Chemical Physics
Bosonic Condensed Phase Real-time Dynamics from Ring Polymer Molecular Dynamics
Yotam M. Y. Feldman, Sourav Karmakar, Sutirtha Paul et al. (+3 more)
We present a method for approximating real-time correlation functions and
quantum transport coefficients of bosonic condensed phases. The direct evaluation of
quantum real-time correlation functions in the path integral formulation is impossible due to a severe dynamical sign problem. Evaluating imaginary-time correlation functions and inverting them using analytic continuation is famously ill-posed. Ring
polymer molecular dynamics (RPMD) provides an alternative approach resulting in accurate approximations for real-time correlation functions of condensed phases but neglects exchange effects. In this work, we develop a bosonic RPMD method, which is exact in the harmonic, short time, and high temperature limits. A critical enabling observation is that the Kubo-transformed correlation function for
bosons is real only when the correlated observables are symmetric under exchange. We
benchmark the method on harmonic and anharmonic model systems and then use it to directly obtain the Lieb-Liniger gas density-density real-time correlation functions at various temperatures and momentum transfers. This work enables the direct simulation of finite-temperature, real-time dynamics of large bosonic condensed phases using RPMD for the first time.
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All authors Yotam M. Y. Feldman, Sourav Karmakar, Sutirtha Paul, Jacob Higer, Adrian Del Maestro, Barak Hirshberg
Physics and Society
Does a rising tide lift all boats? A wealth exchange model on a dynamic network with economic growth
Gustavo L. Kohlrausch and Sebastian Gonçalves
Wealth inequality, although an age-old problem, has seen a substantial rise since the early XXI century. The distributions of wealth and income across countries follow a universal pattern, typically manifesting as a two-class division, which suggests that fundamental mechanisms underpin the emergence of these economic disparities.
Agent-based models, which allow the rules of interaction between economic
agents to be explicitly defined, are particularly well-suited for studying economic systems and analyzing their emergent properties. In this work, we examine a recently proposed dynamic complex network
agent-based model within the context of a growing economy. The model evolves via three alternating processes: independent
stochastic wealth growth of each
agent, wealth exchanges between connected
agents, and the rewiring of connections within the complex network. The wealth growth of each
agent is governed by a
stochastic process characterized by two parameters: a drift term $\mu$, representing economic growth, and
volatility $\sigma$, reflecting heterogeneity in productivity. We analyze the outcomes for various values of a social protection factor $f$, which favors the poorer
agent in each transaction. Higher values of $f$ amplify the effect of economic growth: while increasing $\mu$ reduces inequality, increasing $\sigma$ has the opposite effect. In this context, economic growth benefits the poorest
agents only when strong social protection is in place.
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Data Analysis and Statistics
A Two-Regime Statistical Framework for Wind-Power Distributions: From Wind-Speed Fluctuations to Turbine Control
S. Mitra, S. E. Lakhal, C. P. Connaughton et al. (+2 more)
Wind-power variability is a major challenge for the reliable integration of utility-scale wind energy into modern power systems. Although wind-speed statistics are often described by simple parametric distributions, translating these statistics into turbine-level power fluctuations is nontrivial because the relationship between wind speed and power is highly nonlinear and changes across different turbine operating regimes. Here, we develop a two-regime statistical framework for wind-power distributions. In the aerodynamic operating regime, between the cut-in and rated speeds, the turbine power follows an approximate cubic dependence on wind speed. Starting from a physically motivated Rician model for the wind-speed magnitude, we derive an analytical expression for the corresponding wind-power distribution using a nonlinear change of variables. In the control-dominated near-rated regime, where active blade-pitch and generator control regulate the turbine output, the aerodynamic transformation is no longer applicable. Instead, we characterize the power deficit relative to the rated power and show empirically that its continuous tail is well described by a bounded stretched-exponential distribution for both individual turbines and wind-farm ensembles. These results provide a physically interpretable statistical description of wind-power fluctuations across the full operational range of utility-scale wind turbines.
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All authors S. Mitra, S. E. Lakhal, C. P. Connaughton, J. E. Sardonia, M. M. Bandi
Optics
Calibration of scintillator-based X-ray detectors for broadband laser-driven X-ray radiation
Orsolya Morvai, Benoit Lefebvre, Marcel Lamač et al. (+8 more)
Laser-driven X-ray sources produce broadband radiation with substantial shot-to-shot fluctuations, requiring calibrated detector-response models for quantitative measurements of
photon fluence and spectral distribution. Scintillator-based flat-panel detectors, originally developed primarily for medical and industrial X-ray imaging, are increasingly being adopted for diagnostics of
laser-
plasma-based X-ray sources because they provide large-area, spatially resolved detection. We report the calibration of two complementary X-ray detector systems: a CsI:Tl-based flat-panel detector and a plastic-scintillator filter-stack spectrometer intended for spectral reconstruction. Both detectors were characterized using well-defined ISO 4037 N-series reference radiation qualities, providing controlled polychromatic X-ray fields for establishing their signal response and signal-to-fluence conversion.
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All authors Orsolya Morvai, Benoit Lefebvre, Marcel Lamač, Uddhab Chaulagain, Petr Odstrčil, Dominik Čap, Vojtěch Janota, Alfred Haavaan Mishi, Romain Caye, Jaroslav Nejdl, Antonia Morabito
Atmospheric and Oceanic Physics
From Heat Stress to Perception: Interpretable Data-Driven Models of Human Thermal Sensation
Abed Hammoud, Xinjie Huang, Qinqin Kong et al. (+2 more)
Heat stress indices are designed to quantify physiological thermal stress, but their relevance for inferring the thermal perception of individuals remains unclear. In this study, we show that thermal stress and thermal sensation often diverge, as evidenced by distinct global sensitivity patterns with respect to environmental drivers. Using thermal sensation vote survey data, we demonstrate that the dominant sensitivities of stress-based metrics do not align with those governing reported human thermal sensation. Given the multitude of globally-applicable thermal stress indices and the lack of comparable general thermal sensation metrics, we develop two complementary data-driven modeling frameworks for thermal sensation. First, we construct
polynomial chaos expansion (PCE) surrogates to represent thermal sensation as a function of meteorological variables, enabling efficient variance-based sensitivity analysis and explicit identification of influential inputs and interactions. Second, we develop multilayer perceptron (MLP) classifiers that capture the nonlinear and subjective nature of thermal perception, while achieving high predictive accuracy. The PCE models provide physically interpretable sensitivities that can explain the drivers of thermal sensation, while the MLPs offer flexible predictive capability suited to complex environments. We apply both modeling approaches at city- and continent-scales, revealing systematic differences in sensitivity structure and performance across climates. In particular, we find that the sensitivity of TSV-based models to the variability of meteorological conditions across geoclimatic zone encodes distinct dependencies on temperature, radiation, humidity, and wind that vary geographically, and are generally different from those of heat stress indices.
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All authors Abed Hammoud, Xinjie Huang, Qinqin Kong, Marialena Nikolopoulou, Elie Bou-Zeid
Optics · Cross-listed from cond-mat.other
Topological Classification of Non-Normalizable Vector Fields
Philipp Gessler, Alessandro Pignedoli, Alexander Neuhaus et al. (+3 more)
Topological classification of physical vector fields conventionally relies on field normalization and homotopy-based invariants. However, when field amplitudes vanish, normalization becomes ill-defined, preventing a direct topological characterization. Here, we introduce a general framework for the topological classification of non-normalizable $n$-dimensional vector fields with compactifiable base spaces by transforming them into $(n+1)$-dimensional normalized vector fields. This construction extends homotopy-based classification to fields containing amplitude zeros. We explicitly demonstrate the approach for one-, two-, and three-dimensional non-normalized vector fields and derive the corresponding topological invariants. The resulting topological charges are robust under continuous deformations and can change only when the
embedding structure becomes singular. Our framework provides a unified route to the topological characterization of non-normalizable fields and opens the door to the study of topological phenomena in a broad range of systems, including
magnetic textures, ferroelectrics, electromagnetic fields, and wave systems.
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All authors Philipp Gessler, Alessandro Pignedoli, Alexander Neuhaus, Frank-J. Meyer zu Heringdorf, Maria Azhar, Karin Everschor-Sitte
Plasma Physics
Laser power transmission in space: Plasma-based power cell
Li Lin and Michael Keidar
Laser power beaming offers a route to space energy delivery, but
semiconductor laser photovoltaic receivers face thermalization, joule heat, and radiative recombination waste, etc. Here we propose a gas-phase
plasma power
cell that converts
vacuum-ultraviolet
photons into electrical output through xenon photoionization and magnetically biased charge separation. Particle-in-
cell Monte Carlo simulations of a low-pressure xenon chamber driven by a 58.4 nm pulsed
laser predict a steady-state
laser-to-electrical conversion efficiency of 82.25% at 2000 W/m2 average incident power. Energy accounting closes to 1%, with 7.52%
photon escape, 8.95% boundary loss, and 1.29% chamber-stored energy. Parameter scans over bias voltage,
magnetic field, and gas pressure identify
photon absorption and electron confinement as controlling design factors. These results are a proof-of-concept gas-phase receiver architecture for space
laser power beaming.
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Data Analysis and Statistics
Rician Distribution as a Physically Interpretable Model for Wind-Speed Statistics
S. Mitra, S. E. Lakhal, C. P. Connaughton et al. (+2 more)
The statistics of atmospheric wind variations are commonly modeled using Gaussian or Weibull forms, which often trade physical interpretability against statistical accuracy, especially in the distribution tails. Here we derive a Rician distribution for wind speed from a simple physical model based on two orthogonal Gaussian velocity components with a non-zero mean in the preferred direction. Using wind-speed records from four geographically distinct wind farms, we show that the Rician model consistently outperforms the Gaussian model and remains competitive with the Weibull model. The same behavior persists when the data are partitioned into monthly windows, where the Rician parameters also provide a transparent description of seasonal and geographic variability, compared to Weibull parameters. In addition, the model naturally connects Gaussian-like and Weibull-like regimes through the Rician parameter ratio $\mu/\sigma$, making the Rician distribution a compact and physically interpretable two-parameter model for wind-speed statistics.
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All authors S. Mitra, S. E. Lakhal, C. P. Connaughton, J. E. Sardonia, M. M. Bandi
Plasma Physics · Cross-listed from astro-ph.SR
Shear interaction and acceleration of a corotating stream detected by Parker Solar Probe
Andrea Verdini, Simone Landi, Emanuele Papini et al. (+4 more)
Recent analysis of Parker
Solar Probe (PSP) and
Solar Orbiter data indicates that fluctuations energy is transferred to the bulk flow in fast streams of the
solar wind at heliocentric distances between 15 and 120 Rsun. To gain insight into this process, we analyze data collected during the inbound orbit of PSP in Encounter 10, when it is in approximate corotation with the Sun and an accelerating stream is detected between 25 and 45 Rsun. The geometry of the flow indicates that a neighboring very fast streams is colliding with the corotating stream, causing large-scale
magnetic field distortion, density enhancement, and acceleration. However, also deposition of fluctuations' energy can heat and do work on the
solar wind
plasma, resulting in a radial acceleration. We evaluate the energy lost by fluctuations via radial variation of conserved quantities in the corotating stream and find that it is almost equally partitioned into heating and work. While the heating is marginally consistent with the non-adiabatic decrease of
proton temperature, the work exerted on the wind is insufficient to account for the measured
solar wind acceleration. Although limited to this event, observations suggest that shear interaction is capable of accelerating slower streams within relatively short distances from the Sun, possibly leaving its imprint as large-scale density and
magnetic fluctuations.
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All authors Andrea Verdini, Simone Landi, Emanuele Papini, Luca Franci, Petr Hellinger, Roberto Livi, Orlando Romeo
Space Physics · Cross-listed from astro-ph.SR
High-Frequency Magnetohydrodynamic Waves with Substantial Energy in the Solar Polar Corona
Yuhang Gao, Hui Tian, Richard Morton et al. (+5 more)
The acceleration and heating of the fast
solar wind remain long-standing challenges in space physics. One type of leading theoretical models requires high-frequency magnetohydrodynamic (MHD) waves to transport and dissipate sufficient energy in the corona. However, such high-frequency waves with energetically significant amplitudes have never been unambiguously observed, leaving a key gap between theories and observations. Using high-cadence, high-resolution extreme-ultraviolet imaging from
Solar Orbiter's Extreme Ultraviolet Imager, we identify a previously hidden population of high-frequency MHD waves in coronal plumes of the
solar polar region. An analysis of the detected propagating kink waves shows that over one-third have periods shorter than 100 s, a population largely undetected by earlier instruments. Power spectral analysis demonstrates that these high-frequency waves carry substantial energy flux, which are significantly underestimated in lower-cadence data. These results suggest that high-frequency MHD waves may contribute importantly to the energy budget of the
solar polar corona and could play a role in
solar wind acceleration, highlighting the value of high-resolution observations for probing energy transport in magnetized space and astrophysical
plasmas.
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All authors Yuhang Gao, Hui Tian, Richard Morton, Tom Van Doorsselaere, Daye Lim, Mingzhe Guo, Jiansen He, Zhenyong Hou
Atomic Physics
Near-deterministic loading of molecular arrays by microwave-assisted collisions
Etienne F. Walraven, Kang Feng, Jonas Rodewald et al. (+2 more)
Molecular tweezer arrays offer great prospects for
quantum simulation, sensing, and computing, and would benefit from methods that enhance loading efficiency. Whereas light-assisted collisions underpin enhanced loading methods for atomic tweezer arrays, this approach cannot be directly extended to molecular arrays due to collisional loss. We show how this collisional loss can be suppressed by shelving molecules in rotationally or vibrationally excited states, so that a shelved molecule interacts with a newly loaded molecule through a repulsive van der Waals interaction. By introducing microwave assisted collisions, we show how to control the final states and the energy released in a collision between a pair of molecules. Following this controlled collision, one of the two molecules can be ejected, and we explore several strategies for ensuring deterministic ejection. Our schemes rely on currently available techniques for
laser-coolable molecules, and we predict achievable filling fractions up to 96%, paving the way for scalable molecular arrays.
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All authors Etienne F. Walraven, Kang Feng, Jonas Rodewald, Michael R. Tarbutt, Tijs Karman
Physics and Society · Cross-listed from cond-mat.stat-mech
Macroscopic wall pressure and microscopic contact load in crowds without egress: social-group cohesion and boundary buffering
Bo-Shiun Shen and Son-Hsien Chen
Crowd safety in confined venues is usually evaluated through evacuation performance or pre-collision avoidance, while direct mechanical hazards in dense gatherings without egress remain poorly understood. We study an Elastic Reorientation Model (ERM), a Social Force Model (SFM), and their coupled dynamics. Post-collision behavior is represented by social-group cohesion ($\gamma_g$) and wall buffering ($\gamma_w$), while risk is quantified by the macroscopic wall line pressure ($P_{\text{wall}}$) and the microscopic maximum per-
agent collision impulse ($\delta p_{\text{max}}$). In the ERM, cohesion and wall buffering generally reduce $P_{\text{wall}}$ by retaining
agents in the bulk, but large groups exhibit a high-$\delta p_{\text{max}}$ hazard window at intermediate cohesion. As $\gamma_g\rightarrow1$, local pairing suppresses cluster growth and shifts kinetic energy from relative to center-of-mass motion, reducing $\delta p_{\text{max}}$. SFM pushing and sliding amplify $\delta p_{\text{max}}$, especially when
agent-
agent and
agent-wall interactions coexist, while active driving raises $P_{\text{wall}}$ through near-wall accumulation. The coupled dynamics produces a wall-pressure/contact-load ($P$-$p$) trade-off. Finite-size scaling reveals an independent-
agent-induced phase boundary at $\gamma_w=0.5$, characterized by a susceptibility discontinuity, and a grouped-
agent-induced continuous phase boundary along a finite segment of $(1-\gamma_w)(1-\gamma_g)=0.5$, characterized by divergent susceptibility and terminating at a critical point. Both disappear in the social-force-free ERM, showing that they emerge from the coupled ERM+SFM dynamics. These results provide mechanistic guidance for crowd-risk mitigation and safety planning in high-density venues without egress.
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Atomic Physics · Cross-listed from cond-mat.quant-gas
Tunable state-dependent interactions in collisionally stable mixtures of polar molecules
Hubert J. Jóźwiak, Hanwei Yang, Eugen Dizer et al. (+2 more)
We propose encoding a pseudo-
spin-$1/2$ system in the ground ($v=0$) and first excited ($v=1$) vibrational states of polar molecules. Double microwave shielding simultaneously shields molecules in both states, suppressing two-body losses by orders of magnitude while strictly avoiding three-body recombination. The microwave dressing is state-dependent and results in highly tunable, long-range dipolar Ising exchange ($J_z$), density-density ($V$), and
spin-density ($W$) interactions. These interaction length scales readily exceed the typical interparticle spacing, pushing the molecules deep into the strongly interacting regime. In bulk gases, this enables the exploration of itinerant
quantum magnetism and
quantum droplets with novel anisotropic
spin textures; in optical
lattices, it naturally realizes extended Hubbard and $t$-$J_z$ models, opening new directions in
quantum simulation.
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All authors Hubert J. Jóźwiak, Hanwei Yang, Eugen Dizer, Arthur Christianen, Tijs Karman
Atomic Physics · Cross-listed from cond-mat.quant-gas
Ro-vibrational van der Waals interaction between ultracold polar molecules
Kang Feng, Hanwei Yang, Hubert J. Jóźwiak et al. (+1 more)
We describe the ro-vibrational van der Waals interaction between ultracold polar molecules. This interaction is strong, leading to fast elastic collisions and orders of magnitude suppression of collisional loss. This enables evaporative cooling of
Fermi mixtures of molecules in different ro-vibrational states, without active shielding by applying external fields. The scheme is compatible with microwave shielding, where it enables controlled state dependent interactions, opening up new opportunities for
quantum simulation and
impurity physics. The interaction can also be used to stabilize fermionic molecules in optical
lattices, to control interactions in synthetic dimensions, for enhanced tweezer loading, and direct infrared shielding.
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All authors Kang Feng, Hanwei Yang, Hubert J. Jóźwiak, Tijs Karman
Optics
Time-Reversal Invariant Topological Photonic Alloy
Feng Ruili, Qu Tiantao, Wu Xianbin et al. (+4 more)
Conventional approaches generate
quantum spin Hall (QSH) and
quantum valley
Hall (QVH) effects by breaking spatial inversion
symmetry across the entire photonic
crystal. Consequently, modulating the bulk transmission gaps within these periodic frameworks typically requires global modification of structural parameters throughout the
lattice, severely limiting device reconfigurability and post-fabrication adaptability. In this work, we demonstrate that global inversion
symmetry breaking is not a prerequisite for inducing topological phases. Instead, local and minimal
symmetry breaking is sufficient. Using a photonic
alloy platform based on random substitutional disorder in a parallel-plate waveguide, we show that a disorder-driven local breaking of z-direction mirror
symmetry and a local breaking of in-plane
symmetry are capable of opening topological gaps to trigger QSH and QVH phase transitions, respectively, thereby supporting robust helical edge states and valley kink states. Rigorous topological characterization via the reflection-phase winding method reveals a striking size-dependent scaling behavior in both configurations, where the threshold doping concentration required to trigger the topological phase transition asymptotically vanishes in the thermodynamic limit. By enabling flexible, on-demand bulk gap engineering simply through random doping tuning rather than global structural reconfigurations, this photonic
alloy platform not only deepens understanding of disorder induced topological physics but also offers a scalable, highly efficient design strategy for integrated topological optical communications.
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All authors Feng Ruili, Qu Tiantao, Wu Xianbin, Shi Xiaoxuan, He Mujun, Zhang Lei, Chen Jun
Applied Physics
Synergistic Role of Electron and Photon Dose in Stepwise Laser-Induced Complete Deoxygenation of Graphene Oxide Revealed by In-situ TEM
Israt Ali and Kenneth R. Beyerlein
Laser-induced reduction of
graphene oxide (GO) represents a highly promising route to
graphene synthesis, offering spatially localized processing, elimination of hazardous chemical reagents, and compatibility with ambient conditions. Here, we introduce a stepwise
laser reduction strategy employing a 532 nm pulsed
laser, monitored in real-time by in situ dynamic transmission electron microscopy (DTEM). By systematically varying the pulse sequence and the cumulative
photon and electron dose, complete deoxygenation of GO is achieved while preserving film integrity. Core-loss EELS confirms full removal of oxygen functional groups and restoration of the sp$^2$ graphitic network, evidenced by a ${\pi}^*-{\sigma}^*$ energy separation of 7.0 eV, in close agreement with graphite (7.1 eV). Crucially, the cumulative electron dose is identified as an active parameter governing the reduction mechanism: electron beam exposure accounts for approximately 5 at. % of the initial oxygen removal and synergistically lowers the energy barrier for subsequent
laser-driven deoxygenation, while excessive electron exposure compromises film integrity through crack formation. The optimal configuration achieves complete deoxygenation at a cumulative
photon dose of 2.5 x 10$^3$ mJ/cm$^2$ with superior in-plane crystallographic order and minimal beam-induced thinning. This work establishes a versatile multi-parameter strategy for controlled scalable
graphene synthesis via combined electron beam and
laser irradiation.
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Medical Physics
Unveiling neuronal microstructure in the human brain in vivo with time-dependent radial diffusivity in MRI
Ante Zhu, Jerome J. Maller, H. Douglas Morris et al. (+14 more)
Diffusion time-dependence, defined as variations in diffusivity and/or diffusional kurtosis with
diffusion time, has emerged as a valuable non-invasive imaging marker for characterizing tissue microstructural features, such as
cell size, density, packing disorder, and membrane permeability. In white matter,
diffusion time-dependent changes between the short
diffusion time and long
diffusion time in radial diffusivity (RD), defined as the diffusivity perpendicular to fiber tracts, were demonstrated to correlate strongly with mean axon diameter in ex vivo spinal cord tissues, and to reveal demyelination in mouse corpus callosum. Despite their potential to non-invasively unveil neuronal microstructures to improve the assessment and targeted therapy of neurological diseases, these novel image contrasts obtained at short
diffusion times using oscillating gradient
spin echo (OGSE) have only recently become feasible for human in vivo studies with high-performance gradient MRI systems. In this preliminary study, we characterized time-dependent RD with OGSE encoding in the human
brain in vivo. The change in radial diffusivity between short
diffusion time and long
diffusion time (delta_RD) consistently exhibited high values in the corticospinal tract, indicating high sensitivity of delta_RD to large axon diameter in human
brains. Imaging at a high OGSE frequency of 100 Hz and a moderate b-value of 800 s/mm2 produced the highest delta_RD in the corticospinal tract. This study established a baseline for future investigations of neuronal microstructural alterations in neurological disorders and diseases.
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All authors Ante Zhu, Jerome J. Maller, H. Douglas Morris, Jeffrey P. Guenette, Flavio Dell' Acqua, Chu-Yu Lee, Jeffrey McGovern, Stephan E. Maier, Raymond Y. Huang, Andrew L. Alexander, Maureen N. Hood, Desmond Teck Beng Yeo, Steven CR Williams, Carl-Fredrik Westin, Vincent B. Ho, Vincent A. Magnotta, Hua Li
Biological Physics · Cross-listed from cond-mat.soft
Physical Mechanism of Vacuole Formation in Liquid Droplets
Pranay Jaiswal, Ivar S. Haugerud, William Verstraeten et al. (+3 more)
Vacuoles have been observed in
liquid droplets across variety of experimental systems, ranging from biomolecular condensates composed of
proteins and RNA, to synthetic coacervates formed by charged
polymers or synthetic nanostars. These vacuoles are long-lived domains depleted of droplet material, and their formation is puzzling because the associated increase in interfacial area is thermodynamically unfavorable. Using theory, we show that vacuoles form through a generic mechanism: a local spinodal instability within the droplet. We demonstrate this mechanism in several experimentally relevant scenarios, including temperature quenches and droplets coupled to chemical processes occurring either inside or outside the droplet. Using non-
equilibrium thermodynamics, we develop a theoretical framework that identifies the physicochemical conditions controlling whether vacuoles form and how big vacuoles can become. Our results suggest molecular designs and chemical pathways that promote vacuolation, enabling multi-compartment formation with engineered functions such as enhanced surface catalysis and compartment fission.
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All authors Pranay Jaiswal, Ivar S. Haugerud, William Verstraeten, Kerstin Göpfrich, Job Boekhoven, Christoph A. Weber
Medical Physics · Cross-listed from cs.CV
A systematic evaluation of machine learning classifiers for event-by-event background rejection in LAFOV PET scanners
Konrad Klimaszewski, Michał Obara, Mateusz Bala et al. (+5 more)
The introduction of LAFOV PET scanners brings significant sensitivity gains but also a substantial increase in the background rate from accidental coincidences, phantom-scattered and detector-scattered
photons. While machine learning methods have been applied to background reduction in PET imaging, they target specific background components in post-processing rather than event-by-event classification on the raw data. In this work, we formulate coincidence classification as a supervised multi-class problem and evaluate XGBoost, AdaBoost and Neural Network classifiers as pre-reconstruction filters, using Monte Carlo simulations of the Siemens Biograph
Vision Quadra scanner with NEMA IEC and anthropomorphic XCAT phantoms. We investigate two feature sets: a 4-feature representation based on the Attenuation Factor,
photon time difference, energy sum, and energy difference, and an extended 6-feature set that incorporates
topology-based variables. A systematic robustness study via cross-phantom inference reveals that the 4-feature models generalise significantly better across different phantom geometries, with XGBoost suffering an accuracy loss of only 0.04 compared to 0.13 for the 6-feature variant. Our best models achieve accuracies of up to 0.74 and 0.69 for the NEMA IEC and XCAT phantoms, respectively, outperforming traditional geometry-based cuts. However, we show that this compact feature set not only provides limited suppression of in-phantom scattered coincidences, but it also can lead to non-trivial spatial patterns. With scattered coincidences being the dominant background component in clinical conditions, this suggests that while the method serves as an effective and geometry-agnostic replacement for traditional cut-based selection, meaningful further gains in image quality will require either larger input representations or dedicated treatment of the phantom-scattered component.
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All authors Konrad Klimaszewski, Michał Obara, Mateusz Bala, Beatrix C. Hiesmayr, Lech Raczyński, Roman Y. Shopa, Wojciech Zdeb, Wojciech Krzemien
Atmospheric and Oceanic Physics
Small-scale polarization variations in near-inertial deep Mediterranean horizontal waterflow
Hans van Haren
Deep-sea observations are reported of horizontal waterflow differences with typical amplitudes of 0.02 m s-1 over 50-m small scales so that relative vorticity reaches values of the inertial frequency f. The timeseries observations are made using a complex mooring system deployed in the 2500-m deep Mediterranean Sea, where vertical density stratification is extremely weak, with buoyancy frequency O(f), and the slow waterflow with total speeds <0.07 m s-1 is dominated by inertial internal waves and sub-mesoscale eddies. Horizontal waterflow differences increase when polarization, i.e. direction of traversal of
elliptic oscillatory motion, switches sign. Common anticyclonic polarization of inertial motions is predominantly found under near-homogeneous conditions. It alternates with uncommon cyclonic polarization under stratified-water conditions, varyingly over 50-m distances. The alternation is in line with predictions from non-traditional inertio-
gravity wave theory, but only when relatively strong turbulent convection causes local reduced stratification, as observed.
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Optics · Cross-listed from cond-mat.mtrl-sci
Laser induced optical reconfiguration in Ge_Sb_Te Films with composition dependent response
M. Zhezhu, A. Vasilev, M. Sukiasyan et al. (+5 more)
Phase change Ge_Sb_Te (GST) materials exhibit pronounced optical contrast and tunability driven by structural transformations, enabling a diverse range of photonic and optoelectronic applications. GST materials undergo reversible amorphous crystalline phase transitions during which the refractive index and extinction coefficient increase significantly in the crystalline phase across a broad spectral range. However, a systematic correlation between local composition, crystalline microstructure, and broadband optical response within as deposited crystalline GST films has not been established, particularly for films spanning various compositions within a single growth process and in the absence of amorphous-crystalline transitions. Here, we report a systematic study of composition resolved optostructural property relationships in as-deposited crystalline GST films spanning Ge3Sb2Te6, Ge2Sb2Te5, and GeSb2Te4 within a single CVD process, avoiding intermediate phase transitions. This enables direct correlations between composition, microstructure, morphology, and broadband optical response across 400-1700 nm. Specifically, the compositional gradient results in a shift of the absorption minimum from 815.9 nm to 889.8 nm, accompanied by a 5.9 fold change in the intensity, reflecting the strong dependence of optical behavior on composition and microstructure. We further show that femtosecond
laser irradiation enables spatially selective tuning of the optical response. These findings establish crystalline GST films as a platform for broadband-tunable, spatially programmable photonic elements, controllable through both compositional design and localized
laser processing.
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All authors M. Zhezhu, A. Vasilev, M. Sukiasyan, A. Kutuzyan, N. Anosov, M. Yaprintsev, D. A. Ghazaryan, H. Gharagulyan
Computational Physics · Cross-listed from cond-mat.mes-hall
First-Principles Wannier Representation of Proximity Effects
Yaroslav Zhumagulov, Johan Félisaz, Stepan S. Tsirkin et al. (+2 more)
Proximity effects in layered
heterostructures are commonly represented by static parameters fitted to first-principles band structures, an approximation that usually discards the energy dependence of interlayer hybridization, momentum transfer, and spatial structure. We address this limitation by deriving a dynamical proximity operator directly from density functional theory by downfolding the
heterostructure Kohn-Sham
Hamiltonian onto a fixed low-energy target Wannier subspace. We demonstrate the method for three different
graphene heterostructures coupled to
magnetic and semiconducting substrates.
Graphene/hBN/Co(0001) exhibits proximity-induced exchange resonances driven by hybridization with Co states.
Graphene/PtSe$_2$ develops a sublattice-selective, intervalley-coherent, proximity-induced coupling. For
graphene/WSe$_2$, we identify the spatial modulation of both Rashba and valley-Zeeman proximity-induced
spin-orbit couplings. The method determines the full microscopic structure of the proximity coupling from first principles, providing input for transport and correlated-phase calculations.
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All authors Yaroslav Zhumagulov, Johan Félisaz, Stepan S. Tsirkin, Denis Kochan, Oleg V. Yazyev
Optics
Antichiral hinge states in a higher-order photonic nodal ring semimetal
Yuchen Peng, Deep Mondal, Yuting Yang et al. (+17 more)
Antichiral states propagate in the same direction on opposite boundaries, defying the conventional constraint that boundary modes must cancel net chirality. Previously found antichiral states have been limited to first-order topological semimetals. However, antichiral hinge states, the antichiral counterpart of recently discovered higher-order
chiral hinge states, remain elusive. Here, we report the observation of antichiral hinge states in a higher-order nodal-ring semimetal made of a three-dimensional gyromagnetic photonic
crystal. Near-field scanning measurements reveal a pair of hinge states at two parallel one-dimensional boundaries propagating unidirectionally along the same direction, with robust transport against metallic scatterers. Their spatial positions can be reconfigured by adding or removing photonic layers. The additionally observed antichiral and drumhead surface states manifest a hierarchy of first- and second-order topological boundary states within a single photonic system. Our work extends antichiral states to higher-order topological semimetals and has potential applications in robust and reconfigurable photonic routing.
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All authors Yuchen Peng, Deep Mondal, Yuting Yang, Wanting Wu, Bo Zhao, Shuaiyang Wei, Zhenzhi Liu, Wenrong Qi, Xiaokang Dai, Minqi Cheng, Weili Li, Xinyi Zhang, Fei-Fei Li, Rimi Banerjee, Minggui Wei, Jingyi Tian, Peiheng Zhou, Subhaskar Mandal, Baile Zhang, Gui-Geng Liu
Physics and Society
Open-ended innovation arm-race in zero-sum games
Matteo Marsili
This note discusses zero-sum games with open-ended innovation, whereby each player may introduce new strategies. The innovation process is modelled as a draw of new strategies form a distribution. It is argued that, when the cost of innovation is vanishingly small, this setting can lead to an everlasting innovation arm-race. In particular, the introduction of new technologies of the advanced player increases the marginal utility for technological innovation of the backward one, whereas innovation of the backward player disincentivizes the more advanced one to innovate.
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Computational Physics · Cross-listed from cs.LG
A Physics-Informed Neural Operator for Thermal Ranking of Low-Cost Wall Materials in Hot-Dry Climates
Muhammad Akbar Khan, Fahim Raees and Ubaida Fatima
Identifying cost-effective indigenous building materials that minimise heat penetration through walls is critical for indoor thermal comfort in low-income rural housing in hot-dry climates, where summer temperatures routinely exceed 45 C. We present a two-stage computational framework for thermal ranking of five low-cost indigenous wall materials: mud brick, clay-straw adobe, lime-stabilised bamboo panel, fired clay brick, and lime-mud composite. First, a validated Crank-Nicolson finite difference method (FDM) solves the one-dimensional transient heat equation with Robin boundary conditions under diurnal
solar and outdoor air-temperature forcing, generating 1500 periodic-day solutions across a nine-dimensional parameter space by Latin Hypercube sampling. Second, a Physics-Informed Neural Operator (PINO) with a
Fourier Neural Operator (FNO) backbone learns the parameter-to-solution operator mu -> T(x,t), enforcing both data fidelity and PDE consistency. The trained PINO attains a relative L2 field error of 5.14e-4 and a 0.201 K mean absolute error on the peak inner surface temperature, preserving the FDM material ranking exactly; PINO trained on 150 FDM samples matches a data-only FNO trained on twice as many, so the physics loss is most valuable when data are scarce. The periodic-day formulation also yields the ISO 13786 time lag and decrement factor, reproduced to within 0.99 h and 0.010. At nominal hot-dry summer conditions, clay-straw adobe achieves the best cost-performance index among widely available materials. A
climate sweep, confirmed by FDM spot checks, reveals a regime boundary: under sub-ambient outdoor conditions the ranking inverts to conductive fired clay brick, delineating heat-exclusion and heat-rejection regimes. The framework supports evidence-based material selection for post-flood reconstruction in hot-dry regions.
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Physics and Society · Cross-listed from cs.AI
Engine-Equal, Human-Unequal: A Reproducible Outcome Skew in Engine-Assessed Equal Chess Positions
Jesung Park
Among chess opening positions that a strong engine judges essentially equal (Stockfish 18 evaluation within 10 centipawns of zero, depth-stable) and that humans actually reach on Lichess (October 2025; 1,661 positions, 16.1M occurrences), human results are not balanced. Positions carry outcome skews, each the gap between its games' actual results and what the players' ratings predict, whose directions are stable properties of the naturally-reached position: some positions favour White, others Black. These skews reproduce across three re-partitions – disjoint player-account sets (primary), time, and disjoint rating bands – and on an out-of-sample month eight months later. On the primary split, each position's skew is measured once in each account group, and the replication slope asks how well one measurement predicts the other after removing rating and opening-family effects: one means undiminished carry-over; zero, no linear relation. We find 0.69 (family-clustered 95% CI [0.65, 0.74]), rising to 0.94 on the most-popular, best-measured positions. The slope's value depends on the position mix. Existence is the invariant claim: it survives every tighter evaluation band, search depth, calibration, and popularity cutoff we test, and replicates within blitz and rapid separately. The typical skew is small (median $|\delta| \approx 0.018$, about two percentage points of White score), yet it reproduces, position by position, across disjoint accounts. At these positions the disfavoured side also thinks longer. Even where the evaluation is most confident, it is not a sufficient statistic for human outcomes. The result is observational, and the causal question is left to a pre-registered randomised companion study.
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Chemical Physics
On transition path times for condensed-phase non-adiabatic electron transfer reactions under a two-parabola model
Ryo Nihei, Hiroki Uratani and Hirofumi Sato
Condensed-phase non-adiabatic electron transfer (ET) reactions play an important role in various areas of science. The characteristics of the microscopic transition processes involved in these reactions and their dynamic behavior remain poorly understood. In this study, we performed non-adiabatic simulations based on the Zhu-Nakamura theory, combining the two-parabola model with Kramers-like Langevin dynamics. We numerically analyzed the dependence of the macroscopic reaction time and the timescale of the microscopic transition process on the diabatic coupling between the diabatic states and on the friction parameter in Langevin dynamics. Although the microscopic transfer process is generally regarded as instantaneous in the non-adiabatic regime, we found that the timescale of the microscopic transition process can still be a non-negligible fraction of the macroscopic reaction time.
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Applied Physics · Cross-listed from cs.LG
Using Data-Derived Priors to Guide CNN Architecture Design for NIR Chemometrics
Dário Passos
Convolutional neural networks (CNN) for near-infrared (NIR) chemometrics are often designed using generic architectural rules, although spectral
datasets differ in sampling, smoothness, redundancy, and sample size. We tested whether these properties can provide empirical priors for CNN design. Across 25 NIR regression tasks, we computed descriptors of
dataset size, spectral length and spacing,
entropy, intrinsic rank, autocorrelation, and wavelet-scale structure. Two interpretable 1D-CNN scaffolds (a minimal single-convolution model and an extended shallow model with optional branching, dilation, etc) were optimized using five-fold cross-validated
Bayesian hyperparameter optimization (HPO). Relationships extracted from near-optimal trials were converted into warm-start heuristics and evaluated directly and through leave-one-
dataset-out (LODO) validation. The clearest relationships involved convolutional receptive fields. In the minimal CNN, the preferred kernel fraction decreased with spectral
entropy and intrinsic rank, increased with the wavelet energy-support fraction, and the learning rate tended to decrease with training-set size. Direct and LODO heuristics were competitive with HPO, with median test-RMSE ratios of 0.953 and 1.017, respectively. The extended CNN showed similar but less transferable structure across branch usage, dilation, dropout, filter counts, and receptive-field choices. Ten
stochastic refits showed seed sensitivity comparable to that of HPO-selected configurations. In a separate experiment, joint preprocessing and CNN HPO outperformed standardized-spectra HPO in 19 of 25 tasks, although gains were
dataset-dependent. These results show that spectral descriptors can provide practical CNN design priors, guiding shallow NIR models toward plausible hyperparameter regions before target-specific tuning
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Optics · Cross-listed from quant-ph
The Natural Formulation of Cubic-Phase Dynamics in the Linear Potential
Maximilian L. D. D. Pellner and Georgi Gary Rozenman
A
quantum wave packet in a linear potential, i.e. a constant force such as
gravity, accumulates a cubic-in-time phase, universal across Schrödinger-type platforms. The natural formulation of the cubic phase dynamics follows from their canonical realization, the Airy eigenstates. The eigenforce, the potential gradient for which the Airy profile is stationary and hence the intrinsic force behind its known self-acceleration absent any applied force, derives from the
eigenvalue problem and characterizes the state uniquely up to a rigid translation. Alongside the applied force, it underlies the analytically closed form of these dynamics, comprising three known contributions, intrinsic, force-induced, and a cross term. The force-induced one alone is shape-independent, whereas the Airy eigenstate renders the other two non-dispersing. The cubic coefficient factorizes into two Newtonian force balances, vanishing at the stationary eigenstate and at a non-trivial zero where the phase cancels while the packet keeps accelerating. This exposes the eigenforce as an effective antagonist to the applied force, not only in the caustic's self-acceleration but here also within the phase, while leaving the centroid untouched by Ehrenfest's
theorem. Spatially uniform within each packet, it escapes direct measurement, accessible only as the relative phase of two colliding packets, each in its own potential. The relative cubic coefficient is
symmetry-forbidden for identical packets and activated by preparation asymmetry. Simulated interference of two truncated Airy packets demonstrates the extraction. Spanning ultracold atoms, paraxial optics, and surface-
gravity water waves, it provides a platform-independent probe of the cubic phase and, through its force dependence, of the constant force itself.
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Classical Physics · Cross-listed from math.AP
Well-posed homogenized strain-gradient models for linear elastodynamics and elastostatics in arbitrary periodic media
Rémi Cornaggia, Marc Bonnet, Giuseppe Rosi et al. (+2 more)
This work develops well-posed homogenized strain-gradient models for linear elastostatics and elastodynamics in periodic media, with a primary focus on elastic wave propagation. Using the classical two-scale asymptotic expansion method, we carry out second-order periodic homogenization for media in $\mathbb{R}^d$ ($d = 2, 3$), with no restriction on the periodicity
cell geometry or material distribution. Reciprocity identities applied to suitably chosen pairs of
cell solutions provide alternative expressions for the effective stiffness and inertia tensors arising at the leading, first and second orders, substantially reducing the number of
cell problems that must actually be solved. Since direct two-scale homogenization beyond leading order generically yields ill-posed effective operators, a Boussinesq-trick procedure is introduced, involving a tunable scalar weight, to recast the resulting fourth-order partial differential equation as a valid strain-gradient elasticity (SGE) model possessing the requisite
symmetry, sign-definiteness and coercivity properties. These properties are then used, via the Hille-Yosida
theorem, to establish the well-posedness of the corresponding transient initial-value and forced-response problems. Several practically relevant special cases are examined, including centrosymmetric
cells, homogeneous mass density and homogeneous elasticity, each yielding simplified model structures. Numerical illustrations on three two-dimensional periodicity
cells (square, hexagonal and a non-centrosymmetric
chiral lattice) compare the resulting dispersion relations against reference Floquet-Bloch computations and assess transient wave propagation, demonstrating the model's capacity to capture anisotropic and dispersive effects beyond classical elasticity while preserving mathematical well-posedness.
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All authors Rémi Cornaggia, Marc Bonnet, Giuseppe Rosi, Saad El Ouafa, Nicolas Auffray