Applied Physics · Cross-listed from quant-ph
A 3D-Printed GHz Microwave-Resonator Paul Trap for Electron Confinement and Millisecond Spin-Qubit Coherence
Niklas V. Lausti, Vineet Kumar, Ivan Hudák et al. (+4 more)
We report a 3D-printed microwave-resonator Paul trap that operates at the GHz frequencies required for electron confinement while preserving an open geometry suitable for
laser access and imaging ion Coulomb
crystals. The resonator exhibits moderate quality factors of approximately 1000, enabling large confining electric-field amplitudes at low input power, and is in good agreement with finite-element-method (FEM) predictions despite manufacturing imperfections, which we experimentally characterize. The validated FEM model is then used to calculate the electromagnetic fields in the trapping region. These field distributions, together with surface-roughness measurements, are incorporated into a model of electron
spin-
qubit decoherence to estimate the coherence time. Our analysis predicts that electron
spin-
qubit coherence times on the order of 10 ms should be achievable under the assumption that motional heating is dominated by Johnson noise, making such systems relevant for
quantum information processing. The method of obtaining the coherence time is applicable to any electron Paul trap.
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All authors Niklas V. Lausti, Vineet Kumar, Ivan Hudák, Jiří Hajnyš, Peter Kúš, Radek Plašil, Michal Hejduk
Computational Physics · Cross-listed from cs.LG
Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems
Kasper Helverskov Petersen, Rasmus Hannibal Tirsgaard, François R J Cornet et al. (+2 more)
Large-scale self-supervised pretraining has reshaped modern machine learning, substantially advancing the ability of
language and
vision models to generalize across downstream tasks. While deep learning has driven considerable progress in modeling atomistic systems in recent years, self-supervised pretraining in this domain has not yet achieved comparable downstream generalization. To address this, we introduce Atom-JEPA, a self-supervised pretraining framework that learns latent representations from unlabeled 3D structures through complementary atom-level and substructure-level objectives inspired by joint-
embedding predictive architectures. We pretrain Atom-JEPA on large-scale molecular and crystalline
datasets and evaluate its transfer performance by fine-tuning on a diverse set of downstream property prediction tasks. Atom-JEPA achieves state-of-the-art performance on molecular ADMET and
quantum-chemical property prediction tasks, and is highly competitive in predicting the physical properties of crystalline materials. These results demonstrate the potential of latent-space predictive pretraining to support broad downstream generalization from structural data alone. Code and pretrained model checkpoints are publicly available at https://github.com/khelverskovp/atom-jepa
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All authors Kasper Helverskov Petersen, Rasmus Hannibal Tirsgaard, François R J Cornet, Mikkel Jordahn, Mikkel N. Schmidt
Data Analysis and Statistics
Data geometry preserves prediction but reshapes explanation
Nicola Amoroso, Mario Caruso, Marianna La Rocca et al. (+8 more)
Across scientific domains, empirical data often give rise to positive semidefinite
matrices that encode similarities, couplings or interactions and induce natural geometries. We investigate whether changing the geometry used to compare the same empirical representations preserves subject-level performance and the local structures from which explanations are derived, a question we term the prediction explanation invariance problem. We address this problem across morphometric MRI, fMRI and
EEG data by comparing Frobenius and trace geometries applied to the same empirical
matrices. Predictive performance was broadly preserved across geometries, but comparable performance did not imply agreement in subject-level decision scores or predicted labels. Predictive similarity also masked geometry-dependent differences in local neighbourhoods, perturbation sensitivities and explanatory rankings. Dimensionality reduction made the two subject-space geometries progressively more concordant, while classification performance and decision-level agreement declined. These results identify data geometry as a hidden degree of freedom in explainability: similar performance does not guarantee invariant decisions or explanations.
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All authors Nicola Amoroso, Mario Caruso, Marianna La Rocca, Loredana Bellantuono, Tommaso Maggipinto, Michele Morelli, Sabina Tangaro, Marco Tatullo, Roberto Bellotti, Ester Pantaleo, Alfonso Monaco
Optics · Cross-listed from cs.CV
PolarScale: A Physics-Grounded Benchmark for Radiometrically Consistent RGB-to-Stokes Estimation
Beibei Lin, Tingting Chen, Xin Zhang et al. (+3 more)
Polarization imaging provides physical cues beyond intensity imaging but typically requires specialized hardware. Recent methods infer polarization from RGB-like inputs, yet predict only normalized Stokes components or relative descriptors, from which the radiometric scale needed for full Stokes reconstruction has been divided out. We introduce PolarScale, a
benchmark that makes this scale an explicit prediction and evaluation target. Built on existing trichromatic full-Stokes measurements, PolarScale takes the per-scene normalized total-intensity image $s_0$ (a scene-referred linear image, not a consumer sRGB photograph) and asks models to predict normalized Stokes components, AoLP/DoLP/DoCP, and a per-scene scale. Because the scale is divided out of the input, it is not physically identifiable; PolarScale therefore evaluates
dataset-conditioned semantic scale estimation against a constant-scale control, together with angular, self-consistency, and physical-bound metrics. Across seven restoration-based and generative backbones and three prediction strategies, the strongest restoration models estimate the scale with 3.6-4.3% mean relative error versus 5.7% for the constant control and violate physical bounds on fewer than 0.25% of pixels, whereas two generative baselines collapse to a near-zero scale; explicit descriptor supervision improves descriptor accuracy (23.66 vs. 18.88 dB PSNR for MAE). Predicted full-Stokes representations improve diffuse/specular separation, material segmentation, and glare classification, although in diffuse/specular separation the learned scale performs only on par with the constant control.
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All authors Beibei Lin, Tingting Chen, Xin Zhang, Wenhao Zhao, Dongjun Li, Zifeng Yuan
Optics
Perfect Bound States and non-Markovian Dynamics for Imperfect Giant Atoms in a Semi-Infinite Waveguide
T. Y. Liu, X. Y. Li, W. Y. Hu et al. (+3 more)
Bound states in structured reservoirs require exact interference conditions and are therefore sensitive to imperfections in the coupling geometry. In this paper, we study a two-level giant atom coupled at multiple points to a mirror-terminated semi-infinite waveguide. The exact atom-
photon bound state requires both cancellation of the outgoing radiation amplitude and dispersive matching to the atomic detuning. Generalized delay-equation dynamics, continued-pole spectra, and real-space
photon fields verify this criterion for coupling-strength, position, and coupling-phase imperfections. For representative realizations, retuning restores one-, two-, and three-root responses after strength errors and one- and two-root responses after position errors. The specified position-imperfect three-root configuration fails because its $2\pi$ root is no longer dark, consistent with a $58.77\%$ spectral mismatch. Ensembles of 1000 realizations at each error amplitude show near-unity target-state recovery for strength errors, unity recovery of the specified one- and two-root targets but no three-root recovery for position errors, and no nontrivial exact recovery for independent phase errors. Optimized phase-imperfect responses instead retain finite linewidths. Root matching with realization-dependent control retuning therefore constitutes a compensation procedure, rather than generic passive robustness against arbitrary disorder.
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All authors T. Y. Liu, X. Y. Li, W. Y. Hu, T. Z. Luan, Cheng Shang, H. Z. Shen
Fluid Dynamics
Motif: A Modular Finite-Volume Framework for Transient Incompressible Flow
Utku Şentürk
This document presents the theory, implementation, and verification of Motif, a two-dimensional incompressible flow solver developed as a teaching and research framework. The governing equations are discretized using the finite-volume method on staggered Cartesian grids. Convection is treated explicitly using the second-order Adams–Bashforth method,
diffusion implicitly using the Crank–Nicolson method, and pressure–velocity coupling using projection methods. Both the Standard projection and the approximate second-order projection of Perot (1993) are considered. Particular
attention is given to the discrete operators, boundary conditions, temporal treatment of pressure, conservation properties, and numerical dissipation and dispersion. The implementation is verified using a sequence of periodic, wall-bounded, and inlet–outlet flow problems on uniform and smoothly stretched grids. Spatial and temporal convergence, discrete mass conservation, kinetic-energy behavior, enstrophy, and energy spectra are examined. The results demonstrate the expected accuracy of the spatial discretization and distinguish the temporal behavior of the two projection approaches. The document is intended both to describe Motif in sufficient detail for independent implementation and to examine the numerical properties relevant to its continued development toward direct numerical simulation.
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Optics
Synthesizing free-electron wave functions by stimulated near-field interactions
Álvaro Rodríguez Echarri and Albert Polman
Stimulated electron-optical-near-field interactions imprint a coherent, phase-coherent modulation on the wave function of a free electron, of which the free-space dispersion subsequently converts into a train of attosecond density peaks. Light thereby becomes a tool for synthesizing the electron wave function itself, setting when, where, and how narrowly the electron density concentrates. Here we study
photon-induced near-field electron microscopy (PINEM) to gain control over that synthesis in two stages: first for a single PINEM interaction, whose design parameters we obtain in closed form, and then for multiple PINEM interactions acting in parallel, which extends the control across space and time. The design rules follow from decomposing the propagated density into temporal harmonics, which we classify into three: (i) the arrival time of the attosecond train, fixed by the optical phase of the coupling; (ii) the distance at which the train forms, set by diffraction at the point where all classical trajectories converge; and (iii) the pulse duration, fixed by the imprinted energy spread. We evaluate these parameters for a scanning-electron-microscope (SEM) configuration at 10~keV, where the compression completes within tens of micrometers from the interaction region, with results 20% better than previous approaches. Letting the electron then interact with several spatially separated near fields in parallel, normal to the trajectory, each pathway carrying its own coupling strength and optical phase, we show that retaining or erasing which-path information changes both the propagated density and the measurable energy spectrum, the latter providing in turn a measure of the mutual coherence of the driving fields. These results establish PINEM as a quantitative synthesis tool for free-electron wave functions in compact, low-voltage electron microscopes.
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Optics
Boosting the photon bunching of classical light via a modified Fabry-Pérot cavity
Lu Zhang, Dongxu Zhou, Hongzhi Zhang et al. (+1 more)
We proposed to boost the
photon bunching effect of classical light via a modified Fabry-Pérot cavity with one of the cavity mirrors being replaced by a spatial light modulator, through which multiple independent transverse modulations, each was to encode independently spatially correlated phase on the wave front of the light field, was cascaded in sequence in the longitudinal propagation direction in the cavity. The two-
photon bunching peak and the three-
photon bunching peak of the generated superbunching light field were measured to be $36.9\pm2.0$ and $\rm (2.46\pm0.12)\times10^{3}$, respectively, which, as compared to those of thermal light, were improved by one-order and three-order of magnitude, respectively. Correspondingly, the ghost image visibility reconstructed with the superbunching light was demonstrated experimentally to be improved by $\sim 40$ times as compared to that with the pseudo-thermal light. Such classical superbunching light field is of essential importance not only for fundamental physics but also for potential applications such as correlated imaging, ghost interference and nonlinear optics.
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All authors Lu Zhang, Dongxu Zhou, Hongzhi Zhang, Guoquan Zhang
Optics
In-line Dispersion Control of Femtosecond Laser Pulses by Multilayer Huygens' Metasurfaces
Anna Fitriana, Katsuya Tanaka, Roland Schiek et al. (+3 more)
Dispersion is a key limiting factor in ultrafast systems as it modifies the temporal structure of ultrashort optical pulses. Conventional dispersion compensation techniques, though widely used, rely on a combination of several bulky optical components and complex, long propagation paths, posing challenges for integration into compact photonic platforms. All-dielectric resonant metasurfaces operating in the Huygens' regime of spectrally overlapping electric and
magnetic dipolar resonances offer a promising route to low-loss dispersion control at the sub-wavelength scale; however, the achievable dispersion from a single layer remains fundamentally limited by its phase gradient and spectral bandwidth. Here, we experimentally demonstrate in-line dispersion control of femtosecond
laser pulses using a multilayer architecture of dielectric Huygens' metasurfaces, without requiring spatial separation of their spectral components, as typically employed in
Fourier-plane dispersion compensation schemes. The phase dispersion accumulates across stacked layers approaching a total of 8pi, corresponding to a maximum group delay dispersion of around 3969 fs2. This enables efficient compensation of the input chirp and results in a significant compression of femtosecond
laser pulses in the telecom wavelength range. Importantly, the metasurface stack functions as a single compact transmissive element, which is simply inserted into the beam path. Overall, our results establish a compact, scalable platform for integrated pulse compression and ultrafast dispersion engineering.
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All authors Anna Fitriana, Katsuya Tanaka, Roland Schiek, Thomas Perstch, Dragomir Neshev, Isabelle Staude
Optics · Cross-listed from cs.CV
RACE-FPP: A Robust AI-assisted Characterisation Enhancement for Fringe Projection Profilometry
Osman Ali, Xiangjun Kong, Tibebe Yalew et al. (+2 more)
Fringe Projection Profilometry (FPP) requires precise system characterisation to achieve reliable three-dimensional (3D) reconstructions; however, characterisation accuracy strongly depends on robust checkerboard feature localisation, which can deteriorate under challenging imaging conditions such as lens blur and characterisation target orientations. Existing deep learning-based corner detectors are typically assessed using detection metrics and camera reprojection error alone, without considering their wider impact on projector characterisation, camera-projector stereo characterisation consistency, or overall measurement accuracy. In this work, we introduce a complete FPP characterisation pipeline that incorporates deep learning-based corner detection into the standard camera characterisation workflow. We also characterise the projector by sampling phase values at the centres of the white squares in the characterisation target. Rather than treating corner detection as an isolated task, the proposed framework explicitly analyses how localisation errors propagate throughout the entire FPP characterisation chain. Performance is evaluated using detection metrics (e.g., precision and recall), camera and projector reprojection errors, and the camera and projector stereo characterisation. Across a mixed
dataset of clean and degraded images, the camera reprojection error is reduced from 1.237 pixels to 0.259 pixels, while the projector reprojection error is reduced by roughly 50%. Dimensional evaluation of reconstructed artefacts shows improved
geometric accuracy compared with those resulting from the conventional pipeline. Overall, the findings indicate increased robustness of system-level characterisation under challenging imaging conditions, thereby enabling more reliable industrial FPP measurements.
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All authors Osman Ali, Xiangjun Kong, Tibebe Yalew, Waiel Elmadih, Samanta Piano
Instrumentation and Detectors
Omnidirectional Radiation Detector with Perpendicular Dual Silicon Photomultiplier Readout - Directional Sensitivity and Machine Learning Source Positioning
Ana Marija Kožuljević, Gabriela Jazvac, Luka Lotina et al. (+1 more)
Directional information of incident gamma rays in radiation detection is essential to many applications, from medical imaging to mapping radioactive contamination after nuclear accidents, characterization of nuclear waste during decommissioning, and nuclear security. In this work, we present a radiation detector capable of detecting gamma-ray
photons in 4$\pi$, utilizing Gadolinium Aluminum Gallium Garnet (GAGG) scintillating
crystals and silicon photomultipliers (SiPMs). The GAGG
crystals are assembled in a cubical 4$\times$4$\times$4
matrix, and their light output is read out by SiPMs from two neighboring sides. The size of each
crystal is 3$\times$3$\times$3 mm$^3$, while the
matrix pitch is 3.2 mm, matching the size and the pitch of the 4$\times$4 SiPMs for one-to-one coupling. The layers perpendicular to the SiPMs are separated by optical reflectors, providing efficient light collection while lowering the probability of inter-
crystal leakage. The design of the radiation detector offers high detection efficiency and full-view imaging of gamma-ray sources through Compton scattering. Monte Carlo simulations were performed in Geant4 to evaluate the detection efficiency of the proposed design due to its geometrical non-uniformity. Machine learning models developed with the XGBoost
algorithm were trained and tested on the simulated data to assess the capability of the detector to localize point sources of 511, 662, and 1275 keV energies. We find that the proposed design does not influence the collection efficiency of the high-energy gamma-ray
photons and offers sensitivity to the direction of the incoming gamma rays. The trained models are capable of determining the source-to-detector distance of the Na-22 and Cs-137 point sources from measurements, thus providing initial conditions for faster image reconstruction.
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All authors Ana Marija Kožuljević, Gabriela Jazvac, Luka Lotina, Luka Pavelić
Plasma Physics
Fast-ion effects on $E\times B$ staircase organization and the heat-flux response to the ion-temperature gradient
Il-Hwan Kim and Jaemin Seo
Zonal-flow organization can modify the relation between heat flux and temperature gradient, but how fast ions affect this organization and the accompanying transport response remains less well characterized. We use nonlinear, global gyrokinetic simulations based on KSTAR fast-ion-regulated enhancement (FIRE) mode to compare cases with and without fast ions during profile relaxation across five initial main-ion temperature gradients. We observe that fast ions induce larger zonal-flow and shearing-rate amplitudes, together with persistent shear layers. At the reference profile based on the experiment, these shear layers coexist with temperature-gradient corrugations qualitatively consistent with $E\times B$ staircases. When fast ions are present, inward and outward ion heat fluxes coexist at different radii, which causes the average heat flux to be smaller than when fast ions are absent. This redistribution of ion heat transport may be relevant to understanding the improved ion confinement observed in FIRE mode. In particular, we note a transition-like response in the presence of fast ions, whereby the heat flux decreases as the ion-temperature gradient increases, in contrast to the conventional Fick's law trend without fast ions. This behavior that deviates from Fick's law suggests that FIRE mode may represent a bifurcation to a distinct transport regime rather than a continuous high-performance extension of L-mode. These findings highlight the importance of the initial temperature gradient and global zonal-flow organization when assessing fast-ion effects on ion heat transport.
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Computational Physics · Cross-listed from math.NA
AdHImEx: Adaptively High-Order Implicit-Explicit Transport for Large Time Steps
Amber J. te Winkel, Hilary Weller, Christian Kühnlein et al. (+1 more)
Adaptively Implicit-Explicit (AdImEx) time stepping provides stability for large time steps for mass-conservative transport, making it attractive for the numerical representation of advection in weather and
climate prediction. Existing AdImEx transport schemes become first-order accurate in the large-time-step, implicit regime and may require multiple sparse
matrix solutions per time step. This work introduces AdHImEx, a new AdImEx scheme that addresses both limitations simultaneously. AdHImEx provides second-order accuracy for large Courant numbers while requiring only a single
matrix solution per time step. It is a Runge-Kutta scheme that blends third-order accurate explicit time stepping and Crank-Nicolson implicit time stepping to provide numerically verified stability for Courant numbers up to 100. AdHImEx is designed for flows that are predominantly explicit, activating implicit time stepping only where large Courant numbers occur. It retains the full efficiency and third-order accuracy of the explicit time stepping in regions with small Courant numbers. In this work, it is combined with a fifth-order accurate finite-volume discretisation in space for mass conservation. A second contribution of this work is a novel stage-dependent treatment of the divergence operator that preserves constancy despite different implicit and explicit Runge-Kutta stage time steps and spatially varying implicitness, removing spurious divergence. This innovation is applicable to other AdImEx time stepping schemes. Convergence, transport, and efficiency tests demonstrate substantial improvements over previous first-order AdImEx schemes, little phase and amplitude error, accurate transport on locally refined meshes with large Courant numbers, and promising efficiency characteristics for atmospheric transport.
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All authors Amber J. te Winkel, Hilary Weller, Christian Kühnlein, James Kent
Physics and Society
A New Model for the Income Distribution
Ekrem Aydiner
In this study, we propose a kinetic trap–
diffusion model to describe the emergence of Pareto distributions in money-exchange systems. Using kinetic Monte Carlo simulations, we show that the Pareto exponent depends explicitly on temperature and takes values in the range $0.5 \leq \nu(T) \leq 1.5$. In the present framework, the temperature $T$ acts as a control parameter that regulates the exchange dynamics through thermally activated
diffusion. Unlike conventional kinetic exchange models, where the Pareto exponent is fixed by microscopic rules, the proposed model generates a range of Pareto exponents as a function of $T$. The temperature-dependent Pareto exponent constitutes the central novelty of the proposed kinetic trap–
diffusion framework. This feature provides a natural explanation for the empirically observed variations in Pareto exponents across different countries and economic conditions. In addition, the fraction of zero-wealth
agents and the Gini index exhibit a non-monotonic dependence on temperature, revealing distinct dynamical regimes arising from the competition between trapping and money mobility. The persistence of the Pareto-like stationary distribution under strongly nonuniform initial conditions further supports the robustness of the proposed mechanism. These results show that different Pareto-tail and inequality regimes can emerge from the same trap–
diffusion dynamics through changes in a single control parameter
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Computational Physics · Cross-listed from cond-mat.soft
Efficient Searches for Low-Energy Structures in Clusters with Thousands of Particles: Application to the Thomson Problem
Paolo Amore and David J. Wales
We propose an
algorithm for identifying low-energy minima in systems containing thousands of particles, at moderate computational cost. We focus on spherical
crystals, in which particles form ordered structures on the surface of a sphere. Our method uses symmetric seed configurations, or known structures, to initialize searches across contiguous ranges of system sizes. Newly identified minima are then used to guide searches at neighbouring sizes, allowing information to propagate efficiently through configuration space. We have tested this approach on the Thomson problem, one of the few interacting-particle systems for which global optimization has been considered for systems of this size. We substantially improve on many previous solutions, particularly at larger system sizes, where systematic global optimization is computationally expensive. Since favourable packings for the Thomson problem are reflected in systems spanning atomistic to mesoscopic length scales, the newly characterized defect patterns may inform structure prediction for a broad range of problems with spherical
topology.
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Physics and Society
Social Physics: A manifesto
János Kertész, Marc Barthelemy, Guido Caldarelli et al. (+19 more)
Social Physics seeks quantitative, empirically testable explanations of collective human behavior. Its name has a long and contested history, but its contemporary program is neither the claim that society is literally a physical system nor an attempt to replace the social sciences with physics. It is an interdisciplinary practice: observation and experimentation, model construction, mathematical and computational analysis, and repeated confrontation with data. The field has been transformed by analyzing digital traces, network science,
agent-based modeling, large-scale experiments, and the capacity to study coupled dynamics across economic, social, technological, biological, and physical layers. We review advances in financial analysis and modeling; economic complexity; the structure and
evolution of social networks; spreading, opinion, and information dynamics; inequality, cooperation, conflict, mobility, cities, culture, science, and collective behavior; and the emerging study of human-AI ecosystems. Across these domains, common features recur - heterogeneity, interaction, feedback, adaptation, non-
equilibrium dynamics, multiscale organization, and emergent collective outcomes. We also confront the limitations that have arisen in this field: convenience samples, platform dependence, weak causal identification, over-universal claims, insufficient engagement with meaning and institutions,
privacy risks, and the danger that predictive models become instruments of manipulation. We propose a future Social Physics organized around theory - data reciprocity; causal and generative explanation; measurement validity and cross-context generalization; responsible, participatory data governance; genuinely interdisciplinary collaboration; and reflexive study of interventions and
algorithms that alter the systems being observed.
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All authors János Kertész, Marc Barthelemy, Guido Caldarelli, Bikas K. Chakrabarti, Tiziana Di Matteo, Serge Galam, Marta Gonzales, Yurij Holovatch, Janusz A. Holyst, Sarika Jalan, Hawoong Jeong, Neil F. Johnson, Renaud Lambiotte, Linyuan Lü, Thomas Lux, Rosario N. Mantegna, Matjaz Perc, Jari Saramäki, Michael Small, Misako Takayasu, Taha Yasseri, Wei-Xing Zhou
Medical Physics
Laplace-Domain Beamforming for Ultrafast Plane-Wave Imaging
Martin F. Schiffner
Fourier-domain beamforming methods, such as filtered backpropagation (FBP), are beneficial in ultrafast plane-wave imaging due to their computational efficiency and high image quality. These methods use the
Fourier diffraction
theorem (FDT) for steered plane waves to exactly invert linear scattering models. However, these models rely on simplifying assumptions that degrade image quality. The use of linear transducer arrays, in particular, requires: (i) a two-dimensional space, and (ii) lossless tissues. Herein, Laplace-domain beamforming is proposed. This method retains the computational efficiency of the
Fourier-domain methods while improving image quality for linear arrays. Specifically, the method uses a generalization of the FDT, here called Laplace diffraction
theorem, to account for three spatial dimensions, finite array element heights, and lossy tissues. A phantom experiment showed that the proposed method improves image uniformity, spatial resolution, and contrast compared to FBP. Using three steering angles, the lateral and axial -6 dB-widths of wires reduced by up to 12% and 25%, respectively, while the contrast of anechoic regions improved by up to 9%.
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Medical Physics
Gold nanorod radioenhancement: interpreting Monte Carlo dose enhancement across geometry, composition, coating, and localization
Ali Taheri, Hans Rabus, Mayeen Uddin Khandaker et al. (+2 more)
Nanoparticle radiosensitization depends on interconnected NP properties, yet geometry, elemental composition, surface coating, and localization are typically studied separately, with their combined biological impact rarely assessed in one framework. Drawing on TOPAS Monte Carlo simulations from PhD research, we consolidated four investigations of metallic nanorods, mainly gold nanorods (AuNRs), examining these parameters across closely linked studies. The findings reveal that each parameter can influence over a distinct spatial range. Nanorod geometry primarily alters the spectrum and distribution of low-energy Auger-Meitner electrons emitted within tens of nanometers. Elemental composition induces significant near-field dose enhancement that rapidly attenuates and becomes negligible beyond roughly 1 um. Surface coatings reduce the fluence of secondary electrons below 3.5 keV, absorbed within about 150 nm of the surface, lowering physical dose contribution by 1-7%. Since coatings predominantly remove low-energy electrons, radiolytic yield changes through a shift in the electron energy spectrum, not directly following dose response. At the vascular scale, the enhanced dose region extends to approximately 10 um from the vessel wall, meaning NP localization determines where the biological target sits relative to radiation sources. Collectively, no single design parameter serves as a universal predictor of radiosensitization. Translating physical radioenhancement into biological effect depends on whether the target lies within each parameter's effective range. Furthermore, charged-particle
equilibrium (CPE) correction, applied where beam confinement necessitated it, substantially alters calculated dose enhancement ratios. Consequently, scoring distance and CPE-corrected values should be explicitly reported to ensure comparability across studies.
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All authors Ali Taheri, Hans Rabus, Mayeen Uddin Khandaker, Farhad Moradi, David Andrew Bradley
Optics
Beyond Group Delay: Fundamental Limits of Achromatic Metasurfaces
Roman Buisine, Nicolas Kossowski, Adelin Patoux et al. (+3 more)
Achromaticity is one of the most demanding functionalities achievable with a metasurface because it requires reproducing the same optical response over a finite spectral bandwidth rather than at a single wavelength. Although previous studies established aperture-bandwidth limits based on temporal-delay considerations, the role of optical performance on these limits has remained unresolved. Here, we develop a rigorous theoretical framework that explicitly highlights how the optical performance sets the true aperture-bandwidth limit of single interface achromatic metasurfaces, quantifying the fundamental limits through the Strehl ratio. We identified two distinct operating regimes. In the first, the achromaticity conditions are exactly satisfied, guaranteeing diffraction-limited performance across the entire bandwidth. Surprisingly, the maximum achievable aperture in this regime is essentially independent of bandwidth and is instead governed by the ability of practical meta-atoms to simultaneously realize the required phase and dispersion. In the second regime, relaxing the required optical performance allows larger apertures at the cost of a fundamental trade-off between aperture, bandwidth, and optical performance. Numerical validation using a large library of high-transmission GaN meta-atoms confirms the theory and reveals the transition between these regimes. Our framework establishes the fundamental limits of achromatic metasurfaces, providing practical design rules for balancing aperture, bandwidth, and optical performance of achromatic metasurfaces.
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All authors Roman Buisine, Nicolas Kossowski, Adelin Patoux, Patrice Genevet, Rémi Colom, Samira Khadir
Geophysics
Ground roll suppression based on the synchrosqueezed wavelet transform and local adaptive subtraction filtering
Zifei Li, Zhengyu Tan and Shaohuan Zu
Ground roll suppression remains a challenge in land seismic data processing, particularly when strong surface wave energy exhibits significant overlap with effective reflection events in the low frequency band. Conventional approaches, such as frequency-wavenumber (F-K) filtering, Radon transform-based methods, and other spatial filtering techniques, often fail to achieve satisfactory results under such conditions due to limited resolution and poor amplitude preservation. To address this problem, a time-frequency domain ground roll suppression method that integrates the synchrosqueezed wavelet transform (SSWT) with local adaptive subtraction filtering is proposed. First, seismic traces are transformed from the time-space domain into the time-frequency domain using SSWT, which provides a highly concentrated time-frequency representation. Based on the distinct distribution characteristics of ground roll noise and effective reflection signals in the time-frequency domain, a ground roll model is extracted. Subsequently, a local adaptive subtraction filter is applied to adjust the amplitude and phase of the extracted ground roll model, and the corrected model is subtracted from the original seismic data to obtain the final suppressed result. Applications to both synthetic and field seismic data demonstrate that the proposed method effectively attenuates ground roll energy while maximally preserving the amplitude and waveform characteristics of reflection signals. Compared with conventional time-frequency-based ground roll suppression approaches, the proposed method exhibits superior amplitude fidelity and improved noise attenuation performance.
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Plasma Physics · Cross-listed from astro-ph.SR
Does Diffusive Shock Acceleration Reach Steady State? Insights from a Near-Sun Shock Observed by Parker Solar Probe
Immanuel Christopher Jebaraj, Mikhail Malkov, Nicolas Wijsen et al. (+7 more)
Collisionless shocks accelerate particles at a rate set by the
diffusion coefficient of those particles in waves they themselves generate. Theory fixes that coefficient only in steady state, and no measurement has tested whether an evolving shock ever reaches that state. We report Parker Solar Probe observations of a fast, near-parallel interplanetary shock at 0.24 au, encountered four hours after eruption, with the upstream waves and the
protons they scatter recorded on the same
magnetic field line. From the wave spectra alone we derive the parallel mean free path of 0.05-30 MeV
protons, resolved in energy and in distance from the shock. The mirror force of the measured compressive fluctuations supplies the scattering through the pitch angles that gyroresonance cannot reach. The mean free path grows with distance nearly as the steady self-generated solution requires, yet the steady balance holds at one energy only, near 1.3 MeV. The intensity profiles are a factor of two shallower than the measured coefficient predicts, because the waves are still growing. Confinement fails between 2.3 and 6 MeV, beginning a factor of two below what the age of the shock allows. The growth of the waves its own particles drive, rather than its age or its size, limits the energy an evolving shock confines.
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All authors Immanuel Christopher Jebaraj, Mikhail Malkov, Nicolas Wijsen, Oleksiy Agapitov, Athanasios Kouloumvakos, Alexandr Afanasiev, Federico Fraschetti, Edin Husidic, Christina Cohen, Rami Vainio
Atomic Physics
Total-field atomic magnetometry using an elliptically-polarized frequency-modulated light beam for geomagnetic-field applications
D.V. Brazhnikov, A.O. Makarov, K.S. Kozlova et al. (+10 more)
We investigate an all-optical scheme for high-sensitivity measurements of the Earth's scale
magnetic field ($B$). The scheme is based on the Bell-Bloom technique with frequency-modulated light. A single elliptically polarized light beam is used both for pumping the alkali-metal atoms and probing Larmor precession of their
spins under the external
magnetic field. In contrast to many other high-sensitivity magnetometry schemes based on nonlinear polarization rotation of the light, the proposed approach enables the observation of
magnetic resonance via changes in the light-beam ellipticity parameter. The approach has been validated in experiments with a vertical-cavity surface-emitting
laser, irradiating a $0.125$ cm$^3$ cesium vapor
cell filled with a buffer gas. In the current experimental conditions, the achieved sensitivity is estimated at $220$ fT/$\surd$Hz under $B$$\,\approx\,$$50$ $\mu$T, while the shot-noise floor corresponds to $\approx\,$$20$ fT/$\surd$Hz. The bandwidth is estimated at $\approx\,$$1$ kHz. The proposed simple and robust single-beam scheme is well suited for miniaturization and is therefore particularly promising for the development of compact, highly sensitive, low-power-consumption atomic magnetometers for a wide range of applications in the geomagnetic field.
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All authors D.V. Brazhnikov, A.O. Makarov, K.S. Kozlova, M.A. Rusina, A.M. Mikhailov, V.A. Vasiliev, E.V. Tanakov, A.N. Goncharov, M.A. Bobrov, Ya.N. Kovach, A.A. Blokhin, N.A. Maleev, S.A. Blokhin
Fluid Dynamics
A Lagrangian analysis of coherent structures in 2D annular Rayleigh-Bénard convection
Luis Álamo, Jezabel Curbelo and Kathrin Padberg-Gehle
Convective instabilities are studied from a Lagrangian perspective in order to gain new insights into how the resulting global, long-lived coherent flow structures organize themselves. We consider a 2D annular fluid layer uniformly heated from the inside and subject to radial
gravity and propose several new Lagrangian diagnostics for characterizing its convective instabilities. In particular, we perform a comprehensive Lagrangian analysis of the flow field across a wide range of dimensionless parameters, establishing a heuristic correspondence between convective plumes and curves of local maxima of Finite-Time Lyapunov Exponent (FTLE) fields. Moreover, we characterize coherent swirling motions inside convective rolls, which are associated to the non-zero
curvature of the flow. By introducing a sliding window method for our finite-time kinematic measures, we demonstrate a direct relationship with radial heat flux quantified by means of the Nusselt number and identify relevant dynamical transitions that leave a trace on both. Finally, we propose a formal criterion for determining viscous boundary layer (UBL) thickness by virtue of radial FTLE profiles and validated against a classical Eulerian method.
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Chemical Physics
Learning consistent molecular mechanics force fields from first principles
Berkay Günes, Leif Seute, Jigyasa Nigam et al. (+1 more)
Classical force fields (FFs) remain the workhorse for large-scale simulations even as machine-learned interatomic potentials (MLIPs) approach ab initio accuracy. They decompose total configuration energies into simple effective interactions whose parameters are traditionally assigned based on atom or bond types, enabling efficient simulations but also limiting their ability to adapt across configurations. Recent machine learning approaches have improved the accuracy and transferability of bonded parameters in these FFs by inferring them as functions of local atomic environments, but still rely on empirical nonbonded parameters for practical simulations. In this work, we introduce a unified approach, grappa-fullFF, which learns both bonded and nonbonded parameters consistently and simultaneously from ab initio reference data. By incorporating physically inspired regularization via supervision of the electrostatic potential and an architecture that facilitates charge equilibration, our model recovers accurate electric response properties, achieves state-of-the-art accuracy on geometry optimization
benchmarks, and reproduces the conformational sampling of both classical and existing machine-learned FFs, without relying on externally assigned nonbonded parameters.
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All authors Berkay Günes, Leif Seute, Jigyasa Nigam, Frauke Gräter
Optics · Cross-listed from quant-ph
Squeezed light from a semiconductor amplifier
Andrey S. Aleksandrov and Anatoly V. Masalov
The possibility of generating light in a squeezed
quantum state during saturated light amplification in a
semiconductor amplifier is theoretically analyzed. Due to four-wave mixing process during amplification, weak components of the spontaneous emission of the medium with symmetric frequency shifts relative to the strong amplified wave acquire the
quantum properties of two-mode squeezed light. The squeezing of quadrature components occurs in the range of frequency shifts of several GHz ($\sim$ the inverse relaxation time of the charge carrier density) and can reach 10 dB or more under optimal conditions. The formation of a two-mode squeezing phase facilitates the observation of the squeezing effect, in which a strong wave, playing the role of a local wave, exhibits quadrature noise suppression without additional homodyne detection.
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Biological Physics
Spatiotemporal Oscillations Driven by Spatial Heterogeneity and Growth
Lewis S. Mosby, Mohit P. Dalwadi and Zena Hadjivasiliou
Temporal oscillations arise naturally in biological systems with feedback loops or explicit delays. When incorporating spatial effects, the travel times of propagating signals can also generate intrinsic delays, and this behaviour is complicated further in the presence of spatial heterogeneity. In this work, we investigate the mechanistic origin and dynamics of spatiotemporal oscillations driven by intrinsic diffusive delays in a representative activator-inhibitor system with spatial heterogeneity using a combination of mathematical modelling, simulations and numerical methods. In contrast to delay-differential equation models where delays are explicitly prescribed, in the partial differential equation system we consider here delays are an intrinsic consequence of signal travel time through space. We demonstrate that undamped oscillations can arise as a result of spatially heterogeneous feedback when the system size increases through a critical length. At this critical length the time for systems to reach steady-state diverges, and the systems first exhibit an
eigenvalue with a positive real part and non-zero imaginary part, corresponding to a Hopf bifurcation. We infer that this critical length could define a theoretical upper limit for the size of systems where oscillations hinder function. The analysis pipeline derived in this work offers a novel route for understanding the onset of spatiotemporal oscillations and Hopf bifurcations in a diverse array of biological systems where interactions are mediated by diffusive species.
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Optics
An Acousto-Optic Colorimeter
Pavel Aksentsev, Georgiy Lobarev, Sergey Korchagin et al. (+2 more)
Uniform color spaces and color-difference formulae rest on visual data obtained almost entirely with surface samples and conventional displays, whose primaries confine the measurements to a limited chromaticity range. The highly saturated region of color space is therefore the least measured part of human color perception, at the moment when
quantum-dot, microLED, and
laser displays have begun to operate inside it. Closing this gap requires stimuli more saturated than any fixed-primary device can produce, together with the stability and uniformity demanded by visual experiments. We present an acousto-optic colorimeter built for this purpose. A four-channel acousto-optic tunable filter selects narrow spectral components from a supercontinuum
laser over the calibrated range of 443–660~nm, with measured linewidths of 1.37–3.20~nm; the wavelength and radiance of every component are set electronically, so the primary set itself becomes an experimental variable. A compact diffuser–light-pipe homogenizer combines the selected components into a uniform observation field, and spectral feedback stabilizes their intensities. The calibrated primary set covered 95% of the area enclosed by the CIE 1964 $10^{\circ}$ spectral locus in the $x,y$ chromaticity plane. The calculated maximum luminance reached 1406~cd\,m$^{-2}$, with 328~cd\,m$^{-2}$ available at the gray Robertson chromaticity. Across an 18-mm observation field the mean spatial $\Delta E_{00}$ difference was 0.913, and five Robertson color centers reproduced under continuous feedback gave mean target errors of 0.34–1.26~$\Delta E_{00}$ over 10-min intervals. The instrument thus delivers calibrated, uniform, and stable highly saturated stimuli, and is intended to extend the empirical basis of color-difference measurement into the region where data are still absent.
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All authors Pavel Aksentsev, Georgiy Lobarev, Sergey Korchagin, Olga Polschikova, Egor Ershov
Physics and Society · Cross-listed from q-fin.TR
A Finite Bid–Ask Spread from Replenishment Displaced from the Quote
Christopher Angstmann, Derick Diana and Tim Gebbie
We give a unified analytic account of a finite bid–ask spread in a two-field reaction–
diffusion order book. The model retains separate bid and ask densities in operational time, with
diffusion, cancellation, reaction and external order creation. On the symmetric equal-coefficient branch, the imbalance field determines the reaction price, while the total standing density carries the spread geometry. A
market-making source is introduced by withholding order placement over a finite interval around the reaction boundary, representing round-trip replenishment displaced from the quote. Under a separated, quasistationary and weak-overlap approximation, transport penetrates inward from the placement edges over the cancellation length, giving the quoted spread as the sub-threshold core of the placement-source-free interval.
Market orders remove standing density at the observed quote, whereas replenishment is delivered outside it and must diffuse back across the penetration depth. We derive the resulting delayed and attenuated quote-level response in operational time. On that branch, finite spread and price impact arise from distinct response sectors, while their calendar-time appearance requires a separate observation clock.
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Physics and Society
Probabilistic neighbors' selection competes with confirmation bias in a bounded confidence model
Chiara Giaquinta, Laura Hernández and David Chavalarias
In this work, we investigate three modified versions of the classic Hegselmann-Krause opinion dynamics model, incorporating features that are typical of many real-world systems, such as uncertainty in the selection of interacting
agents and a weighted evaluation of the relevance of their opinions in the influence function to enhance confirmation bias. Through extensive simulations across different network
topologies, ranging from stylized network models (Barabási-Albert, Erdős-Rényi, and Watts-Strogatz networks) to empirical networks with community structure, we identify the influence of each modification on opinion
evolution and convergence. Our findings reveal that they exert opposite effects on the bounded confidence threshold required for consensus. We further explore an extension based on a data-driven opinion initialization on the empirical networks, where initial opinions are drawn from Gaussian distributions specific to each detected community. While the qualitative effects of the three modified models remain consistent, this new initialization strategy reveals distinct dynamics within the network communities. These insights provide a new and comprehensive perspective on how realistic variations of the Hegselmann-Krause model, in terms of both interaction rules and initial opinion distributions, affect opinion dynamics and shed light on the mechanisms of consensus formation within structured communities.
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Optics · Cross-listed from astro-ph.IM
Optimizing Laguerre-Gaussian Mode Interferometry in Gravitational-Wave Detectors through Modal Degeneracy Breaking
Liu Tao, Eleonora Capocasa and Matteo Barsuglia
Higher-order Laguerre-Gaussian modes can reduce test-mass thermal noise in gravitational-wave interferometers, but their implementation is limited by degeneracy-induced coupling losses in realistic high-finesse cavities. We mitigate these losses by optimizing the mirror
curvature to break modal degeneracy. We develop a general framework for designing an axisymmetric corrective test-mass surface profile that lifts the degeneracy of the sixth-order Laguerre-Gaussian subspace while preserving an injected donut-shaped $\mathrm{LG}_{0,6}$ mode. Expanded in a
Fourier-Bessel basis, the profile is optimized to maximize the frequency splitting from the nearest unwanted mode while minimizing target-mode loss. For a Virgo-like Fabry-Perot arm cavity, the optimized profile separates the $\mathrm{LG}_{0,6}$ resonance from the nearest same-order resonance, $\mathrm{LG}_{1,4}$, by 2.04% of the free spectral range, reducing unwanted-mode gains below unity at the target-mode resonance and suppressing their resonant enhancement. The profile introduces negligible target-mode loss and improves robustness against astigmatism and realistic mirror surface distortions. Monte Carlo simulations with realistic mirror imperfections yield an average contrast defect of 368 ppm and an average reflected optical loss of 979 ppm, equivalent to a round-trip loss of approximately 3.5 ppm for the modeled cavity. These results substantially improve upon the central anti-reflective mirror mask approach based on selective loss engineering, bringing reflected optical loss within a factor of two of that obtained with the fundamental Gaussian mode under the same simulation conditions. This approach offers a route toward robust donut-shaped Laguerre-Gaussian modes in future precision interferometers with realistic imperfections.
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