is tightly linked to the coupling between matter and the field. This coupling is due to the interaction between ions and neutrals in the partially ionized interstellar medium. When the ionization degree drops in the dense environment of prestellar cores, the magnetic field and the matter may decouple, leading to differences in the infalling velocities of ions and neutrals known as ambipolar diffusion. The onset of gravitational collapse resulting from ion-neutral decoupling has never been observed. The aim of this work is to search for signatures of ambipolar diffusion within a prestellar core. We observed the deuterated N$_2$D$^+$ ion and the neutral para-NH$_2$D species towards the prototypical prestellar core L1544. These two species are ideal tracers of prestellar cores sampling the same high densities in the core interior. We compared the velocity centroid and linewidth maps of the ion-neutral pair. We find a mean ion-neutral velocity difference of $\sim$0.05 km/s towards the core. By comparing with predictions from self-consistent calculations of the ambipolar resistivity including dust grain growth, we interpret the observed ion-neutral velocity difference in L1544 as a signature of ambipolar diffusion. We do not detect a significant ion-neutral linewidth difference that may be attributed to the subsonic infall motions of the gas in L1544 and geometrical effects in the presence of inclination. These results emphasize the role of dust grain growth at the prestellar core stage in setting the ambipolar resistivity and regulating the dynamical evolution of dense cores towards their collapse into protostars. We propose that measurements of ion-neutral drift velocities provide new constraints on the total magnetic field strength and the dust size distribution within prestellar cores.

Pulsar timing is a foundational part of pulsar research to triage the most interesting systems and to characterise properties (rotational or otherwise) of the population of these extreme objects. Due to the efficiency of a number of sensitive and/or wide-field surveys in recent years, the number of new pulsars discoveries is growing year-on-year, and most of these lack even basic timing parameter measurements. This work aims to demonstrate the capabilities of international Low Frequency Array (LOAFR) stations operating as single telescopes to follow-up, time and characterise these sources, offering new insight into the emission properties of these neutron stars, and support efforts to build timing models for these sources. Between 2020 and 2023 we used the local-mode allocation of the Irish LOFAR station to follow-up 33 pulsar candidates announced from various surveys at different observing frequencies to determine if an international LOFAR station has sufficient sensitivity to detect and time these sources. From the 33 pulsars selected, 22 pulsars were detected and 17 were selected for long-term monitoring across 590 hours of observing time. This has resulted in coherent timing solutions for all of these sources at 150 MHz -- 7 of these have never had any reported timing solutions, the remaining 10 solutions agree well with announcements from others since the beginning of our project. For a fraction of sources announced by surveys each year, the 14 international LOFAR stations are well placed to follow-up survey candidates for long-term pulsar monitoring beyond the standard timing campaigns performed at these telescopes to date, reducing the pressure on observing time availability at these observatories, and enabling the full scientific potential of these pulsars to be realised.

Massive galaxies experience complex evolutionary processes, including mergers and gas accretion, which can disrupt the chemical equilibrium between their stellar and gaseous components. Using the IllustrisTNG (TNG100) simulation at $z=0$, we investigated the prevalence and physical properties of such chemically decoupled systems within the massive star-forming galaxy population. We identify a substantial subpopulation ($\sim 31.5\%$ of the sample) that exhibits systematic stellar-gas decoupling, characterised by a metal-rich stellar component coexisting with a diluted gas reservoir. These non-equilibrium galaxies are closely linked to recent merger activity and partial quenching, and display systematically suppressed star-formation rates and reduced gas fractions, consistent with a transitional evolutionary phase. We then examined the implications of this phase for galaxy-scale habitability prescriptions by applying a terrestrial planet abundance proxy that combines stellar mass, gas-phase metallicity, and the rate of sterilising events. Despite their diluted gas reservoirs, non-equilibrium galaxies dominate the high end of the inferred present-day habitability proxy distribution, exceeding equilibrium systems by more than an order of magnitude. We interpret this as a habitability trade-off: the same gas dilution and quenching processes that reduce the efficiency of future terrestrial planet formation simultaneously create a transient phase of suppressed radiation hazards for existing planets. The Andromeda galaxy (M31) shows qualitative similarities to this chemically decoupled population, suggesting that galaxies exiting their peak star-forming phase represent a distinct and highly relevant demographic for galaxy-scale habitability. Galactic habitability is therefore intrinsically time-dependent.

Supermassive black holes power Active Galactic Nuclei (AGN), injecting energy that regulates accretion and shapes host galaxies. We investigate the morphology, excitation, and kinematics of molecular hydrogen (H2) in the inner circumnuclear disk of Centaurus A, the nearest radio galaxy. We present JWST/MIRI MRS integral-field spectroscopy of the central 170x100 pc2 at 0.3"-0.7" (5-12 pc) resolution, focusing on pure rotational H2 lines. The spectra show strong nuclear continuum and bright H2 emission from S(1) to S(8), including the first S(8) detection in Centaurus A. Optically thin nuclear lines enable maps of temperature, column density, and ortho-to-para ratio from spaxel-level excitation-diagram fitting. Warm H2 shows a complex morphology, dominating the central region where CO emission is weak or undetected. Low-excitation H2 lines trace an inhomogeneous ring with a 20-pc-radius cavity aligned with the jet's near side, suggesting that the jet affects the morphology of the molecular disk. Higher-excitation lines form filamentary structures around the AGN. Kinematics are rotational with an S-shaped distortion, indicating non-circular motions or a warped disk. A coherent, low-dispersion (70 km/s) streamer spirals inward. A power-law temperature distribution yields a warm (100-2000 K) H2 mass of (5.6+/-1.4)e5 Msun and a dynamical mass of 5e8 Msun within 100 pc. Shock excitation is supported by enhanced H2/continuum and H2/PAH ratios, elevated [Ne III]/[Ne II], and sub-equilibrium ortho-to-para ratios (1.6-2.4). Turbulent dissipation can balance H2 cooling and likely dominates heating beyond 30 pc. In the inner 100 pc of Centaurus A, AGN feeding and feedback are linked: shocks excite H2, regulate the gas temperature, and prevent cooling below 100 K, explaining the weak CO emission and lack of a massive outflow. These shocks may drive angular momentum loss and help fuel the nucleus.

The Lyman-$α$ forest refers to the series of absorption features observed in the spectra of distant quasars that are produced by neutral hydrogen in the intergalactic medium. Observed over a wide range of redshifts with both ground- and space-based facilities, the Lyman-$α$ forest provides a powerful probe of numerous physical processes, including the thermal state of intergalactic gas, the timing and topology of cosmic reionization, the expansion history of the Universe, the growth of cosmic structure, massive neutrinos, and the nature of dark matter. This chapter reviews the transformative impact of machine-learning techniques on Lyman-$α$ forest analyses, particularly in overcoming the computational and methodological limitations of traditional approaches. We discuss a broad range of machine-learning applications, including the automated characterization of individual absorption systems, improved reconstruction of the intrinsic quasar continuum, accelerated emulation of hydrodynamical simulations, and the development of simulation-based analyses, field-level inference methods, and three-dimensional reconstruction techniques for the underlying matter density field. As current and upcoming surveys continue to increase both the volume and precision of Lyman-$α$ forest observations, ML-driven pipelines are becoming an essential component of next-generation astrophysical and cosmological analyses.

The ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients (ELEPHANT), has been developed as a framework for filtering hostless candidates, in real time alert systems, and implemented as a filter in the Fink broker. ELEPHANT works on stamps and requires minimal information, thus allowing for fast identification of extragalactic transient events. In this work we evaluate the performance of the ELEPHANT pipeline by systematically analyzing flagged hostless candidates identified between 1 September 2023 and 31 December 2025. Our goal is to quantifying its accuracy and identify dominant sources of contamination. For each flagged candidate we collected additional information from multiple catalogues and archival repositories. We further examined their light-curve evolution and astrometric consistency (coordinate dispersion over time) to refine source classification. Results. Out of 877 flagged events, 67 are confidently confirmed as genuinely hostless candidates, with no detectable host galaxy in either existing catalogues or archival imaging, representing a high-purity sample of intrinsically faint or absent hosts. Additional 51 events are linked to visually identifiable hosts that are entirely absent from both catalogues and ZTF stamps. For the confirmed hostless subset, the inferred upper limits on host-galaxy absolute magnitudes extend well below the luminosity range of typical dwarf galaxies. The pipeline showed an overall accuracy of 0.84, with the majority of the classified flagged events being Type Ia supernovae, and the second most detected class being Type I superluminous supernova. ELEPHANT has been adapted to deal with the Rubin alert stream and has been processing its alerts since February 2026.

Detecting the redshifted global 21-cm signal from the cosmic dawn (CD) remains a major challenge due to strong terrestrial Radio Frequency Interference (RFI), particularly dominated by Frequency Modulation (FM) transmissions in the 88-110 MHz range. While observations from the radio-quiet lunar farside are ideal, Earth orbit offers an intermediate and simpler alternative that may mitigate several limitations of ground-based experiments. We assess the feasibility of detecting the global 21-cm signal from Earth orbit by quantifying FM-based RFI at different altitudes and orbital configurations. We present STARFIRE-2 (Simulation of TerrestriAl Radio Frequency Interference in oRbits around Earth -- 2), an algorithm that estimates FM transmitter-based RFI intercepted by radiometers in orbit. The model constructs a global FM transmitter database and compensates for incomplete data using statistical methods. Using PRATUSH as the reference experiment, we simulate a range of orbital scenarios to identify configurations that minimize RFI and optimize sensitivity for global 21-cm detection. The algorithm can also be adapted for other experiments. Simulations indicate that conducting such an experiment from Earth orbit is feasible for a thermal noise limited instrument placed in a low-Earth, near-polar orbit. Mock sky observations further demonstrate that most theoretically plausible cosmic dawn 21-cm signals can be recovered with high confidence under these optimized orbital conditions.

We present the results of an observation of the broad-line radio galaxy 3C 111 with the X-Ray Imaging and Spectroscopy Mission (XRISM). The unprecedentedly high spectral resolution of XRISM/Resolve revealed that the Fe K$β$ emission line is significantly weaker than expected from the Fe K$α$ line. This feature may be explained by a blueshifted absorption line from an ionized wind overlapping the Fe K$β$ energy. The inferred outflow velocity is 4600 km s$^{-1}$ or 17200 km s$^{-1}$, depending on whether the absorption feature is identified as Fe XXVI or Fe XXV, with the current data unable to distinguish between the two interpretations. Based on spectral modeling, the kinetic power of the wind is estimated to lie in the range 10$^{41}$-10$^{44}$ erg s$^{-1}$, although this estimate is subject to large uncertainties primarily due to the poorly constrained location of the absorber. The inferred wind power is smaller than the jet power of 3C 111 ($\sim 3\times 10^{44}$ erg s$^{-1}$), and is broadly consistent with theoretical expectations that the jet power exceeds that of disk winds.

Neutrino signal from a population of Seyfert galaxies has been detected by IceCube neutrino telescope in the muon neutrino channel that has sensitivity mostly to the Northern Hemisphere sources. This detection can be verified by KM3NeT telescope that has sensitivity also in the Southern Hemisphere. We define a catalog of Seyfert galaxies that are expected to be detectable with KM3NeT, assuming that the neutrino luminosity scales with the intrinsic hard X-ray luminosity of the sources. We find that four sources: NGC 1068, NGC 4151, NGC 4945 and Circinus galaxy, are detectable by KM3NeT, if their spectra follow either NGC 1068 or NGC 4151 spectral template based on IceCube data. We discuss uncertainties of the neutrino flux estimate, considering the Compton-thick nature of three of the four detectable sources: NGC 1068, NGC 4945 and Circinus. The limited catalog of the four sources can be used in KM3NeT source search to reduce the trial factor of analysis aimed at independent verification of the neutrino signal from Seyfert galaxies.

Magnetar short bursts (SBs) are hard X-ray transients of durations $0.01-1$ s peaking at $\sim 10-100$ keV, and are prime targets for new high-energy missions and polarimeters. The recent association of SBs with bright radio bursts in SGR 1935+2154 has broadened interest in SB physics. We present new advanced fireball models combining general relativistic light bending, polarized transport in magnetized photospheres, magnetic photon splitting attenuation, and magnetospheric vacuum birefringence. These models also have relevance to trapped fireballs in magnetar giant flare pulsating tails. We adopt confined flux tube geometries consistent with adiabatic fireballs, and anisotropic/polarized emergent intensities to produce spectra and polarizations, and energy-time Stokes impulse responses. We predict that most fireballs are highly linearly polarized, especially when vacuum birefringence is important. There is rich potential for diagnostics: coexisting direct and lensed delayed images, gaps by occultation of the neutron star surface, and Shapiro+Rømer delay with temporal caustics. These effects can imprint spin phase dependence of the spectral and polarization character of bursts. Predicted signatures depend strongly on viewing geometry, fireball configuration, and photon splitting assumptions, yielding large variance in model high-energy spectral shapes and cutoffs, and energy-dependent polarization. The models can reproduce established double-blackbody SB spectral phenomenology, and we find that the unusual April 2020 radio-associated SB from SGR 1935+2154 is broadly consistent with a footpoint close to the magnetic pole, and possibly near pole-on viewing geometry. Our models motivate reverberation-style analyses for SBs and suggest that high-quality data might constrain source geometry, burst crustal footpoints, and, potentially, neutron star masses and radii.

We report the identification of the likely X-ray and optical counterpart to the unassociated Fermi source 4FGL J2249.4+6229. To clarify its nature, we investigate the X-ray data from Swift/XRT and SRG/eROSITA as well as photometric data from optical catalogues and archival spectroscopic data from the Gemini-North telescope. Using Zwicky Transient Facility data spanning over 6.6 yr, we confirmed a period of $\approx$5.6 h likely associated with the orbital motion in a binary system. The folded light curves have a smooth sinusoidal shape with two peaks per period and the amplitude of $\approx$0.2 mag. The X-ray spectra of the source are well fitted by an absorbed power law with the photon index of $\approx$2.0 and unabsorbed flux of $\approx$1.4$\times10^{-13}$ erg s$^{-1}$ cm$^{-2}$. All these together with the X-ray to optical flux ratio of $\sim$0.2 implies that 4FGL J2249.4+6229 is a promising redback candidate. Fitting the optical light curves with the direct heating model, we obtained the companion mass of $\approx$0.5 M$_\odot$ and temperature of $\approx$3600 K implying an M-type star. This places it among the coldest and most massive companions known in redback systems.Optical spectra confirms the M-type star and shows the broad asymmetric H$α$ emission line. For the distance of 500--550 pc derived from the optical data, the source can be the redback with the lowest X-ray and $γ$-ray luminosities.

(abridged) We aim to predict the most important parameters for grain-grain collision outcomes for models of interstellar grain population evolution on astrophysical scales: the threshold velocity above which colliding grains shatter, the threshold for vaporization, and resulting distributions of grain sizes. We use molecular dynamics simulations which evolve the dynamics of each atom in a dust grain to explore the outcomes of collisions between silicate grains of radii $a \in [5,50]~Å$ at velocities $0.1-20$ km/s. We run simulations of grains with two materials: amorphous SiO$_2$ and an amorphous silicate of composition suggested by Draine \& Hensley (2021). With these simulations, we quantify the collision velocity dependence of shattered and vaporized mass fractions, and the resulting size distributions of shattering products. We find grain shattering thresholds are $\sim$6 km/s for both amorphous SiO$_2$ and astrodust material, which is a factor of $\sim$2 higher than the canonical value for silicates of 2.7 km/s from Jones et al. (1996). This discrepancy is mostly alleviated by correcting an error in the expression for these velocity thresholds derived in Tielens et al. (1994). We find that the size distributions of shattered products are generally not consistent with the power law distributions predicted by this previous model. We also find that their expression fails to predict the fraction of shattered or vaporized material observed in our numerical simulations. The model of Hirashita \& Kobayashi (2013) for the same quantities similarly fails to match the simulations. We provide updated shattering velocity thresholds for standard candidate grain materials to the astrophysics community. Broadly, our updated threshold velocities that astrophysical dust grains may be more robust to shattering in the interstellar medium than previously assumed.

Blazars' non-thermal emission shows rapid variability across all wavelengths, so spectral energy distributions (SEDs) built from quasi-simultaneous data are crucial for revealing the jets physical properties. In this work, we construct quasi-simultaneous broadband SEDs for 93 Fermi blazars (56 FSRQs, 35 BL Lacs, and 2 blazar candidates of uncertain type), fit both peaks with cubic functions to allow for potential asymmetries, and examine correlations among key parameters. Our main results are summarized as follows: (1) We find that synchrotron peak frequency and curvature are only weakly related, suggesting that charged particles are accelerated by mixed acceleration mechanism. (2) The blazar sequence is confirmed in the observer's frame through negative correlations of both the bolometic luminosity $\log L_{\rm bol}$ and the Compton dominance $\log Y$ with the synchrotron peak frequency $\log ν_{\rm syn}^{\rm peak}$. After correcting for Doppler boosting, a weak positive correlation emerges between $\log L_{\rm bol}$ and $\log ν_{\rm syn}^{\rm peak}$. FSRQs and BL Lacs exhibit distinct correlation patterns within the blazar sequence, indicating differences in cooling mechanisms. (3) Using variability time lags between 0.1-1 GeV and 1-300 GeV light curves, we estimate lower limits of Doppler factors for 4 sources, providing a jet-speed diagnostic anchored directly to the $γ$-ray emission zone.

We present a unified H i rotation curve database for 129 dwarf and irregular galaxies drawn from four Local Volume surveys: the Local Volume H i Survey (LVHIS; 33 galaxies), VLA-ANGST (29), LITTLE THINGS (26), and WALLABY DR2 (41). The database provides standardised kinematic parameters, distance estimates, morphological classifications, and rotation curve data in machine-readable JSON, JSONL, and CSV formats with a documented 27-field schema, supporting retrieval-augmented generation (RAG) applications and cross-survey kinematic analysis. Quality tiers distinguish 26 galaxies with full multi-point tilted-ring rotation curves from 103 with single-ring or profile-width estimates. Three worked examples demonstrate corpus queries, including application of the ω correction to DDO 154 (LITTLE THINGS). This work is presented as a data resource; no new dynamical model is proposed. The database and all computation scripts are available at Zenodo (https://doi.org/10.5281/zenodo.20320362).

Neutron stars in close binary systems have the potential to spin up to millisecond periods due to the accretion of matter and angular momentum from their low-mass companions. In later stages of this process, they sometimes start to swing between the accretion-powered and rotation-powered regimes, manifesting themselves as low-mass X-ray binaries and millisecond radio pulsars, respectively. Such systems are known as transitional millisecond pulsars. PSR J1023+0038 was the first one of this kind to be discovered and the first to show optical pulsations at the rotation frequency of the neutron star during a peculiar low accretion state. The optical pulse profile is characterized by a smooth double-peaked shape resembling thermal light curves of X-ray pulsars, but more likely emerging from re-emission of the pulsar wind energy by charged particles in the surrounding medium. Although the amplitudes of the peaks show strong variability, the overall structure of the pulse profile was observed to be fixed, with the optical pulsed fraction less than 1 percent. Here, we report time-resolved observation of a dramatic violation of this permanence during our high temporal resolution observations of PSR J1023+0038 with the 6-m BTA telescope of the Special Astrophysical Observatory. On a timescale of a few seconds the pulse profile took a single-peaked, nearly sinusoidal shape, with synchronous magnification of the pulsed fraction up to about 5 percent. After spending about 220 seconds in this new regime, accompanied by flaring activity, the system returned to its normal state. We discuss a number of possible explanations of this peculiar behavior in the context of the physics and geometry of interactions between the pulsar wind and surrounding matter. However, a complete picture is yet to be revealed.

We present a framework for detecting transient gamma-ray phenomena in a controlled environment by combining end-to-end simulations of the Fermi-LAT sky with self-supervised spatio-temporal deep learning. We generate a ten-year synthetic Universe with gtobssim and process the simulated events into daily all-sky maps of counts and exposure, obtaining a time-ordered sequence that mirrors the structure of Fermi-LAT observations. To model the nominal evolution of the sky, we employ a Convolutional Long Short-Term Memory (ConvLSTM) network that operates directly on map sequences, preserving spatial locality while learning temporal dependencies. The model is trained to reconstruct expected emission, and departures from the learned baseline are quantified through pixel-wise mean-squared residual maps. We then define statistically motivated anomaly criteria by estimating per-pixel thresholds from the residual distribution on the training set, and we enforce spatial coherence via local filtering to suppress isolated fluctuations. The ConvLSTM is then deployed as trained predictor on Fermi-LAT daily maps, where the sky can depart from the nominal behavior because of genuine astrophysical variability and instrumental non-stationarities. The resulting pipeline flags localized, time-dependent excesses consistent with high-variable sources or transient events (e.g., flares or GRBs) and provides a benchmark for evaluating anomaly-detection strategies on long-duration, Fermi-LAT-like datasets.

This chapter reviews the application of Artificial Intelligence (AI) techniques to the study of galaxy clusters, covering both theoretical developments and their use as tools to infer cluster properties from a variety of observational tracers. We discuss recent advances in mass estimation from SZ, X-ray, optical, and dynamical data, highlighting the ability of AI methods to capture non-linear features, projection effects, and complex cluster morphologies beyond more classical approaches. In addition, we present other emerging applications, including the emulation of baryonic physics from N-body simulations, the characterization of dynamical states and mergers, and the analysis of the diffuse components such as the intracluster light. Particular emphasis is placed on the role of simulations in training these models, the impact of baryonic modelling, and the need for a robust uncertainty quantification and interpretability. Finally, we outline current limitations and future prospects, stressing the importance of combining flexible simulation strategies with AI techniques to fully exploit next-generation surveys for precision cosmology.

Collisionless shocks are common in astrophysical systems and stand as sites of particle acceleration. While particles at perpendicular shocks may not return to the upstream region, at oblique shocks a fraction of energetic electrons manage to escape the shock and travel upstream. An extended region known as the electron foreshock is formed, where these reflected particles drive various instabilities that may promote electron acceleration. Here we present the first 2D3V particle-in-cell (PIC) simulations of electron-ion non-relativistic oblique shocks that explore the interaction of the foreshock with pre-existing compressive turbulence with relative amplitude of 15% based on interstellar medium estimates. We find that pre-existing turbulence influences the emergence and behavior of the whistler-wave instability, as it enhances the amplitudes of the magnetic-field fluctuations and leads to larger nonlinear structures. This impacts the dynamics of the reflected electrons, resulting in a shorter and hotter electron foreshock. At the end of our simulations, with pre-existing upstream turbulence we observe non-thermal electrons that are more numerous, reach higher energies, and carry a larger portion of the total energy.

We report the discovery of tidal disruption event (TDE) WFST250820mmsw/AT2025wet by the 2.5-meter Wide Field Survey Telescope (WFST). It exhibits a blue nuclear flare throughout the observed evolution with a g-band peak magnitude ~22, which is about 3 magnitudes brighter than its host galaxy. A Keck/LRIS spectrum taken near the optical peak reveals a featureless blue continuum, with no discernible emission lines. However, its redshift can be accurately determined to be 1.037 by its host galaxy absorption lines. Blackbody fits to the multiband spectral energy distribution (SED) of AT2025wet yield a constant temperature of ~19,000K and a peak luminosity of (8.27 +0.92 -0.71)*10^44 erg s^-1 while actually the SED likely peaks at a much shorter wavelength than a 19,000K blackbody. The SED modeling of the host galaxy implies a stellar mass of ~10^11.2 M_odot and an estimated central black hole mass of ~10^8 M_odot, with no evidence of significant active galactic nucleus activity prior to the flare. All of these observations are well consistent with a featureless TDE scenario, making it the highest-redshift non-jetted TDE known to date. TDEs at such high redshift provide us a unique opportunity to explore the intrinsic SEDs of TDEs, particularly to test whether they peak in the extreme-UV regime, thereby addressing the missing energy puzzle and the origin of optical emission in TDEs. Ongoing surveys represented by WFST and the Legacy Survey of Space and Time (LSST) are expected to discover an increasing number of TDEs at higher redshifts, which will extend our census of SMBHs across redshift space and help unravel the mysteries of optical TDEs through direct probes of their UV emission.

Time variability is a strong probe of energetic phenomena which occur at small spatial scales, like Active Galactic Nuclei (AGN). We use ALMA observations at 100 GHz executed over a period of 2.5 months to look for time variability in the Antennae galaxies, a prototypical early stage merger galaxy pair, for which there are no previous signatures of an AGN in the optical, infrared or X-ray. Most 100 GHz detections in the Antennae are spatially extended and associated with star forming regions, but two sources in the southern galaxy NGC 4039 are compact. One of these compact sources, S3, is offset by 1 arcsecond in the northeast direction from the stellar peak of NGC 4039, and marginally resolved at 10 parsec resolution. The other source, S4, is co-spatial with the stellar peak of NGC 4039 and unresolved even at a resolution of 4 parsec. We examine the time variability of these two sources using their power spectrum. We find that S4 varies with a characteristic timescale of 13+/-3 days, indicating that the phenomena responsible for the 100 GHz emission is smaller than 0.01 parsecs. By comparing the observed flux of the two sources with various candidate origins, we show that while S3 can be explained either by a young massive stellar cluster or an AGN, S4 is likely to be an AGN that is possibly Compton-thick.

A recent 2023 paper by Massaro et al. introduced the G4Jy-3CRE, a new catalog of the brightest radio sources in the southern hemisphere that serve as a southern equivalent to the Third Cambridge Catalog Revised (3CR). The G4Jy-3CRE catalog selected 264 sources from the GLEAM-4Jy survey based on the same criteria used to select the sources in the 3CR. In this paper, we present new Australian Square Kilometre Array Pathfinder (ASKAP) continuuum imaging of the G4Jy-3CRE catalog. We use the three most recent data releases from the Rapid ASKAP Continuum Survey (RACS), covering the sky south of +30°decl.: RACS-low1, RACS-mid, and RACS-high. Together, these data releases cover a range of frequencies from 600 to 1800 MHz. The RACS surveys have improved spatial resolution and sensitivity over archival surveys at the same frequency, enabling us to classify 173 sources (66% of the sample) with morphologies indicative of the presence of jets, 37 of which did not show jet activity on archival radio maps. We were able to effectively classify FRI/FRII galaxies up to a redshift of z = 1.35. Moreover, we identified six optical counterparts for sources that were either previously unidentified or ambiguous.

In the 2021 outburst of RS Ophiuchi, the gamma- and the X-ray flux were measured quasi-simultaneously from day 1 after the optical peak, offering the first comprehensive view of shocks in a nova occurring in a symbiotic system. We present a previously unpublished observation done with NuSTAR in the 3-79 keV range, 9 days after maximum, and we review the complex history of the evidence of shocks in the previous outbursts of this nova in the light of the intensive X-ray monitoring of 2021. We find evidence that the shock causing the particle acceleration measured with the Cherenkov telescopes produced also the thermal flux detected in the 0.2-30 keV X-ray range, while the large gamma-ray flux observed with Fermi after about a day, is not consistent with the X-ray observations. We conclude that an initial, strong shock, with particle-particle loss timescale shorter than the timescale of particle acceleration at energy higher than a few GeV, occurred close to the red giant atmosphere,where either the X-rays' emitting volume was reduced by turbulence, or - perhaps less likely - the X-rays were completely absorbed by large column density near the giant and by the accretion wake along the line of sight. We compare RS Oph with other novae in long period systems with evolved companions,discussing how the shocks' phenomenology is a powerful tool to derive other physical parameters. Finally, we discuss predictions that in T CrB, expected to have a new outburst within the next few years, the shocks may not be as energetic as in RS Oph.

Pulsar timing is a valuable source of high-precision astrophysical measurements which can be used to probe gravitational physics, including by detecting gravitational waves. An important factor limiting the precision of these measurements is pulse jitter; i.e., intrinsic, short-timescale variation in the amplitude and shape of pulses from a given pulsar. Because conventional pulse time-of-arrival (TOA) measurement relies on template matching, which assumes the average pulse shape is stable, such variation gives rise to jitter noise in TOA measurements. Here we introduce a generalization of the template matching technique, making use of principal component analysis, which can account for variations in pulse shape. We compare this technique to other proposals for mitigating jitter noise in pulsar timing, paying particular attention to the possibility of corrections absorbing other astrophysical signals of interest, and demonstrate its effectiveness using simulated data.

The element abundances of Milky Way disc stars encode entangled imprints of multiple enrichment processes, making it difficult to uncover the underlying chemical evolution. Here we re-project 16 stellar abundances for 199,290 red giant stars ([Fe/H]$ > -1$) into a set of (4) shared enrichment patterns, providing a generative framework for learning the organising structure of the Milky Way disc. The relative contributions of these patterns vary systematically across the disc, revealing a low-dimensional enrichment basis that responds coherently to global drivers of disc evolution. By grouping stars according to their pattern contributions, we identify coherent enrichment pathways that exhibit strong chemo-spatial correlations and are stratified in both age and height above the plane, linking radial growth to vertical disc structure. Stars occupying similar positions along these enrichment pathways also show coherent vertical deviations across radius, indicating that the low-dimensional chemical structure captures the disc's response to dynamical perturbations. We identify a transition in enrichment behaviour at approximately 6 Gyr, marking the onset of a more chemically mixed regime with increasing contributions from delayed sources. Within this connected system, the observed $α$-bimodality arises within a shared, low-dimensional abundance structure, with stars populating continuous sequences of changing enrichment fractions that are tightly coupled to spatial, temporal, and orbital coordinates across the Milky Way disc.

We present a uniform, epoch-resolved analysis of soft X-ray observations of eight comets obtained with NICER, using Bayesian statistics to identify charge-exchange line components, measure relative ion fluxes, and infer nominal solar-wind freeze-in temperatures. The sample exhibits recurring spectral morphologies that fall into distinct families: carbon-dominated, intermediate, and nitrogen-/oxygen-dominated. Epoch-resolved flux ratios yield a robust separation between diagnostics: carbon-derived freeze-in temperatures cluster near T_freeze(C) about 1.4-1.7 MK, while nitrogen- and oxygen-derived diagnostics are systematically higher, typically T_freeze(N,O) about 2.0-2.3 MK. Short-timescale variability in inferred freeze-in conditions is common, indicating that instantaneous solar-wind charge-state fluctuations, rather than large changes in coma composition, dominate the spectral differences. We discuss instrumental and modeling limitations, demonstrate how our Bayesian fitting method mitigates degeneracies via physically motivated priors and Bayesian model selection, and recommend laboratory measurements and coordinated high-resolution X-ray observations to refine charge-exchange diagnostics and validate low-resolution inferences.

We present a new absolute age determination for NGC 6791, one of the Milky Way's oldest and most metal-rich open clusters. Its unusual properties make it an important probe of inner-disk evolution and asteroseismic calibration, but its age has remained difficult to determine because of coupled uncertainties in reddening, distance, photometry, and stellar-model physics. Gaia DR3 photometry together with detached eclipsing binaries (DEBs) in NGC 6791 are combined with 10,000 Monte Carlo isochrone sets (marginalizing over uncertainties in composition, convective mixing processes, opacities, diffusion, nuclear reaction-rates, distance modulus, and reddening) to determine the age of NGC 6791. For each isochrone we build a synthetic color-magnitude diagram (CMD) that matches the observed star count in the MSTO and subgiant-branch window and injects empirical photometric scatter perpendicular to the ridgeline, enabling CMD comparisons without artificial-star tests. We assess CMD morphology using a bootstrap-calibrated two-dimensional Kolmogorov-Smirnov statistic, and add an external check based on the nearest-point metric: a coeval DEB statistic in $(M,L)$ space. These statistics are mapped to probability-density weights via bootstrap-resampling and combined into a single isochrone weight. NGC 6791 is determined to have an age of $8.46\pm0.66$ Gyr, $[\mathrm{Fe/H}]=+0.280\pm0.079$, $Y=0.2968\pm0.0158$, $(m{-}M)_V=13.333\pm0.058$, and $E(B{-}V)=0.183\pm0.024$. Our error budget shows no single dominant contributor, and highlights differences between open-cluster and globular-cluster age errors. Combined with its super-solar metallicity, our age estimate favors an inner-Galaxy origin for NGC 6791 and subsequent outward migration, provides a benchmark for asteroseismic calibration at high metallicity, and extends the absolute cluster age--metallicity relation to an old, metal-rich open cluster.

Shock-driven turbulence is central to astrophysical plasmas in which explosions and compressive driving inject energy through shocks rather than steady stirring. We present three-dimensional, three-temperature (ion, electron, and radiation; 3T) radiation-hydrodynamic simulations of a laboratory platform in which two offset CH mesh targets are irradiated by a $30\,\rm ns$ X-ray pulse. Mesh ablation launches counter-streaming supersonic flows whose vorticity is seeded baroclinically at mesh-cell corners, advected into collimated channels over $\sim15\,\rm ns$, and injected into the outgoing streams before collision. The flows first collide at $t\simeq75\,\rm ns$, forming a shocked turbulent mixing layer that persists for at least $300\,\rm ns$, reaches $\ell_0\simeq4.5\,\rm mm$, and evolves toward an effectively isothermal equation of state with $γ_{\rm eff}\simeq1.1$. After stagnation, $u_0(t)\propto t^{-1.1}$ while $t_0/t_{c_s}\simeq0.2$ remains nearly fixed. Compression and stretching dominate the vorticity budget, and the velocity field relaxes toward a kinetic-energy partition of approximately $70\%$ solenoidal and $30\%$ compressive. The Reynolds stress is strongly anisotropic at the outer scale and remains measurably anisotropic over much of the resolved inertial interval, indicating directional memory of the collision axis and mesh geometry across many scales. The solenoidal strain spectrum implies $\ell_{ν,\rm s}\simeq92\,μ\rm m$, $\ell_0/\ell_{ν,\rm s}\simeq49$, and an effective Reynolds number $\mathrm{Re}\sim2\times10^2$. The density-gradient spectrum is directly tied to the compressive mode spectrum, which evolves independently from the incompressible cascade. Abridged.

We present the galaxy stellar population catalogue from the JWST Advanced Deep Extragalactic Survey (JADES) Data Release 5 (DR5), providing homogeneous Bayesian inference of physical galaxy properties in GOODS-N and GOODS-S. Using deep JWST/NIRCam and MIRI imaging combined with ancillary multi-wavelength data, we model the spectral energy distributions of ~500,000 sources with the Prospector framework. Our modelling incorporates flexible non-parametric star-formation histories (SFHs), nebular emission, dust attenuation, metallicities, and mid-infrared AGN and dust emission. We adopt an evolving star-forming main sequence (SFMS) prior for modelling the SFHs, which provides a physically-motivated long-term shape of SFHs while retaining non-parametric flexibility. The prior links stellar mass growth and SFR through the observed redshift-dependent SFMS, shaping the global behaviour of the inferred SFHs but allowing substantial deviations and scatters wherever supported by the data. We derive posterior distributions for stellar masses, SFRs, SFHs, dust attenuation, metallicities, and AGN contributions. The depth and wavelength coverage of JADES enable robust stellar mass measurements down to low-mass limits, as well as improved constraints on recent star-formation activity for ~350,000 galaxies at z = 1 - 9. The adoption of a physically motivated prior mitigates unphysical solutions and reduces degeneracies between redshift, age, dust, and metallicity, particularly for faint sources. We validate the catalogue through consistency checks and comparison to spectroscopic redshifts where available. The resulting value-added catalogue provides a uniform set of stellar population parameters suitable for statistical studies of galaxy growth, quenching, and the build-up of stellar mass across cosmic time. The full catalogue and posterior summaries are publicly released as part of JADES DR5.

Context. Ultra-diffuse galaxies (UDGs) lie at the extreme end of the size-luminosity distribution of low surface-brightness (LSB) galaxies. Their detection and characterization require deep imaging and reliable source detection techniques that can handle low signal-to-noise ratios and severe source blending. Aims. We aim at improving the detection and characterization of the LSB galaxies and UDG candidates in different environments. To this end, we have developed a new automated detection Python-based tool, named ATTILA. Methods. We use deep g- and r-band imaging from the VST Early-type GAlaxy Survey (VEGAS), covering the central region of Hydra I and three new additional fields. Sources are identified combining tiling processing, source detection, and iterative deblending. The structural parameters are derived through surface brightness profile analysis and Sérsic modelling. Cluster membership is determined using the early-type galaxies colour-magnitude relation. Results. We identify 24 new UDGs, doubling the known population in the Hydra-I cluster to 48, consistent with expectations from halo mass scaling relations, and 92 additional LSB galaxies. In real data, ATTILA recovers more than 80% of previously known LSB galaxies and significantly improves the automated detection rate relative to standard methods. Conclusions. By improving the recovery of faint and diffuse sources while mitigating blending and contamination effects, ATTILA enables a more complete census of the LSB galaxy population, including UDGs.

Recent efforts to characterise the molecular gas content of brightest cluster galaxies (BCGs) at intermediate redshift have revealed a sub-population of gas-rich systems, whose star formation activity is likely influenced by environmental processing. In this study, we aim to investigate the molecular gas reservoirs and star formation fuelling of central galaxies in groups, also known as brightest group galaxies (BGGs), at intermediate redshifts. We present targeted carbon monoxide (CO) line observations of three BGGs in the COSMOS field at $z \sim 0.3$, obtained with the IRAM 30m telescope. The galaxies exhibit disturbed morphologies, extended blue substructures, and interaction signatures. Furthermore, they exhibit significant star formation rates derived from multiwavelength diagnostics. We detect CO(1$\rightarrow$0) emission in one system, revealing a substantial molecular gas mass of $M_{H_2} \sim 3 \times 10^{10}$ M$_\odot$, while for the other two BGGs, CO emission lines remain undetected, yielding stringent upper limits of $M_{H_2} \lesssim 10^{10}$ M$_\odot$. By combining molecular gas constraints with fiducial star formation rates derived from total infrared emission, we infer gas depletion timescales in the range of $\lesssim 0.5-1.5$ Gyr. These results may indicate that, despite their active star formation and interaction signatures, some BGGs could already experience efficient gas exhaustion or suppressed gas replenishment, suggesting that gas depletion precedes star formation quenching. Our findings hint that environmental processes in galaxy groups could strongly regulate the availability of cold gas and drive rapid evolutionary phases in central galaxies, possibly bridging the gap between gas-rich BCGs and passively evolving systems.

We analyse new H-band integral-field unit observations of two galaxies at ~4 Mpc, using a principal components analysis of pixel spectra to probe their giant star content. In both galaxies, the signals arise in near-resolved point-like sources without large-scale variation, consistent with each pixel sampling stars randomly from a common underlying population. In the (mostly) old bulge of NGC 5128, the observed pixel-to-pixel variation is dominated by a component with a mid-M giant spectrum with prominent CO bandheads. We also recover a smoother second spectral component, apparently driven by contributions from later spectral types. This component is not present in predictions from Poisson-sampled models of old stellar populations; we suggest that it arises from the cool phases of long-period variable stars. (An appendix provides direct evidence for such variables in complementary two-epoch MUSE observations.) In the contrasting galaxy NGC 5102, where a post-starburst stellar population is known to be present, we again find two distinct components. As before, the first component carries the CO bands typical of M-giants. The second eigenspectrum in this younger galaxy shows a strong 1.77 micron C2 bandhead, a feature which is characteristic of carbon stars. Our results highlight the ability of integral field data to access information beyond the total spectrum, even when individual stars cannot be classically resolved.

Recent observations have revealed a unique class of active galactic nuclei (AGNs), termed little red dots (LRDs). These objects are hypothesized to be powered by massive black holes rapidly accreting in dense gaseous environments. Theoretical studies suggest that the circum-nuclear gas can form an optically thick black hole envelope (BHE), whose structure resembles the atmospheres of convective stars near the Hayashi limit. Given that such cool stars typically generate magnetic fields, we propose a dynamical and spectral model for an LRD enshrouded by a magnetized BHE. Assuming spherical free-fall accretion onto a rotating, magnetized BHE, our model accounts for key observational properties of LRDs. We propose that the Doppler component of broad emission lines originates from plasma clumps co-rotating within the BHE magnetosphere. Including additional broadening due to electron scattering allows the resulting line profile to be fitted by a combination of a Gaussian core and an exponential tail. This model can reproduce Doppler components up to a few thousand ${\rm km~s^{-1}}$. We suggest that conventional black hole mass estimation methods based on the virial relation may yield erroneous results. Furthermore, our model is consistent with X-ray non-detections in LRDs. We evaluate the X-ray luminosities of two potential sources: the post-shock region of accretion shocks and a magnetically heated corona. We find that these X-ray luminosities are constrained to $\lesssim 10^{41}~{\rm erg~s^{-1}}$ across a wide range of black hole masses ($10^5 M_\odot \lesssim M_{\rm BH}\lesssim 10^7M_\odot$) and accretion rates, consistent with current upper limits on X-ray emission.

We re-examine the claim by Wiseman et al. (2026) that progenitor-age bias has a negligible impact on cosmological inferences from Type Ia supernovae (SNe Ia). We show that their inferred host-age-Hubble residual (HR) slope is severely underestimated because their combined SN Ia sample spans an unusually wide redshift range ($0.04 < z < 0.42$), over which the mean host age evolves by $\sim$\,3 Gyr. As a result, SNe Ia spanning substantial host-age differences are effectively assigned similar HR values prior to regression, artificially flattening the inferred age-HR relation. In addition, their application of the Pantheon+ host-mass correction further suppresses the slope, but the underlying dust model is highly incompatible with the measured dust attenuation curves of galaxies. We also demonstrate that our age bias correction is robust to uncertainties in host-progenitor age mapping arising from different choices of the SN Ia delay-time distribution. The reduced progenitor-age evolution argued by Wiseman et al. (2026) must, by the same logic, be accompanied by a steeper inferred progenitor-age-HR slope. When these two effects are consistently combined in computing the redshift-dependent magnitude correction, the final correction, and hence the resulting cosmological impact, remain largely unchanged from Son et al. (2025).

Interstellar medium (ISM) structures gravitationally perturb stellar orbits in galactic disks, driving orbital heating and migration. However, studies of these transport processes tend to model the ISM very crudely, e.g., as a collection of compact, spherical ``clouds'' moving in the disk plane. Here, we revisit this problem with more realistic models of ISM density fluctuations drawn from the TIGRESS-NCR magnetohydrodynamic simulations, which follow the physics governing the ISM in Milky-Way-like conditions at high resolution. By integrating test-particle trajectories through time-dependent TIGRESS-NCR structures, we uncover transport behavior that contrasts sharply with conventional theoretical expectations. Notably, radial heating scales as $σ_R \propto t^{1/2}$ for initially cold orbits at early times, and $σ_R \propto t^{1/5}$ for warmer orbits at late times, contrary to the classic $σ_R \propto t^{1/3}$ prediction. The ISM drives substantial radial migration, accounting for $\gtrsim 30\%$ of that observed in the solar neighborhood (even without stellar spiral structure), and leads to a very low heating-to-migration ratio of $\mathrm{rms}\,δJ_R\,/\,\mathrm{rms}\,δJ_\varphi \approx 0.055$, where $J_R$ and $J_\varphi$ are the radial and azimuthal actions respectively. Vertical motion suppresses the amplitude of radial transport, but does not change the basic scalings. All our simulation results can be explained using quasilinear diffusion theory, accounting for the fact that the dominant ISM fluctuations have wavelengths of $λ_* \sim 600\,$pc and correlation timescales of $τ_* \sim 70\,$Myr. We provide simple fitting formulae for the corresponding diffusion coefficients. In Paper II, we study the ISM's role in vertical disk heating.

We investigate the role of mass ratio reversal (MRR), in which the initially less massive star in a binary forms the more massive compact object, in shaping the astrophysical binary black hole (BBH) merger rate and mass distribution inferred by LIGO-Virgo-KAGRA, comparing simulation outcomes from population synthesis frameworks COMPAS and SEVN. We find that the observational imprint of MRR differs qualitatively between the two models. In COMPAS, MRR systems dominate the merger rate density at high primary masses ( $\gtrsim$ 12 M$_\odot$), high secondary masses ( $\gtrsim$ 20 M$_\odot$), and high mass ratios ($q>0.6$), whereas in SEVN, MRR systems remain subdominant across the BBH mass distribution. This implies that the initially less massive star can massquerade as the observed primary black hole, such that the primary-mass distribution is not a direct tracer of the initially more massive stars, but instead a superposition of physically distinct evolutionary populations. We identify in the simulations three distinct evolutionary pathways leading to MRR systems: core-growth, in which stable mass transfer increases the helium-core mass of the secondary; PPISN-shrinking, where pulsational pair-instability episodes reduce the primary remnant mass; and asymmetric-CCSN, where differential supernova mass loss drives the reversal. When weighted by the local BBH merger-rate density, the core-growth channel dominates almost exclusively. MRR systems predominantly originate from massive ($\gtrsim$ 50 M$_\odot$), low-metallicity progenitors, with most of the systems forming below 0.1 $Z_\odot$. Our results demonstrate that MRR is a physically distinct and potentially observable feature of isolated binary evolution. Accounting for MRR will be important for robustly connecting future gravitational-wave observations to the physics of massive binary evolution and compact-object formation.

JWST has revealed a substantial population of "Little Red Dots" (LRDs) at $z>4$, challenging conventional AGN frameworks. However, the low-redshift regime remains largely unexplored. In the second paper of the (LRDs)$^2$ series, we present a systematic selection from DESI DR1 and identify 27 LRDs at $z=0.2-0.9$, yielding a number density lower limit of $7.5 \times 10^{-10}$ cMpc$^{-3}$. We conducted near-IR spectroscopic follow-up observations for 18 of them, revealing their full SED shapes and emission lines. These low-$z$ LRDs share the hallmark properties of their high-$z$ counterparts: compact morphology, V-shaped UV-optical continua, broad Balmer emission with extreme decrements (median H$α$/H$β\sim 16$), frequent Balmer absorption (67%), and blackbody-like optical-to-near-IR continua. All have low metallicity, occupy the same regions in the BPT diagram as high-$z$ LRDs, and have softer ionizing spectra than typical AGNs. The consistency between low-$z$ and high-$z$ LRD properties indicates the same physical processes at work. The correlation between broad-line Balmer luminosity and $L_{5100}$ deviates from that of local type-1 AGNs, limiting the direct application of local BH mass calibrations. Ionized [O III] outflows are ubiquitous (78%). One LRD at $z=0.196$, J1717+3807, shows robust long-term variability in $i$ and WISE bands. The optical-to-NIR continua of LRDs reveal a wide range of temperatures $\sim 2000-4700$ K (peak $0.6-1.5$ $μ$m), with a subset showing cooler and larger envelopes than those at high $z$. Low-$z$ LRDs serve not only as proximate laboratories for probing the nature of LRDs, but also trace the cosmic evolution of this population from the cosmic dawn to the present day.

Type Ia supernovae (SNe Ia) play an important role throughout astrophysics, most notably as standardizable cosmological candles. Yet, their stellar progenitors and explosion mechanism remain areas of active investigation. For decades, the canonical model for normal brightness SNe Ia used in cosmology was a carbon-oxygen white dwarf (WD) accreting from a non-degenerate stellar companion, approaching the Chandrasekhar mass (M_Ch). Previously, all models of near-M_Ch SNe Ia invoked an ad hoc assumption on the critical process of detonation initiation, and could therefore be tuned to a variety of outcomes. Here, we present global 3D hydrodynamical simulations of near-M_Ch progenitors, which incorporate, for the first time, a laboratory-validated ab initio mechanism for the turbulence-driven deflagration-to-detonation transition (tDDT). The tDDT detonation mechanism is highly efficient, leading to detonation initiation which is prompt in comparison to most prior work. Despite spanning a factor of six in central ignition density and qualitatively distinct ignition topologies, all models converge on nearly identical synthetic spectra at peak luminosity, spectroscopically matched to the overluminous SN 1999aa. The turbulence-driven Chapman-Jouguet criterion drives each progenitor to a common detonation configuration from diverse initial conditions, providing a physical foundation for the ignition-insensitive detonation outcomes implicit in the empirical standardizability of SNe Ia. This provides the first physically motivated, self-consistent pathway for delayed detonation in SNe Ia simulations. Further work is necessary to understand how this mechanism might produce more delayed detonation initiation and potentially fail, thereby yielding SNe Iax.

It has been argued that supermassive black holes (BHs) coevolve with the central parts of galaxies, as a result of the common fuel for both the BH and star formation in the galaxy central region, as supported by the particularly significant relation between BH growth and the central mass density within 1 kpc found among star-forming galaxies. In the context of this scenario, one would naturally expect a close observational link between AGN activity and star formation activity in the central regions, e.g., the surface star formation rate density in the central 1 kpc region ($Σ_{\rm SFR, 1~kpc}$), as the manifestation of coeval growth. With ~3000 galaxies in the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey that have X-ray coverage from SRG/eROSITA, XMM-Newton, or Chandra, we studied how the X-ray AGN fraction varies with $Σ_{\rm SFR, 1~kpc}$. We found that the fraction of X-ray AGNs with relatively higher specific BH accretion rates increases with $Σ_{\rm SFR, 1~kpc}$, consistent with the expectation. Comparison of the mean star formation rate surface density ($Σ_{\rm SFR}$) profiles of the host galaxies of these AGNs and normal galaxies sharing similar properties reveals elevated $Σ_{\rm SFR}$ in AGN hosts across the entire central region. As for optically-selected AGNs, their hosts also tend to show high $Σ_{\rm SFR}$ in the central regions on average compared to normal galaxies, but are discrepant with X-ray AGNs in terms of the trend of AGN fraction vs. $Σ_{\rm SFR, 1~kpc}$, which can be explained by selection effects. While these general trends all support the coeval growth scenario, they do not contradict observational evidence for AGN feedback, as the time-averaged effects from local AGN feedback are modest in star-forming regions.

We present an information-theoretic analysis of the Cosmic Web that goes beyond the scalar density contrast and exploits the full structure of the tidal deformation tensor. The three eigenvalues (lambda1, lambda2, lambda3) of the tidal Hessian furnish a natural morphological classifier: clusters, filaments, walls, and voids correspond to (+,+,+), (+,+,-), (+,-,-), and (-,-,-) sign patterns, and their joint probability distribution function (PDF), known analytically in the linear regime from Doroshkevich (1970), defines a continuous Shannon entropy that quantifies the information encoded in the geometry of large-scale structure. Additional information resides in the shear invariants Q = Trace(T2) and A = Trace(T3), which are algebraically independent of the density contrast delta and capture anisotropic deformation invisible to the density alone. The information dimension of each morphological component is related to its Hausdorff (fractal) dimension through the multifractal formalism: clusters (DH = 1.2), filaments (DH = 1.8), walls (DH = 2.5), and voids (DH = 3) define a spectrum of generalized Renyi dimensions Dq, whose q = 1 limit recovers the Shannon information dimension. The resulting entropy budget identifies filaments as the dominant information carriers of the mater distribution, while the tidal eigenvalue entropy is maximized in wall-like configurations near the saddle points of the gravitational potential. We also compute the redshift evolution of the multifractal entropy and derive its relation to the linear growth rate f(z), providing an independent constraint complementary to redshift-space-distortion measurements of f*sigma8.