Computational Physics
Physics Enhanced Deep Surrogates for the Phonon Boltzmann Transport Equation
Antonio Varagnolo, Giuseppe Romano and Raphaël Pestourie
Designing materials with controlled heat flow at the nano-scale is central to advances in microelectronics, thermoelectrics, and energy-conversion technologies. At these scales,
phonon transport follows the Boltzmann Transport Equation (BTE), which captures non-diffusive (ballistic) effects but is too costly to solve repeatedly in inverse-design loops. Existing surrogate approaches trade speed for accuracy: fast macroscopic solvers can overestimate conductivities by hundreds of percent, while recent data-driven operator learners often require thousands of high-fidelity simulations. This creates a need for a fast, data-efficient surrogate that remains reliable across ballistic and diffusive regimes. We introduce a Physics-Enhanced Deep Surrogate (PEDS) that combines a differentiable
Fourier solver with a neural generator and couples it with uncertainty-driven active learning. The
Fourier solver acts as a physical inductive bias, while the network learns geometry-dependent corrections and a mixing coefficient that interpolates between macroscopic and nano-scale behavior. PEDS reduces training-data requirements by up to 70% compared with purely data-driven baselines, achieves roughly 5% fractional error with only 300 high-fidelity BTE simulations, and enables efficient design of porous geometries spanning 12-85 W m$^{-1}$ K$^{-1}$ with average design errors of 4%. The learned mixing parameter recovers the ballistic-diffusive transition and improves out of distribution robustness. These results show that
embedding simple, differentiable low-fidelity physics can dramatically increase surrogate data-efficiency and interpretability, making repeated PDE-constrained optimization practical for nano-scale thermal-materials design.
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Data Analysis and Statistics · Cross-listed from nlin.CD
Quantifying the irregularity of a time series
Max Potratzki, Manuel Adams, Timo Bröhl et al. (+1 more)
We introduce circulance, a scalar measure for classifying time series of dynamical systems. Circulance captures the extent of temporal regularity or irregularity that is encoded in the
topology of a directed ordinal pattern transition network derived from a time series. We demonstrate numerically that circulance sensitively and robustly positions time series of canonical model systems, representative of preset dynamical regimes, along a continuous spectrum from regularity to randomness. Analyzing empirical data from long-term observations of high-dimensional, complex systems – human
brain and the Sun – reveals that circulance aids in elucidating different dynamical regimes.
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All authors Max Potratzki, Manuel Adams, Timo Bröhl, Klaus Lehnertz
Biological Physics
The rationality of radical pair mechanism in real biological systems
Xiaoyu Chen, Haibin Liu and Jianming Cai
The radical pair mechanism (RPM) in the chemical
magnetic compass model is considered to be one of the most promising candidates for the avian
magnetic navigation, and
quantum needle phenomenon further boosts the
navigation precision to a new high level. It is well known that there are also a variety of methods in the field of
magnetic field sensing in laboratory, e.g. Ramsey protocol of NV centers in diamond. Here, we compare the RPM model and Ramsey-like model under laboratory conditions and under in vivo conditions respectively. The results are both surprising and reasonable. Under laboratory conditions, if we have precise control over time and a reasonably accurate prior knowledge of the
magnetic field direction, the Ramsey-like model will outperform the RPM model. However, when such information is unavailable, as under in vivo conditions, the RPM model stands out. The RPM model achieves greater practicality at the cost of reduced accuracy.
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Computational Physics · Cross-listed from cond-mat.soft
Gravitational aggregation regimes: critical dissipation threshold, optimal rigidity and fractal transition
Yohann Trivino
I present a three-dimensional Discrete Element Method study of self-gravitation and contact mechanics in cold granular assemblies. The model couples direct Newtonian attraction between every particle pair with a linear visco-elastic normal contact law. Particles are treated as non-cohesive spheres; the normal force is parameterized to reproduce a prescribed restitution coefficient. Rotations are integrated using quaternions to avoid singularities. By normalizing the stiffness kn by kstar = G*m^2/R^3 and time by the free-fall time t_ff, I perform systematic parameter campaigns over dissipation (gamma) and normalized stiffness ktilde = kn/kstar. Results reveal three aggregation regimes. For low gamma the particles remain largely dispersive; above a critical gamma of about 5e2 aggregation accelerates until plateaus are reached in the aggregation time T_agg divided by t_ff. For stiffness ktilde on the order of 1e6 the aggregation time reaches a clear minimum. The cluster fraction C/Ntot shows a non-monotonic dependence on ktilde, with optimal cohesion at intermediate
rigidity and peripheral isolation at extreme stiffness. Mapping the fractal dimension F across (gamma, ktilde) demonstrates transitions from compact structures (F about 3) to ramified structures (F below 2). These findings quantify how microscopic contact laws govern both the kinetics and microstructure of
gravity-driven aggregation, providing a predictive framework for planetesimal formation and for calibrating DEM models against laboratory and micro-
gravity experiments.
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Physics and Society · Cross-listed from cs.SI
Accumulated Local Effects and Graph Neural Networks for link prediction
Paulina Kaczyńska, Julian Sienkiewicz and Dominik Ślęzak
We investigate how Accumulated Local Effects (ALE), a model-agnostic explanation method, can be adapted to visualize the influence of node feature values in link prediction tasks using Graph Neural Networks (GNNs), specifically Graph Convolutional Networks and Graph
Attention Networks. A key challenge addressed in this work is the complex interactions of nodes during message passing within GNN layers, complicating the direct application of ALE. Since a straightforward solution of modifying only one node at once substantially increases computation time, we propose an approximate method that mitigates this challenge. Our findings reveal that although the approximate method offers computational efficiency, the exact method yields more stable explanations, particularly when smaller data subsets are used. However, the explanations produced with the approximate method are not significantly different from the ones obtained with the exact method. Additionally, we analyze how varying parameters affect the accuracy of ALE estimation for both approaches.
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Medical Physics · Cross-listed from cs.LG
Energy-Efficient Federated Learning via Adaptive Encoder Freezing for MRI-to-CT Conversion: A Green AI-Guided Research
Ciro Benito Raggio, Lucia Migliorelli, Nils Skupien et al. (+6 more)
Federated Learning (FL) holds the potential to advance equality in health by enabling diverse institutions to collaboratively train deep learning (DL) models, even with limited data. However, the significant resource requirements of FL often exclude centres with limited computational infrastructure, further widening existing healthcare disparities. To address this issue, we propose a Green AI-oriented adaptive layer-freezing strategy designed to reduce energy consumption and computational load while maintaining model performance. We tested our approach using different
federated architectures for
Magnetic Resonance Imaging (MRI)-to-Computed
Tomography (CT) conversion. The proposed adaptive strategy optimises the
federated training by selectively freezing the encoder weights based on the monitored relative difference of the encoder weights from round to round. A patience-based mechanism ensures that freezing only occurs when updates remain consistently minimal. The energy consumption and CO2eq emissions of the federation were tracked using the CodeCarbon library. Compared to equivalent non-frozen counterparts, our approach reduced training time, total energy consumption and CO2eq emissions by up to 23%. At the same time, the MRI-to-CT conversion performance was maintained, with only small variations in the Mean Absolute Error (MAE). Notably, for three out of the five evaluated architectures, no statistically significant differences were observed, while two architectures exhibited statistically significant improvements. Our work aligns with a research paradigm that promotes DL-based frameworks meeting clinical requirements while ensuring climatic, social, and economic sustainability. It lays the groundwork for novel FL evaluation frameworks, advancing
privacy, equity and, more broadly, justice in AI-driven healthcare.
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All authors Ciro Benito Raggio, Lucia Migliorelli, Nils Skupien, Mathias Krohmer Zabaleta, Oliver Blanck, Francesco Cicone, Giuseppe Lucio Cascini, Paolo Zaffino, Maria Francesca Spadea
Fluid Dynamics
Direct numerical simulation of thermo-diffusively unstable premixed hydrogen-air flames in a fully-developed turbulent channel flow at $Re_\tau=530$
Felix Rong, Max Schneider, Hendrik Nicolai et al. (+2 more)
Direct Numerical Simulations (DNS) of premixed hydrogen-air flames anchored in a fully-developed turbulent channel flow (TCF) are performed at a friction Reynolds number of $\mathrm{Re}_\tau=530$ and thermochemical conditions susceptible to the emergence of intrinsic thermo-diffusive (TD) phenomena acting on the turbulent flame. Two premixed flames are studied: a slower flame ($\varphi=0.25$), predominantly propagating within the core flow, and a faster one ($\varphi=0.35$), reaching closer to the channel walls and intermittently quenching on it. The present DNS database provides new insights into the characteristics of premixed flames susceptible to TD phenomena and propagating in realistic near-wall shear
turbulence. The influence of varying
turbulence intensity, and of wall-distance dependent time and length scales, on the flame propagation characteristics is evaluated through a detailed analysis of the local stretch factor $I_0$, quantifying reactivity enhancements caused by TD phenomena. At $\varphi=0.25$, the flame response to the fluid motions is mainly forced by the weaker
turbulence present in the core flow. This results in an augmented $I_0$ compared to the laminar reference value, suggesting reactivity enhancement by the strongly non-linear interaction of TD phenomena with (relatively) weak turbulent motions present within the core flow. At $\varphi=0.35$, as the flame propagates from the core flow towards the channel walls, the flame response is forced by
turbulence of increasing intensity, resulting in a corresponding augmentation of the Karlovitz number. Crucially, as the flame propagates into the near-wall region, the peak value of $I_0$ is co-located with the peak Reynolds stresses ($y^+ \sim 10$). This observation suggests a strong (local) synergistic interaction between TD phenomena and wall
turbulence, ultimately resulting in significantly enhanced flame speed.
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All authors Felix Rong, Max Schneider, Hendrik Nicolai, Christian Hasse, Andrea Gruber
Atomic Physics
High-Resolution Laser Spectroscopy on the Hyperfine Structure of $^{255}$Fm (Z=100)
M. Urquiza-González, M. Stemmler, T. E. Albrecht et al. (+36 more)
We report on high-resolution
laser spectroscopy of $^{255}$Fm ($T_{1/2} = 20$h), one of the heaviest nuclides available from reactor breeding. The hyperfine structures in two different atomic ground-state transitions at 398.4~nm and 398.2~nm were probed by in-source
laser spectroscopy at the RISIKO mass separator in Mainz, using the PI-LIST high-resolution ion source. Experimental results were combined with hyperfine fields from various atomic ab-initio calculations, in particular using MultiConfigurational Dirac-Hartree-Fock theory, as implemented in GRASP18. In this manner, the
nuclear magnetic dipole and electric quadrupole moments were derived to be $\mu = -0.75(5)~ \mu_\textrm{N}$ and $Q_\textrm{S} = +5.84(13)$~eb, respectively. The
magnetic moment indicates occupation of the $\nu$~7/2[613] Nilsson orbital, while the large quadrupole moment confirms strong, stable prolate deformation consistent with systematics in the heavy actinides. Comparisons with available expectation values from
nuclear theory show good agreement, providing a stringent
benchmark for the used theoretical models. These results revise earlier data and establish $^{255}$Fm as a reference isotope for future high-resolution studies.
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All authors M. Urquiza-González, M. Stemmler, T. E. Albrecht, B. Bally, M. Bender, S. Berndt, M. Block, A. Brizard, J. S. Andrews, J. Bieron, P. Chhetri, H. Dorrer, C. E. Düllmann, J. G. Ezold, S. Goriely, M. J. Gutiérrez, D. Hanstorp, R. Hasse, R. Heinke, K. Hens, S. Hilaire, M. Kaja, T. Kieck, N. Kneip, U. Köster, A. T. Loria Basto, C. Mokry, D. Münzberg, K. Myhre, T. Niemeyer, S. Péru, S. Raeder, D. Renisch, J. Runke, S. K. Schrell, D. Studer, K. van Beek, J. Warbinek, K. Wendt
Physics Education
Virtual high voltage lab: gamified learning in a safe 3d environment
Vladyslav Pliuhin, Yevgen Tsegelnyk, Maria Sukhonos et al. (+3 more)
The integration of immersive technologies has transformed engineering education, particularly in high-risk disciplines like high-voltage engineering, which is essential for urban energy infrastructure. This study presents a 3D virtual laboratory developed using Unreal Engine 5 to support the High Voltage Engineering course for undergraduate students in Power Engineering, Electrical Engineering, and Electromechanics. The research investigates how an immersive, gamified virtual laboratory enhances learning outcomes, safety training, and preparedness for urban infrastructure challenges. We hypothesize that VLab-HV significantly improves student engagement, knowledge retention, practical skills, and safety awareness compared to traditional laboratories, contributing to urban energy system resilience. Through ten curriculum-aligned experiments, gamified interactions, and AI-driven pedagogical tools, VLab-HV offers a risk-free environment for mastering HV concepts. Evaluation via usability testing, engagement metrics, and surveys confirms superior learning outcomes. The study highlights the role of VLab-HV in training engineers and professionals for urban energy challenges, with planned expansions for multiplayer and virtual reality integration.
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All authors Vladyslav Pliuhin, Yevgen Tsegelnyk, Maria Sukhonos, Ihor Biletskyi, Sergiy Plankovskyy, Taras Sakhoshko
Accelerator Physics
Analytical Approximations for Beamstrahlung at Very High Energy Electron-Positron Colliders
Dongxing He, Arianna Formenti, Spencer Gessner et al. (+1 more)
Among the many effects that occur in beam-beam electron-positron collisions at TeV energies, emission of hard synchrotron radiation, or beamstrahlung, has special importance. Beamstrahlung determines the energy spectrum of the most energetic electrons, positrons, and
photons and supplies the initial condition for the calculation of all other QED processes. In this paper, we show that the description of beamstrahlung simplifies in the limit of large
quantum parameter $\Upsilon$, which is realized in 10 TeV
collider designs. The beamstrahlung spectra for electrons and
photons are given in terms of universal functions. We supply approximations to these functions that will be useful for more general studies of the beam-beam interaction at very high energies.
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All authors Dongxing He, Arianna Formenti, Spencer Gessner, Michael Peskin
Atmospheric and Oceanic Physics
Extratropical Atmospheric Circulation Response to ENSO in Deep Learning Pacific Pacemaker Experiments
Zhanxiang Hua, Christina Karamperidou and Zilu Meng
Coupled atmosphere-ocean deep learning (DL)
climate emulators are a new frontier but are known to exhibit weak ENSO variability, raising questions about their ability to simulate teleconnections. Here, we present the first Pacific pacemaker (PACE) experiments using a coupled DL emulator (DLESyM) to bypass this weak variability and isolate the atmospheric response to observed ENSO forcing. We find that while the emulator realistically captures internal atmospheric variability, it produces a significantly amplified forced teleconnection response to ENSO. This amplified response leads to biases in simulating extremes, notably an overestimation of atmospheric blocking frequency and duration with the underestimation of peak intensity. Our findings underscore that coupled DL
climate models require in-depth and physically-grounded validation, analogous to traditional numerical models, to build confidence in their use for physical
climate analysis.
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Atmospheric and Oceanic Physics
The early history of Marine Cloud Brightening (MCB); the legacy of John Latham and Stephen Salter
Alan Gadian
This paper discusses the initial development of Marine Cloud Brightening (MCB) as a theoretical idea, from its inception as a cloud microphysics process in circe 1990 to the full-blown concept by 2015. It primarily focuses on the work of founders John Latham and Stephen Salter and their contributions. Recently the concept has been developed further, e.g. in the UK ARIA project, as a prospective method to ameliorate the Earths rapid warming.
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Biological Physics
An Affordable Fiducial Marker Strategy for Reliable Autofocus in Long-Term Live Microscopy
Ilyas Djafer-Cherif and Bartlomiej Waclaw
Long-term time-lapse imaging of biological samples requires correcting for focal drift, which would otherwise gradually push the sample out of focus. We present a software-based method that eliminates this time-dependent blur using only a motorized Z-drive, with no additional hardware. The method relies on imaging marks made on the side of the coverslip opposite to the sample. We provide a Beanshell script implementation, evaluate its performance across multiple objectives, and
benchmark it against a hardware autofocus system, finding comparable results. Finally, we demonstrate its effectiveness in live imaging of growing bacterial colonies.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
Cr2O3/e̱ta}-Ga2O3 Heterojunction Diodes with Orientation-Dependent Breakdown Electric Field up to 12.9 MV/cm
Yizheng Liu, Haochen Wang, Carl Peterson et al. (+3 more)
We report the fabrication of Cr2O3/e̱ta}-Ga2O3 heterojunction diodes using reactive magnetron sputtering of Cr2O3 on highly doped e̱ta}-Ga2O3 bulk substrates along (100), (010), (001), (110), and (011) orientation dependence of high electric field handling capability in e̱ta}-Ga2O3. Additional relative permittivity values in (110) and (011) orientations of e̱ta}-Ga2O3 were computed by using first-principles calculation methods for accurate apparent charge density (ND-NA) extraction and breakdown electric field analysis from capacitance-voltage measurements. The HJDs fabricated on n+ (110) exhibited breakdown electric fields >10 MV/cm up to 12.9 MV/cm, showing the highest experimentally observed parallel-plane junction electric field among e̱ta}-Ga2O3-based junctions. Breakdown electric fields among (100), (010), (001), and (011) orientations showed distinct distribution in the range of 5.13-5.26 MV/cm, 5.10-7.05 MV/cm, 2.70-3.33 MV/cm, and 3.88-4.38 MV/cm, respectively, validating the orientational dependence of parallel-plane junction electric field at breakdown in low-
symmetry monoclinic e̱ta}-Ga2O3. The parallel-plane breakdown electric fields (EBr,||) reported in this work were extracted when the device experienced catastrophic breakdown at 100 mA/cm^2 current density compliance, and should not be confused with critical electric field (Ec) as a function of drift layer doping concentration, which accounts for electric-field dependent impact ionization coefficients in Si, SiC and GaN. This study can guide the choice of
crystal orientation for high performance gallium
oxide-based devices that require high electric field handling capability.
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All authors Yizheng Liu, Haochen Wang, Carl Peterson, James S. Speck, Chris Van De Walle, Sriram Krishnamoorthy
Fluid Dynamics
Uncovering bistability phenomena in two-layer Couette flow experiments using nonlocal evolution equations
Xingyu Wang, Pierre Germain and Demetrios T. Papageorgiou
This paper investigates the stability of interfacial long waves in two-layer plane Couette flow using a nonlinear, nonlocal asymptotic model derived from the Navier-Stokes equations and valid for thin upper layers. Nonlocality enters through a coupling of the thin and main layers, and crucial inertial effects are retained. The models generically support bistability phenomena observed in experiments where two stable travelling waves, one unimodal and the other bimodal, are recorded at the same lid velocity. In direct comparisons with experiments, the models show remarkable agreement, both qualitatively and quantitatively. The two stable travelling waves are identified and their basins of attraction characterised via large-time computations for different initial conditions. We also identify a new
symmetry-breaking travelling-wave branch bifurcating from the bimodal family, compute higher-wavenumber travelling-wave branches, and present time-periodic orbits arising via
Hopf bifurcation.
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Instrumentation and Detectors
Evaluating the Effective Segregation Coefficient in High-Purity Germanium (HPGe) Crystals for Ge Detector Development in Rare-Event Searches
S. Chhetri, D.-M. Mei, S. Bhattarai et al. (+5 more)
The performance and scalability of rare-event physics experiments depend on large-volume, detector-grade high-purity germanium (HPGe)
crystals with precise control of
impurity segregation during growth. We report a detailed study of
impurity distribution in a single Czochralski-grown HPGe
crystal produced at University of South Dakota (USD). The
crystal was sectioned longitudinally into 37 segments, enabling the first high-resolution and systematic mapping of dopant profiles along the length of a detector-grade HPGe boule.
Hall-effect measurements were used to extract
impurity concentrations for boron (B), aluminum (Al), gallium (Ga), and phosphorus (P) in each segment. From these data, we determine effective segregation coefficients ($K_{eff}$) and initial melt concentrations ($C_0$) for the dominant dopants and compare them with classical Burton-Prim-Slichter expectations. The results provide quantitative insight into
impurity transport and melt-solid partitioning under realistic detector growth conditions. These findings inform process-optimization strategies for HPGe
crystal pulling, improve
impurity control along the boule, and support the reliable fabrication of large, low-background HPGe detectors for next-generation rare-event searches.
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All authors S. Chhetri, D.-M. Mei, S. Bhattarai, N. Budhathoki, A. Warren, K.-M. Dong, S.A. Panamaldeniya, A. Prem
Instrumentation and Detectors
Tungsten Germanide Superconducting Nanowire Single-Photon Detectors with Saturated Internal Detection Efficiency at Wavelengths up to 29 {\mu}m
Benedikt Hampel, Daniel Kuznesof, Andrew S. Mueller et al. (+13 more)
Superconducting nanowire single-
photon detectors (SNSPDs) are among the most sensitive single-
photon detectors available and have the potential to transform fields ranging from infrared astrophysics to molecular spectroscopy. However, extending their performance into the mid-infrared spectral region - crucial for applications such as
exoplanet transit spectroscopy and vibrational fingerprinting of molecules - has remained a major challenge, primarily due to material limitations and scalability constraints. Here, we report on the development of SNSPDs based on tungsten germanide, a novel material system that combines high mid-infrared sensitivity with compatibility for large-scale fabrication. Our detectors exhibit saturated internal detection efficiency at wavelengths up to 29 {\mu}m, while using 2.7x thicker films (8 nm vs 3 nm) and up to 4.5x wider nanowires (360 nm vs 80 nm) compared to mid-infrared-optimized SNSPDs fabricated from tungsten silicide. This advance will enable scalable, high-performance single-
photon detection in a spectral region that was previously inaccessible, opening new frontiers in remote sensing, thermal imaging, environmental monitoring, molecular physics, and astronomy.
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All authors Benedikt Hampel, Daniel Kuznesof, Andrew S. Mueller, Sahil R. Patel, Robert H. Hadfield, Emma E. Wollman, Matthew D. Shaw, Dirk Schwarzer, Alec M. Wodtke, Khalid Hossain, Allison V. Mis, Alexana Roshko, Richard P. Mirin, Sae Woo Nam, Martin J. Stevens, Varun B. Verma
Instrumentation and Detectors
Investigating the Timing Behavior of Compton Scattering in BGO for Time-of-Flight PET
Minseok Yi, Daehee Lee, Alberto Gola et al. (+5 more)
Bismuth germanate (BGO) is gaining renewed
attention as a viable material for hybrid Cherenkov/scintillation time-of-flight positron emission
tomography (TOF-PET) detectors. While single-
crystal studies have demonstrated excellent timing resolution by leveraging
prompt Cherenkov
photons, practical detector modules based on pixelated arrays introduce a high prevalence of inter-
crystal scattering (InterCS) events, complicating timing accuracy. In this study, we experimentally investigated the impact of InterCS on BGO Cherenkov timing using a dual-pixel detector coupled to a segmented SiPM readout. Events were classified into full-energy deposition (FED; primary
crystal 511 keV absorption), InterCS, and penetration types via energy-weighted positioning and validated using GATE simulations, which also revealed that over 25% of the experimentally identified full-energy events involved intra-
crystal scatter (IntraCS). For InterCS events, the optimal timestamp selection was achieved by choosing the earlier of the two timestamps, yielding a coincidence timing resolution of 221 ps FWHM (831 ps FWTM)-markedly worse than the 184 ps (603 ps FWTM) obtained for FED events. Furthermore,
prompt photon yield was found to decrease measurably due to energy splitting: InterCS events averaged 4.73 detected
photons in the first 1 ns, compared to 5.76 for FED events. These results emphasize the importance of incorporating time-aware, per-pixel timestamping strategies in pixelated BGO TOF-PET systems to maintain optimal timing performance in the presence of scatter.
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All authors Minseok Yi, Daehee Lee, Alberto Gola, Stefano Merzi, Michele Penna, Simon R. Cherry, Jae Sung Lee, Sun Il Kwon
Chemical Physics
Bridging Atomistic and Mesoscale Lithium Transport via Machine-Learned Force Fields and Markov State Models
Muhammad Nawaz Qaisrani, Christoph Kirsch, Aaron Flötotto et al. (+4 more)
Lithium
diffusion in solid-state battery anodes occurs through thermally activated hops between metastable sites often separated by large energy barriers, making such events rare on ab initio molecular dynamics (AIMD) timescales. Here, we present a bottom-up multiscale workflow that integrates AIMD, machine-learned force fields (MLFFs), and Markov state models (MSMs) to establish a quantitatively consistent link between atomistic hopping mechanisms and mesoscale transport. MLFFs fine-tuned on AIMD reference data retain near-DFT accuracy while enabling large-scale molecular dynamics simulations extending to tens of nanoseconds. These extended trajectories remove the strong finite-size bias present in AIMD and yield
diffusion coefficients in excellent agreement with experiment. Furthermore, from these long MLFF trajectories, we obtain statistically converged lithium jump networks and construct MSMs that remain Markovian across more than two orders of magnitude in the lag times used for their construction. The resulting MSMs faithfully reproduce mean-square displacements and recover rare
diffusion processes that do not occur on AIMD timescales. In addition to propagating lithium distributions, the MSM transition
matrices provide mechanistic insight: their
eigenvalues and eigenvectors encode characteristic relaxation timescales and dominant transport pathways. Although demonstrated for defect-free crystalline Li$_x$Si$_y$ phases, the AIMD$\rightarrow$MLFF$\rightarrow$MSM framework is general and provides a transferable approach for describing lithium transport in amorphous materials, defect-mediated
diffusion, and next-generation solid-state anodes.
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All authors Muhammad Nawaz Qaisrani, Christoph Kirsch, Aaron Flötotto, Jonas Hänseroth, Jules Oumard, Daniel Sebastiani, Christian Dreßler
Optics
Nonreciprocal Negative Refraction Enabled by Photonic Time Crystals
Mohammad R. Tavakol and Wenshan Cai
We propose and theoretically demonstrate nonreciprocal negative refraction enabled by time-varying photonic structures. By engineering temporal modulations at the interfaces of
hyperbolic media, we achieve isolation between forward and backward beams while preserving the hallmark property of negative refraction. Two complementary approaches are developed: in the optical regime, a multilayer AZO/ZnO
hyperbolic slab is sandwiched between permittivity-modulated dielectric layers (3D time
crystals); in the microwave regime, a wire medium is sandwiched between time-modulated resistive metasurfaces (2D time
crystals). Both designs exploit Floquet harmonic expansions and are validated with a customized harmonic-balance finite-element solver. We report isolation exceeding 46 dB in the optical device and ~11 dB in the microwave counterpart. This work introduces a general framework for nonreciprocal negative refraction across frequency regimes, expanding the design space of time-varying metasurfaces and photonic time
crystals.
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Classical Physics
Generalizing Shell Theorem to Constant Curvature Spaces in All Dimensions and Topologies
Ava K. Tse, Olivia M. Markowich and Trung V. Phan
A gravitational potential has the spherical property when the field outside any uniform spherical shell is indistinguishable from that of a point mass at the center. We present the general potentials that possess this property on constant
curvature spaces, using the Euler-Poisson-Darboux identity for spherical means. Our results are consistent with known findings in flat three-dimensional space and reduce to Gurzadyan's cosmological
theorem when the rescaling factor is exactly $1$. Our approach naturally extends to nontrivial spatial
topologies.
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Applied Physics
Depletion-limited Effective Hall mobility in Micrometer-Scale High-Purity Germanium Crystals
Narayan Budhathoki, Dongming Mei, Sanjay Bhattarai et al. (+5 more)
Electrostatic effects can strongly constrain charge transport in thinned high-purity germanium (HPGe), with direct implications for radiation detectors and Ge-based electronic and
quantum devices. We report a systematic experimental characterization of the thickness-dependent effective
Hall mobility in bulk-grown, detector-grade HPGe at room temperature using
Hall-effect measurements on n- and p-type samples sequentially thinned from 2.7~mm to 7~\textmu m. The intrinsic bulk carrier mobility remains thickness independent in this regime; the observed reduction in
Hall-extracted mobility arises from electrostatic surface depletion that reduces the electrically active conducting thickness. The thickness-dependent data are accurately parameterized by an empirical extended-exponential relation, $\mu(t)=\mu_{0}[1-\exp(-(t/\tau)^{\beta})]$, where $\tau$ is a characteristic electrostatic length scale. Comparison with boundary-scattering and depletion-based models shows that Fuchs–Sondheimer scattering is negligible, while electrostatic depletion dominates the transport behavior. The hierarchy $\lambda_{D}<\tau\lesssim W_{0}$ directly links the apparent mobility reduction to long-range screening and near-surface electric fields. These results yield a simple design guideline: maintaining thicknesses $t\gtrsim 3\tau$ preserves near-bulk transport, whereas thinner structures operate in a depletion-controlled regime with strongly reduced effective conductivity.
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All authors Narayan Budhathoki, Dongming Mei, Sanjay Bhattarai, Sunil Chhetri, Kunming Dong, Shasika Panamaldeniya, Athul Prem, Austin Warren
Fluid Dynamics · Cross-listed from cond-mat.soft
The metastability of lipid vesicle shapes in uniaxial extensional flow
M.A. Shishkin and E.S. Pikina
In this work, we investigate the elastic properties of deflated vesicles and their shape dynamics in uniaxial extensional flow. By analysing the Helfrich bending energy and viscous flow stresses in the limit of highly elongated shapes, we demonstrate that all stationary vesicle configurations are metastable. For vesicles with small reduced volume, we identify the type of bifurcation at which the stationary state is lost, leading to unbounded vesicle elongation in time. We show that the stationary vesicle length remains finite at the critical extension rate. The critical behaviour of the stationary vesicle length and of the growth rates of small perturbations is obtained analytically and confirmed by direct numerical computations. The beginning stage of the unbounded elongation dynamics is simulated numerically, in agreement with the analytical predictions.
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Atmospheric and Oceanic Physics
Sunlight, the Bond Albedo, CO2, and Earth's Temperature
R. Louw, W. A. van Wijngaarden and W. Happer
The main determinants of Earth's absolute surface Temperature, T, are the
solar constant, S, the Bond albedo, A, and the effective emissivity for thermal radiation, e. In this note we assume that the value of the effective emissivity, e = e(C), is determined by the atmospheric concentration C of CO2. We show that the
solar constant is most important, the albedo is second, and the CO2 concentration is a distant third.
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Computational Physics · Cross-listed from cs.LG
Physics Steering: Causal Control of Cross-Domain Concepts in a Physics Foundation Model
Rio Alexa Fear, Payel Mukhopadhyay, Michael McCabe et al. (+2 more)
Foundation models trained on text and images have been shown to develop abstract internal features that align with human concepts and that can be directly manipulated via activation steering to alter model behaviour. Whether scientific foundation models learn similarly abstract and domain-general representations has remained an open question. Inspired by recent work identifying single directions in activation space that control complex behaviours in large
language models, we show that Walrus, a large physics foundation model, learns linearly steerable representations of physical phenomena. By computing the difference between activations representing contrasting physical regimes, we identify single directions in activation space that correspond to vorticity,
diffusion, and even temporal progression. We find that injecting these concept directions back into the model during inference enables fine-grained causal control:
vortices can be induced or removed,
diffusion enhanced or suppressed, and simulations sped up or slowed down. Moreover, directions derived from one physical system also steer the behaviour of other physical systems, suggesting that they are domain-general. These results provide early evidence that scientific foundation models can learn general representations of physical principles, and further support for the Linear Representation Hypothesis.
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All authors Rio Alexa Fear, Payel Mukhopadhyay, Michael McCabe, Alberto Bietti, Miles Cranmer
Optics
Super-resolution microscopy via fluctuation-enhanced spatial mode demultiplexing
Stanislaw Kurdzialek
We introduce a superresolution technique that combines spatial mode demultiplexing (SPADE) with emitter blinking. We show that temporal fluctuations not only enhance the precision of SPADE imaging, but also drastically simplify the measurement required to recover full object information—in the presence of fluctuations, SPADE can be replaced by the much simpler image inversion interferometry. Both gains are enabled by exploiting temporal cumulants of the detected signal. We further show that the proposed fluctuation-enhanced techniques are significantly more robust to dark-count noise than conventional SPADE.
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General Physics
The EGUP-Induced Critical Radius: A New Holographic Scale for Quantum Gravity
Sara Motalebi
We present a unified framework incorporating both the Generalized and Extended Uncertainty Principles (GUP/EUP) in Anti-de Sitter space. This reveals a fundamental
quantum gravity scale, the critical radius $r_{\rm crit}=(\beta/\gamma)^{1/4}\sqrt{\ell_{P}L}$, which marks a phase transition where
quantum gravitational ($\beta$) and AdS
curvature ($\gamma$) effects equilibrate. At this scale, we demonstrate three interconnected phenomena: (i) a breakdown of the standard
holographic duality, signaled by the exact vanishing of the boundary stress tensor $\langle T_{\mu\nu}\rangle=0$ under the self-duality condition $\partial_z g_{\mu\nu}|_{z=r_{\rm crit}}=0$; (ii) a topological transition manifested by the complexification of the central charge, $c_{\rm eff}=c\left(1+\frac{i}{2}\sqrt{\kappa}\ell_{P}^{2}\right)$ with $\kappa=(\beta/\gamma)^{1/4}\sqrt{\beta\gamma\ell_P/L}$; and (iii) a mechanism as a scenario for information paradox resolution, where information is recovered via topological storage in Chern-Simons states, modifying the Page curve with $\Delta S_{\rm recovery}>0$. These effects establish a consistency condition $L>\sqrt{\beta}\ell_{P}$ for a valid AdS/CFT correspondence and identify $r_{\rm crit}$ as the thermodynamic critical point where black holes transition to stringy remnants and information is topologically scrambled.
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Computational Physics · Cross-listed from quant-ph
Opportunities and Challenges of Computational Electromagnetics Methods for Superconducting Circuit Quantum Device Modeling: A Practical Review
Samuel T. Elkin, Ghazi Khan, Ebrahim Forati et al. (+5 more)
High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects, these numerical methods are referred to as computational electromagnetics (CEM) methods. Although the CEM research field is mature, emerging applications can still stress the capabilities of the techniques in use today. The design of superconducting
circuit quantum devices falls in this category due to the unconventional material properties and important features of the devices covering nanometer to centimeter scales. Such multiscale devices can stress the fundamental properties of CEM tools which can lead to an increase in simulation times, a loss in accuracy, or even cause no solution to be reliably found. While these challenges are being investigated by CEM researchers, knowledge about them is limited in the broader community of users of these CEM tools. This review is meant to serve as a practical introduction to the fundamental aspects of the major CEM techniques that a researcher may need to choose between to model a device, as well as provide insight into what steps they may take to alleviate some of their challenges. Our focus is on highlighting the main concepts without rigorously deriving all the details, which can be found in many textbooks and articles. After covering the fundamentals, we discuss more advanced topics related to the challenges of modeling multiscale devices with specific examples from superconducting
circuit quantum devices. We conclude with a discussion on future research directions that will be valuable for improving the ability to successfully design increasingly more sophisticated superconducting
circuit quantum devices. Although our focus and examples are taken from this area, researchers from other fields will still benefit from the details discussed here.
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All authors Samuel T. Elkin, Ghazi Khan, Ebrahim Forati, Brandon W. Langley, Dogan Timucin, Reza Molavi, Sara Sussman, Thomas E. Roth
Data Analysis and Statistics · Cross-listed from hep-ph
The Intrinsic Dimension of Collider Events and Model-Independent Searches in 100 Dimensions
Raffaele Tito D'Agnolo, Alfredo Glioti, Gabriele Rigo et al. (+1 more)
The phase space of
hadron collider events spans hundreds of dimensions, generating an intricate geometry that we are just starting to explore. The number of possible new physics signals is exponential in the number of dimensions and detecting all of them is currently impossible for any human or artificial intelligence. In this work we introduce a method to search for new physics model-independently in this high-dimensional space. It is based on the measurement of the most basic property of the
manifold of
collider events, its dimensionality. Our proposed technique does not suffer from a look-elsewhere effect that grows exponentially with the number of dimensions of the
dataset, and by construction is insensitive to energy scale uncertainties. We illustrate its potential by finding new physics in simulated events with hundreds of phase space dimensions, taking as input single particles rather than jets. This study sets the stage for new model-independent search strategies based on global properties of
collider data
manifolds.
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All authors Raffaele Tito D'Agnolo, Alfredo Glioti, Gabriele Rigo, Alessandro Valenti
Biological Physics
Rectification of stress by fiber networks: Manifestation of non-linear screening through self-organized buckling
Kanaya Malakar, Albert Countryman and Bulbul Chakraborty
Force transmission at large length scales is crucial for such biological functions as
cell motility and morphogenesis. The networks that transmit these forces are malleable, patterned by active forces generated at the microscale by biological motors. In this paper we explore a simple model of a non-linear fiber network which has only two modes of deformation, but exhibits diverse mechanical phases with distinct large-scale response, tuned by the strength of a microscopic force dipole. We demonstrate, via numerical simulations, that the network is remodeled by organized patterns of buckling, which lead to a renormalization of the Poisson ratio. Finally, we show that the emergent behavior at large length scales can be ascribed to "mechanical screening" of the force dipole, analogous to dielectric screening of charges in electrostatics.
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