Computational Physics · Cross-listed from math.NA
Tensor-Network Finite Elements for Analytic Operator Equations
Abhijatmedhi Chotrattanapituk, Michael J. Landry, Chu-Liang Fu et al. (+1 more)
Operator equations (OEs) underpin quantitative modeling across science and engineering. Finite-element (FE) methods discretize continuous OEs into finite-dimensional algebraic systems, whereas tensor networks (TNs) provide flexible variational representations of correlated discrete systems. Here, we develop a framework that connects FE with TN for analytic OEs. The power of this method comes from its ability to convert highly non-linear partial differential equations into linear
matrix equations. In particular, we show that FE discretization induces a hierarchy of multilinear interaction tensors, through which differential, integral, nonlinear,
memory, and delay equations can be expressed within a common algebraic structure. The resulting systems are reformulated as weighted-residual optimization problems over TN degrees of freedom.
Matrix-product-state calculations for one-dimensional linear and nonlinear
diffusion reproduce conventional solutions with controlled error while preserving continuity and Neumann boundary conditions. The framework provides a common variational
language for analytic OEs and establishes a direct connection between FE numerical formalism and TN variational
algorithms, offering a general foundation for TN-based and
quantum-inspired approaches to solving OEs.
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All authors Abhijatmedhi Chotrattanapituk, Michael J. Landry, Chu-Liang Fu, Mingda Li
Data Analysis and Statistics
Profile-Likelihood and Baseline-Sensitivity Diagnostics for Digitized Radiation-Sensor Decay Datasets
Victor V. Golovko
Accurate interpretation of radiation-sensor decay data is important for environmental monitoring, site remediation, radiation metrology, detector quality assurance, and
nuclear data evaluation. When the original gamma-spectrometry records are unavailable, a published decay plot may be the only source that can be reanalyzed independently. This study presents a reproducible reduced-data workflow for testing half-life estimates from a digitized 198-Au decay
dataset. A weighted exponential fit to the digitized data points reproduces the published room-temperature half-life, indicating that the main decay scale is retained in the figure-level
dataset. The analysis then tests how the fitted result changes under plausible figure-level effects, including baseline-like offsets, time-axis reconstruction, finite-window leverage, and ratio-based robustness checks using pairwise summaries and Steiner's most frequent value statistics. The no-offset fit is locally well constrained, but small constant offsets can shift the fitted half-life because the normalization, decay constant, and residual baseline are partly degenerate over the limited time window. Toy Monte Carlo diagnostics show that some
estimator shifts are expected for finite-window exponential data. This study does not revise recommended
nuclear data or replace the original experiment. Instead, it shows how published radiation-sensor decay data can be tested for reproducibility, identifiability, and sensitivity to analysis choices when only reduced or figure-level information is available.
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Geophysics
Probabilistic Seismic Hazard Assessment of Palghar District, Maharashtra, India by considering spatially non-uniform seismicity
Suman Sinha, S. Selvan, Sachin Khupat et al. (+1 more)
The Palghar district of Maharashtra has recently received
attention because of frequent occurrences of earthquakes in its vicinity in the last few years since November, 2018. The district area falls under seismic zone III, as per the seismic zonation map of India. As the recent earthquake activities have been preceded by many major seismic events in the region, it necessitates to re-evaluate the level of seismic hazard of the area in a reliable and realistic way. With this aim in mind, the probabilistic seismic hazard map of Palghar district with regard to 5% damped Peak Ground Acceleration (PGA) and Pseudo Spectral Acceleration (PSA) at 0.2 s and 1.0 s for 10% and 2% probability of exceedance (PoE) in 50 years at engineering bedrock level is presented. The estimation of hazard are performed in a finer grid resolution of 0.02 deg X 0.02 deg and takes into consideration the nonuniform distribution of earthquake probability within a seismic source zone (SSZ) and data-driven selection of appropriate Ground Motion Prediction Equations (GMPEs). The spatial variation of the hazard maps, reflected in he final results, demonstrates notable improvements over the earlier studies.
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All authors Suman Sinha, S. Selvan, Sachin Khupat, Rizwan Ali
Applied Physics
Non-intrusive MEMS microphone sensing of acoustic field state in resonant acoustic levitators
Jan H. Dörsam, Maximilian L. Amberg, Sven Suppelt et al. (+6 more)
Reliable operation of resonant acoustic levitators requires knowledge of the acoustic field state because the optimum transducer-reflector distance and resonant operating condition shift with wavelength, temperature, object insertion, and mechanical
alignment. Existing adjustment methods are limited, especially for compact closed-loop operation and architectures without a passive reflector. Here, we investigate transducer-mounted microelectromechanical system (MEMS) microphones as off-axis external sensors that acquire relative acoustic signals without placing sensors inside the levitation cavity. Using a linear microphone configuration, we performed transducer-reflector distance sweeps over resonance modes n = 5-8 and compared microphone amplitude with acoustic radiation force measured by a precision balance and with peak-to-peak transducer current. The channel-mean microphone-voltage maxima occurred within two sampled distance increments, or at most 30 micrometers, of the force maxima. At the microphone-derived peak positions, at least 98.3% of the corresponding maximum force was retained. Microphone amplitude localized the force maximum more sharply than peak-to-peak transducer current. In one frequency-shift experiment, microphone phase provided a proof of principle for correction-direction estimation, while envelope modulation captured channel-resolved field changes during object oscillation. Ring measurements showed channel-dependent responses as transducer-reflector tilt was varied, but did not provide a calibrated or unique tilt estimate. These results show the potential of external MEMS microphones as relative acoustic observables for resonance-related field-state assessment and provide a basis for compact transducer-side feedback. The principle may also be transferable to transducer-transducer and array-based architectures.
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All authors Jan H. Dörsam, Maximilian L. Amberg, Sven Suppelt, Sören Soennecken, Chuanchao Xu, Alexander A. Altmann, Tomislav Maric, Dieter Bothe, Mario Kupnik
Plasma Physics
A Shortcut to Statistically Steady-State Turbulence with Flow Matching
Gianluca Galletti, Gerald Gutenbrunner, William Hornsby et al. (+5 more)
Many nonlinear physical systems exhibit an initial transient phase in which perturbations grow before nonlinear interactions lead to a statistically steady state. While this saturated regime is of primary interest, direct numerical simulations must resolve the full transient dynamics before reaching it, incurring significant computational cost. In Computational Fluid Dynamics, reduced-order approaches such as Large Eddy Simulation mitigate computational cost by modeling small-scale dynamics, enabling tractable approximations of turbulent flows. In contrast, for systems such as gyrokinetics, comparably effective closures for the full dynamics are not generally available, and high-fidelity simulations remain necessary. Existing surrogate modeling approaches for these systems are autoregressive, hence they suffer from accumulating error. We instead propose to bypass explicit time
evolution by directly modeling the distribution of saturated states under an ergodicity assumption, stating that ensemble averages over samples are equivalent to time averages of a single long simulation. We introduce GyroFlow, a latent generative model that directly estimates steady-state statistics of gyrokinetic
turbulence in 5D phase space, without resolving the transient phase. GyroFlow generates saturated snapshots from noise, conditioned on dimensionless operating parameters and outperforms autoregressive, reduced-order, and other generative approaches, while providing substantial speedup. To evaluate generation quality we propose FGyD, a distributional metric computed in the latent space of a pretrained gyrokinetic model, and show that it correlates with downstream flux accuracy and solver convergence. Finally, GyroFlow can be used to warm-start the numerical code used to produce the data.
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All authors Gianluca Galletti, Gerald Gutenbrunner, William Hornsby, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter, Fabian Paischer
Atomic Physics
High-fidelity entanglement of polar molecules by dynamic geometric control
Scarlett S. Yu, Avikar Periwal, Jiaqi You et al. (+6 more)
In
quantum information systems made of optical tweezer arrays of ultracold molecules, thermal motion of molecules degrades the coherence of their interactions, which limits
entanglement fidelity and the concomitant scientific applicability of these systems. We show that by controlling the geometry of the dipolar interaction, even when a molecule occupies many motional states in the tweezer, coherence can be preserved. We characterize several geometries that suppress sensitivity to thermal fluctuations. We further use programmable, coherence-preserving motion of the molecules during
entanglement to refocus dephasing from relative positional jitter of the tweezers, which is relevant even on the 10 nm scale. These methods yield substantially improved dipolar coherence and enable generation of two-molecule
entanglement with a Bell state fidelity of $\mathcal{F}= 0.976^{+0.008}_{-0.011}$ in directly
laser-cooled molecules.
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All authors Scarlett S. Yu, Avikar Periwal, Jiaqi You, Zirui Liu, Qinshu Lyu, Youngju Cho, Loïc Anderegg, Eunmi Chae, John M. Doyle
Instrumentation and Detectors · Cross-listed from astro-ph.IM
picoMUX: microcontroller based time-domain multiplexing readout for kilopixel TES arrays
Simon Tartakovsky, Alexandre E. Adler, Jason E. Austermann et al. (+23 more)
Advances in cryogenic SQUID-based time-domain multiplexing (TDM) have outpaced their warm readout electronics. Next generation CMB
telescopes are baselining kilopixel TES arrays with few viable electronic options. We present picoMUX, a new TDM readout electronics architecture that replaces the FPGA typically used in such systems with a complement of modern microcontrollers. Designed around the current generation NIST multiplexer, it fully exploits its differential nature and two-level switching. The system achieves the desired timing metrics (sub {\mu}s row dwell time) while reducing cost, complexity, and power consumption over a comparable FPGA solution. Preliminary noise measurements are consistent with expectations and show no evidence that the novel architecture introduces excess noise. picoMUX demonstrates how recent advances in microcontrollers enable simpler, low-power, low-cost TDM readouts for kilopixel TES arrays.
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All authors Simon Tartakovsky, Alexandre E. Adler, Jason E. Austermann, Steven J. Benton, Shannon M. Duff, Malcolm Durkin, Jeffrey P. Filippini, Aurelien A. Fraisse, Thomas J.L.J. Gascard, Sho M. Gibbs, Suren Gourapura, Jon E. Gudmundsson, Johannes Hubmayr, William C. Jones, Ashesh Khatua, Jared L. May, Darby McCauley, Johanna M. Nagy, Ivan L. Padilla, Ricardo R. Rodriguez, John E. Ruhl, M. Shaaf Sarwar, Christopher Rooney, Joseph van der List, Michael R. Vissers, Philippe Voyer
Medical Physics
Reconstruction-Independent Resolution Limits in Preclinical Cone-Beam Micro-CT: A Closed-Form Analysis
Falk L. Wiegmann and Nancy L. Ford
Spatial resolution in preclinical cone-beam micro-CT is bounded by two reconstruction-independent limits, a
photon-noise limit from the projection-domain signal-known-exactly, background-known-exactly (SKE/BKE) ideal observer with the Rose criterion, and an angular-sampling limit from the Crowther criterion. The
photon-noise bound is a property of the input data and applies to any reconstruction
algorithm. The angular-sampling bound applies to classical analytic and iterative reconstructions (FDK, FBP, SIRT) that do not inject signal priors. We derive both limits in closed form for a circular feature in a uniform background, including an off-axis fan-beam extension, and combine them into a spatially varying effective resolution map. The combined limit yields a closed-form scan-design optimum. The maximum worst-case spatial frequency scales as the cube root of the total
photon budget per detector pixel (per-view flux times number of views), and an analytic rule sets how to split that budget between flux and views. We illustrate the framework on a representative preclinical micro-CT scanner, with parametric sweeps over flux and projection count that show how each acquisition parameter reshapes the resolution map. An accompanying open-source web calculator implements these bounds for arbitrary scanner geometries.
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Atomic Physics
A cryogenic neutral-atom platform with full optical access and 2-hour trap lifetime
Akhil Kumar, Lorenzo Festa, Avishay Grinberg et al. (+10 more)
Neutral-atom
quantum processors are rapidly scaling toward system sizes of more than ten thousand
qubits, allowing for the realization of a new class of
quantum computing
algorithms and
quantum simulation experiments. However, current neutral-atom platforms generally have to find a compromise between the optical accessibility and the storage time of atoms in optical potentials, limiting the available
qubit numbers. Here we report on the operation of a novel, cryogenically enhanced, neutral-atom apparatus that overcomes these apparently conflicting requirements. We demonstrate
vacuum-limited trapping lifetimes of up to two hours of single $^{88}\mathrm{Sr}$ atoms in an optical tweezer array while preserving full optical access and without the need for complex cryogenic enclosures. Our measurements show that exceptionally long single-atom lifetimes can be achieved with a relatively simple cryostat design. Our architecture can be straightforwardly ported to other atomic species and shows a viable path for scaling up to sorted arrays of tens of thousands of atoms.
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All authors Akhil Kumar, Lorenzo Festa, Avishay Grinberg, Eran Reches, Dimitrios Tsevas, Kevin P. Mours, Zhao Zhang, Robin Eberhard, Sebastian Blatt, Andrea Alberti, Johannes Zeiher, Immanuel Bloch, Max Melchner
Plasma Physics
Single-Shot High-Energy Muon and Particle Radiography with a Multi-GeV Laser-Wakefield-Accelerator-Driven Source
Kaixin Zhu, G. Jackson Williams, Roberto Versaci et al. (+29 more)
We report the first demonstration of single-shot particle radiography using a 1-10 GeV
laser-wakefield-generated beam of
muons, pions, and
neutrons. The test objects were imaged ~15 m from the beam source, through dense lead shielding followed by the walls of a building and a truck. The
muon content of the beam was directly confirmed using large volume scintillator-based detectors, which recorded particle decay events with timing delays consistent with the
muon lifetime. Simulations confirm that the high energy component of the beam transmitted through the test object is nearly entirely composed of
muons, directly showing their highly penetrative nature, with a single-shot fluence equivalent to >8 hours of integration of
cosmic ray
muons near the horizon. Our work establishes single-shot high-energy particle radiography with a
laser-wakefield-accelerator-driven source.
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All authors Kaixin Zhu, G. Jackson Williams, Roberto Versaci, Ela Rockafellow, Anna Cimmino, Jaron E. Shrock, Reed Hollinger, Gabriele M. Grittani, Jiří Šišma, Ari Sloss, Nikola Durand, Nischal Tripathi, Jay Jablonski, James King, Gerardo Palma, Zach Rautio, Bryan Sullivan, Shoujun Wang, Frederica Sorkin, Sina Zahedpour, Ping Zhang, Bo Miao, Andrew Yandow, Mayank Gupta, Scott W. Hancock, Scott C. Wilks, Vincent Tang, David Warner, Jorge J. Rocca, John Harton, Howard M. Milchberg, Brendan A. Reagan
Chemical Physics · Cross-listed from cs.HC
Sensing the properties of virtual objects without physical feedback
Rhoslyn Roebuck Williams, Harry J. Stroud, Luis E. Toledo et al. (+2 more)
People who have interacted with simulated worlds and simulated objects in extended reality (XR) often have a sense that they can 'feel' the objects being simulated despite them not being physical. Our sense of touch is essential for how we 'feel' the physical world, however, there is an open question as to what it means to 'feel' virtual objects when interacting with them in immersive digital environments. In prior research, we have reported that participants often describe a subjective experience of 'feeling' the properties of simulated molecular objects while using interactive molecular dynamics in extended reality (iMD-XR), a field-based interaction paradigm for manipulating real-time simulations of molecular objects without haptic feedback. To better understand these subjective reports of 'feeling', we used a psychophysics approach to quantify the threshold at which participants perceive differences in the
rigidity of simulated molecular objects (C$_{60}$ molecules) in iMD-XR. To evaluate this, we carried out experiments to compare the just-noticeable differences (JNDs) in two conditions: (1) via direct interaction with a real-time C$_{60}$ simulation, and (2) via observation-only$\unicode{x2013}$i.e. watching another person interacting with the simulations. Our findings show that direct interaction enabled participants to perceive more subtle
rigidity differences of 11.5%, compared to 18.5% for observation-only. Furthermore, participants who undertook interaction first were better able to distinguish
rigidity differences in the subsequent observation-only condition, suggesting that interaction trained participants to better perceive differences in molecular properties. These findings demonstrate a novel and flexible approach for sensing the properties of virtual objects in XR, and offer new insights into iMD-XR's potential in molecular research and education.
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All authors Rhoslyn Roebuck Williams, Harry J. Stroud, Luis E. Toledo, Mark D. Wonnacott, David R. Glowacki
Atmospheric and Oceanic Physics
Robustness of Deep Learning Models for PV Power Forecasting under NWP Forecast Errors: A Spatiotemporal and Physically Interpretable Analysis
Dandan Chen, Yan Zhao and Xuepeng Chen
Engineering use of AI
forecasting models requires not only high nominal accuracy but also predictable behavior under uncertain inputs. In photovoltaic (PV)
forecasting, this requirement is especially challenging because numerical weather prediction (NWP) errors are temporally correlated, state dependent, and physically coupled across variables. Existing evaluations, however, often rely on perfect forecast assumptions or simplistic perturbations that do not reflect these characteristics. This study presents a physically constrained robustness evaluation framework based on simulation, using virtual PV power as a controlled response variable to isolate the propagation of input uncertainty from confounders at the plant level. Six representative machine learning and deep sequence models, including PatchTST, GRU, N-HITS, and LightGBM, are evaluated under dynamic NWP perturbations with heteroscedasticity modulated by clear-sky conditions and Erbs reconstruction that preserves radiation consistency. The results show that sequence models provide stronger noise filtering and temporal resilience than a strong tabular baseline under medium to high disturbance regimes. SHapley Additive exPlanations (SHAP) and Integrated Gradients (IG) further support a feature reallocation tendency at the case level, in which predictive reliance shifts from corrupted future forecasts toward more stable historical observations and deterministic physical priors. A Pareto analysis of accuracy under clean conditions, robustness, and computational latency then translates these findings into engineering implications for robustness assessment and model selection under forecast uncertainty.
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Fluid Dynamics
A Unified Gradient Theory for Frame-Indifferent Rates of Tensorial Internal Variables
Luis Espath
We develop a thermodynamically consistent framework for weakly nonlocal continua with tensor-valued internal variables. Let $\boldsymbol{L}=\operatorname{grad}\boldsymbol{v}$, with stretching tensor $\boldsymbol{D}=\operatorname{sym}\boldsymbol{L}$ and
spin tensor $\boldsymbol{W}=\operatorname{skw}\boldsymbol{L}$. We introduce the generators $\boldsymbol{\Gamma}_{\alpha}=\boldsymbol{W}+\alpha\boldsymbol{D}$, $\alpha\in\{0,1\}$, which unify corotational and upper-convected transport. The resulting kinematic structure induces canonical frame-indifferent evolutions of both the internal variable and its spatial gradient, thereby providing a closure for gradient-dependent theories. Starting from the balances of linear momentum and microforces, together with an internal power expenditure depending on the internal variable and its gradient, we derive a local free-energy imbalance for incompressible isothermal processes. Under isotropy and inherited
symmetry assumptions, this imbalance admits a canonical decomposition into contributions associated with $\boldsymbol{D}$, $\operatorname{grad}\boldsymbol{L}$, the generator-induced rate $\mathfrak{D}_{\alpha}\boldsymbol{J}$, and its gradient $\mathfrak{D}^{\nabla}_{\alpha}(\operatorname{grad}\boldsymbol{J})$. This decomposition yields explicit constitutive restrictions ensuring thermodynamic consistency and identifies the induced higher-order stress contributions arising from gradient dependence. Finally, we construct a coupled gradient theory combining viscoelasticity and constrained orientational order, in which distinct internal variables evolve under different transport mechanisms. The framework extends classical theories with tensorial internal variables, including Oldroyd-B and Landau-de Gennes-type models.
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Fluid Dynamics
Energetics and Stochastics of Extreme Waves Breaking over a Symmetrical Breakwater
Saulo Mendes, Yuchen He, Jérôme Kasparian et al. (+1 more)
Rogue wave formation and enhancement over coastal areas have been documented over the last decade. This seems to contradict the observed low rogue wave (RW) probability near the surf zone. Without considering wave breaking, RW amplification is expected in this regime. To address this gap, we consider fully nonlinear effects of wave breaking through the proxy of height-to-depth ratio, spatial changes on the wavenumber through the WKB approximation, and slope-corrected refraction mild-slope equations on the energetics of irregular wave fields travelling over a breakwater. By increasing the significant wave height towards the breaking limit, the kinetic energy grows faster than the variance of the surface elevation due to nonlinearity. Thus, the kurtosis decays, albeit not to the point of getting sub-Gaussian statistics. We thereby resolve the apparent paradox of the occurrence probability of RW increase at the beginning of shoaling but subsequently decrease when wave breaking becomes dominant. Motivated by these theoretical developments, we experimentally probe inhomogeneous wave fields nearing the wave-breaking regime. We conduct unidirectional irregular wave experiments in a 30 m long wave flume, generating broad-banded waves over a symmetric submerged breakwater featuring a bottom slope of 1/5, allowing detailed characterization of spectral
evolution and the persistence of elevated excess kurtosis even near the breaking limit for this steep slope. We thereby confirm that the excess kurtosis can still be large if the bottom slope is steep, and its maximum value is at least 4 times larger than in other ocean processes, occurring atop the breakwater and about half of its deep water peak wavelength distance after the shoal. As these conditions are typical near shorelines, this understanding is key to coastal areas.
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All authors Saulo Mendes, Yuchen He, Jérôme Kasparian, Amin Chabchoub
Chemical Physics
Measurement and assignment of $\it{J}$ $\geq$ 10 rotational energy levels in the 9510 to 9810 cm$^{-1}$ and 6590 to 6900 cm$^{-1}$ ranges of methane using optical frequency comb double-resonance spectroscopy
Yuan Cao, Adrian Hjältén, Vinicius Silva de Oliveira et al. (+4 more)
Accurate models of high temperature methane spectra are needed in astrophysics. Previous measurements of methane hot-band transitions in the $\it{P}$6 $\leftarrow$ $\it{P}$2 polyad range have been limited to final rotational numbers of $\it{J}$ $\le$ 9, with theoretical predictions at higher $\it{J}$s remaining unvalidated. Here, we use optical-optical double resonance spectroscopy (OODR) with a 3.3 ${\mu}$m narrow linewidth pump to excite the ${\nu}$${_3}$ P(12, A${_1}$$^{(2)}$) methane transition ($\it{P}$2 $\leftarrow$ $\it{P}$0) and a cavity-enhanced frequency comb centered around 1.68 ${\mu}$m to probe the sub-Doppler ladder-type ($\it{P}$6 $\leftarrow$ $\it{P}$2) and V-type ($\it{P}$4 $\leftarrow$ $\it{P}$0) transitions, as well as Doppler-broadened collision-induced four-level transitions ($\it{P}$6 $\leftarrow$ $\it{P}$2). 49 ladder-type transitions with final rotational states $\it{J}$ = 10-12 in the range of 9510 to 9810 cm$^{-1}$ (i.e., the $\it{P}$6 polyad) were assigned to effective
Hamiltonian predictions and the ExoMol database, of which 6 reached vibrational states that had not been observed experimentally before. 19 sub-Doppler V-type transitions with final states $\it{J}$ = 11-13 in the range of 6590 to 6900 cm$^{-1}$ (i.e., the $\it{P}$4 polyad) were observed and assigned to the
Hamiltonian and ExoMol, while only 2 of these V-type transitions could be unambiguously assigned to WKLMC and HITRAN line lists. 170 Doppler-broadened four-level double-resonance (4LDR) lines were observed, 7 of which were newly observed compared with our previous work when pumping transitions starting from the $\it{J}$ = 7 level in the ground state [Lehmann et al., J. Chem. Phys. 163, 144304 (2025)]. We could not assign these lines as they did not form combination differences with other observed 4LDR transitions.
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All authors Yuan Cao, Adrian Hjältén, Vinicius Silva de Oliveira, Isak Silander, Michael Rey, Kevin K. Lehmann, Aleksandra Foltynowicz
Fluid Dynamics
Mixing and sharpening at the interface of a two-layer fluid forced by random jets
Noé Clavier, Hugo Pradel, Romain Volk et al. (+2 more)
Understanding mixing at density interfaces is essential for predicting transport in stratified environmental flows. Laboratory studies have mostly relied on steady, spatially uniform forcing, whereas
turbulence in nature is intermittent and heterogeneous. Here, we present experiments on a two-layer salt-stratified fluid forced by random turbulent bursts generated with a randomly actuated synthetic jet array (RASJA). Density fields are recorded with the light attenuation technique, allowing us to resolve the interface
evolution. We measure that the upward velocity of the interface decreases with the density jump, in agreement with the power-law found in previous oscillating-grid studies. At large density differences, the interface sharpens during mixing, contrary to the smaller density jump case. Background potential energy analysis demonstrates irreversible mixing in both cases, with comparable energy changes. These results extend classical laboratory observations to a more isotropic forcing, offering new insights into the dynamics of mixing in geophysical settings.
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All authors Noé Clavier, Hugo Pradel, Romain Volk, Mickaël Bourgoin, Yvan Dossmann
Physics and Society
Balancing innovation and assimilation in research communities
Bill Nunn, Maria Horner, Marcel Ortgiese et al. (+1 more)
It has been statistically observed that the speed at which a corpus of knowledge advances does not scale linearly with quantities like the number of active researchers or number of research papers published in a given field. Furthermore, as a body of knowledge grows, individual researchers must somehow strike the right balance between generating new knowledge through innovation and assimilating knowledge generated by others. Here, we propose and analyse a pair of interacting particle system models representing some stylised features of the advancement of knowledge in a research community, captured as a
stochastic travelling wave in knowledge space. Both particle systems exhibit a diminishing return in the knowledge advancement speed as research communities grow larger, and suggest that researchers should spend more time on assimilation of knowledge than innovation as their research community grows.
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All authors Bill Nunn, Maria Horner, Marcel Ortgiese, Tim Rogers
Plasma Physics
A new model for runaway electron transport based on chaotic Hamiltonian systems
Dániel Jánosi, Anikó Horváth, Hannes Bergström et al. (+5 more)
The transport of runaway electrons (RE) in ergodic
magnetic geometries is an area of active study. Computing the transport from the direct simulation of particle trajectories is computationally expensive. Instead,
diffusion models, such as the one by Rechester and Rosenbluth, are often employed to incorporate transport effects into reduced simulations. However, the comparison of
diffusion-based to direct simulations reveals that the transport is typically not purely diffusive. In this paper, we introduce a simple transport model, based on chaos theory, which goes beyond the Rechester-Rosenbluth approximation. Besides chaotic
diffusion, our model takes into account the effect of so-called sticky regions, a trapping layer around
magnetic islands, where particle escape slows down to a power-law decay rather than an exponential decay. We demonstrate the applicability of the model both in the Ullmann-Caldas map with parameters corresponding to the TBR-1 tokamak, and in a JOREK simulation of a JET disruption scenario, with remarkably good fits achieved in both cases.
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All authors Dániel Jánosi, Anikó Horváth, Hannes Bergström, Matthias Hölzl, Gergely Papp, Gábor Veres, Gergo I. Pokol, György Károlyi
Atmospheric and Oceanic Physics
Superstatistical Analysis of PDFs and autocorrelation functions for air pollution concentrations in the UK
Nisal Amarakoon, Hankun He and Christian Beck
Conventional statistical models often struggle to fully capture the complex spatio-temporal dynamics, intermittent fluctuations, and heavy-tailed distributions characteristic of real-world air pollution data. Furthermore, existing literature frequently focuses on extreme events, overlooking the persistence of low-pollution states and temporal
memory effects. To address these gaps, we apply superstatistical frameworks from non-
equilibrium statistical physics to analyse a comprehensive five-year
dataset (2020-2025) of hourly air pollutant concentrations across the United Kingdom. Excellent fits of experimentally measured distributions are obtained from our theoretical models. We observe large heterogeneities of the best fitting parameters depending on the locations where the measurements are performed. These parameters form characteristic patterns in the 3-dimensional parameter space and depend on the type of pollutant considered, as well as on the environmental conditions (high traffic, industrial, or rural surroundings). We also investigate autocorrelation functions and provide evidence for differences in day-time and night-time decays of the autocorrelation function. Our investigation mainly focuses onto the dynamics of NO, NO2, PM2.5, PM10, but we also report on some anomalous distributions observed for O3.
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Optics
Phase Angle and Effective Second-Harmonic Generation Coefficient
Yisheng Song
In this paper, the calculation formulae of phase angle are given for two classes of largest effective SHG coefficients in uniaxial
crystals by means of the optimization theory. With the help of such calculation formulae, we present the best phase angles and azimuth angles of all uniaxial
crystals class, as well as their effective SHG coefficients. Furthermore, these calculation is only dependent upon some principal subtensor of second order susceptibility tensor.
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Chemical Physics
Strong-Field Coulomb Explosion of Ethane, Propane, and Butane in Circularly Polarized Laser Fields
Yuxuan Hu, Roy Lau, Cody Covington et al. (+1 more)
We investigate the Coulomb explosion of ethane (C$_2$H$_6$), propane (C$_3$H$_8$), and n-butane (C$_4$H$_{10}$) driven by intense circularly polarized
laser pulses using real-time time-dependent density functional theory (RT-TDDFT). The ionization dynamics are benchmarked against those obtained with linearly polarized fields oriented along the $x$, $y$, and $z$ axes at the same peak intensity. Under the
laser conditions considered here, circular polarization produces greater ionization than any of the linearly polarized configurations for all three molecules, indicating that the rotating electric field enhances the initial electron-removal stage that triggers Coulomb explosion. Using circularly polarized excitation, we systematically characterize fragmentation thresholds, product distributions, channel branching ratios, and bond-breaking dynamics across the alkane series. Atomic hydrogen is the most abundant fragment in all three systems, demonstrating that hydrogen loss is the dominant fragmentation pathway. Ethane primarily retains its two-carbon backbone through partial dehydrogenation, propane exhibits the broadest range of fragmentation channels and the strongest competition between C–H and C–C bond cleavage within the present ensemble, and butane favors backbone cleavage into relatively stable two-carbon fragments, most notably through the $2\mathrm{C_2H_4} + 2\mathrm{H}$ channel. Analysis of the earliest bond-breaking events further shows that C–H dissociation is the preferred initial fragmentation step throughout the series, although the degree of competition with C–C cleavage depends on molecular size.
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All authors Yuxuan Hu, Roy Lau, Cody Covington, Kálmán Varga
Optics · Cross-listed from quant-ph
End-to-End Quantum Key Distribution Across Hybrid Fiber and Free-Space Links with All-Optical Encoding Conversion
Khen Cohen, Tomer Nahum, Michael Tzukran et al. (+6 more)
Quantum key distribution (QKD) promises information-theoretically secure communication, but future networks must bridge fiber and free-space links that naturally employ different photonic encodings, namely time-bin in fiber and polarization in free space. Here we demonstrate a complete hybrid fiber and free-space QKD link that bridges both media within a single end-to-end protocol, converting between the two encodings entirely in the optical domain. Using the decoy-state BB84 protocol operating at 1550 nm, we demonstrate continuous secure-key generation over a 90 m outdoor free-space link. The system operates across atmospheric conditions spanning more than two orders of magnitude in the refractive-index structure parameter Cn^2, from strong daytime
turbulence to quiescent nighttime conditions, and we further validate
photon-level operation over a 750 m free-space extension. Throughout, the link maintains a session-mean
quantum bit error rate (QBER) of 5.6-6.8%, well below the 11% BB84 security threshold. The encoding conversion is performed entirely in the optical domain without measurement or state reconstruction, preserving the security assumptions of the BB84 protocol. Consequently, the time-bin-to-polarization (T2P) and polarization-to-time-bin (P2T) converters remain part of the untrusted
quantum channel rather than trusted intermediate nodes. These results establish secure photonic encoding conversion as a practical interface between fiber and free-space
quantum communication platforms, providing a building block for future
quantum networks applications.
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All authors Khen Cohen, Tomer Nahum, Michael Tzukran, Paz Or, Yehuda Pilnyak, Nitzan Livneh, Hagai Eisenberg, Yaron Oz, Haim Suchowski
Computational Physics · Cross-listed from quant-ph
A Quantum Computing Approach to Track Reconstruction in Strip-Type Detectors
Seungyeob Jwa, Hyunyong Kim, Jangho Kim et al. (+1 more)
This study investigates the use of
quantum annealing for particle track reconstruction in strip-type gaseous detectors. In such detectors, ghost hits and multiple hit combinations can turn pattern recognition into a combinatorial optimization problem. We formulate two reconstruction subproblems as quadratic unconstrained binary optimization problems. The first subproblem selects detector hits associated with a single
photon track inside a localized candidate region. The second subproblem selects cluster triplets from different detector layers so that multiple track candidates can be handled within a single
quantum processing unit(QPU) submission. The proposed formulations are tested using simulated DAMSA detector events. For the single track hit selection task, the QPU based reconstruction gives position and angular resolutions close to those obtained with a Kalman based reconstruction. In the simultaneous association task, valid cluster triplets are first extracted from the QPU samples and then connected using an association rule based on graph connectivity to construct track candidates. The DAMSA event
topology studied here has low pileup and is dominated by the two
photon signal from
axion-like particle(ALP) decay. In this setting, the results show that the QUBO formulations can reproduce local reconstruction decisions. This provides a practical basis for further studies of reconstruction methods that combine
quantum and classical computing in more complex tracking environments.
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All authors Seungyeob Jwa, Hyunyong Kim, Jangho Kim, Minseok Oh
Biological Physics · Cross-listed from astro-ph.HE
Supernova Neutrinos and the Origin of Biomolecular Homochirality
Amirmasoud Jannat, Soroush Shakeri and Farhad Shahbazi
We investigate the role of parity-violating interactions between
supernova neutrinos and
chiral molecules in nearby interstellar molecular clouds as a potential source of biomolecular homochirality. We introduce
neutrino interactions into the autocatalytic chemical reactions in a far-from-
equilibrium noise-induced system. These interactions create a directional bias between L and D enantiomers in the racemization reactions, which is amplified by autocatalysis and
stochastic fluctuations. We solve the
stochastic equations within the Ito sense to obtain the dynamics of the probability distribution of the enantiomeric excesses, offering an astrophysical scenario for the delivery of homochirality seeds to Earth by meteorites. In spite of the weak interactions of
supernova neutrinos, our framework introduces an amplification mechanism to yield a considerable enantiomeric excess of more than $10\%$, in agreement with the latest chemical analysis of the meteorites. Moreover, we scan over the parameter space of the model, inferring from the observational values in order to explore the window of opportunity to generate the initial seeds of homochiral states in interstellar molecular clouds.
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Optics
Symmetry-Informed Deep Learning for Electromagnetic Scattering
Viktor A. Lilja and Philippe Tassin
Deep learning can accelerate the modeling of electromagnetic devices by replacing costly simulations with neural networks trained to map design parameters to scattering parameters. However, data efficiency remains a central bottleneck, as training data is typically generated through expensive numerical simulations. Here we show that
symmetry provides a powerful and largely untapped route to overcoming this limitation in electromagnetic scattering problems. Leveraging the equivariance of Maxwell's equations, we obtain general transformation rules that map
symmetries of electromagnetic devices to corresponding transformations of their scattering parameters. This enables both systematic data augmentation and the construction of exactly equivariant neural networks. We implement the framework for both discrete and continuous
symmetry groups and demonstrate its effectiveness on photonic-
crystal slabs and free-form diffraction gratings. Incorporating
symmetry improves data efficiency by an order of magnitude compared to standard architectures, while equivariant models additionally enforce physical constraints exactly. Our approach is general and complementary to existing physics-informed strategies, provides a first-principles framework for constructing physically grounded surrogate models, and establishes
symmetry as a unifying inductive bias for data-efficient and physically consistent learning in computational electromagnetics and beyond.
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Geophysics
Dispersion-Guided Physics-Aware Deep Inverse Operator for Surface Wave Mode Separation
Yang Cui, Sujith Swaminadhan, Yangkang Chen et al. (+2 more)
Surface-wave (SW) dispersion analysis is widely used in near-surface geophysics and seismology to determine shear-wave velocity structures by measuring SW
geometric dispersion in seismic data. Among the available approaches, multichannel analysis of surface waves (MASW) and two-station methods are commonly employed to extract dispersion information for SW inversion. However, the coexistence of fundamental and higher modes in seismic data poses challenges for these methods, particularly for two-station analysis. To separate the different mode components, we propose a physics-aware unsupervised deep-learning framework. The method acts as a deep inverse operator that directly separates fundamental- and higher-mode components in the time-space domain using an adaptive Gaussian mask constructed in the frequency-phase-velocity (f-v) domain. Physical constraints are incorporated into the loss function by maximizing energy concentration within the target mask while suppressing leakage outside it. Through backpropagation, the network learns the inverse mapping from physical constraints in the f-v domain to wavefield separation in the time-space domain without requiring labeled training data. Numerical experiments on both synthetic and field data show that the framework provides a robust and automated solution for SW mode separation, facilitating more reliable dispersion-curve picking and improving the accuracy of subsequent SW inversion.
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All authors Yang Cui, Sujith Swaminadhan, Yangkang Chen, Christian Schiffer, Myrto Papadopoulou
Instrumentation and Detectors · Cross-listed from gr-qc
Evaluating KAGRA upgrade scenarios for multimessenger observations of binary neutron stars
Yuta Michimura, Soichiro Morisaki, Kenta Hotokezaka et al. (+1 more)
Binary
neutron star mergers are key targets for multimessenger astronomy, motivating future upgrades of gravitational-wave detectors. For KAGRA, both broadband sensitivity improvements that increase the binary
neutron star detection range, and high-frequency optimizations targeting
neutron-
star physics are under consideration. We present a computationally efficient framework to evaluate the multimessenger performance of detector upgrades by combining Fisher-
matrix estimates of localization area and localization volume with detector duty factors and binary
neutron star merger rates. We apply this framework to proposed KAGRA upgrade scenarios within the LIGO-Virgo-KAGRA network. For identical sources, the high-frequency upgrade improves sky localization by about 20% compared with the broadband option. However, when detection rates are taken into account, the broadband upgrade yields a larger number of well-localized events. Despite its shorter binary
neutron star range than the other detectors, the inclusion of KAGRA increases the number of events localized within $10^3$ Mpc$^3$ volume by about 60%. These results provide a quantitative framework for evaluating future detector upgrades from the perspective of multimessenger observations.
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All authors Yuta Michimura, Soichiro Morisaki, Kenta Hotokezaka, Masaomi Tanaka
Biological Physics · Cross-listed from cond-mat.soft
Entropy-Driven Initiation and Cellular Uptake Mediated by Viscoelastic Cytoskeleton: A Kinetic Phase Diagram from Onsager Variational Principle
Jinjie Liu, Zhong-Can Ou-Yang and Hao Wu
A fundamental question in receptor-mediated endocytosis remains unanswered: what initial driving force brings ligands and receptors into close proximity? While previous models assume pre-existing contact and overlook this initiation problem, we propose that entropic forces from nanoscale biomolecules in crowded cellular environments provide the essential driving mechanism. We develop a unified continuum model rooted in the Onsager variational principle, where engulfment depth serves as the generalized coordinate and the driving force derives from a free energy landscape of entropic, binding, membrane, and cytoskeleton contributions. The framework naturally incorporates: (i)
entropy-driven adhesion as initiation; (ii) ligand-receptor binding as the sustaining force; (iii) membrane deformation via the Helfrich-Canham
Hamiltonian; and (iv) cytoskeleton viscoelasticity through the elastic-viscoelastic correspondence principle. The kinetic phase diagram predicts a critical biomolecule concentration for initiation, a lower bound of ligand density for complete engulfment, a finite size window for engulfable particles, and an optimal virus radius of 30–60 nm that decreases with increasing binding energy. The Onsager solubility condition naturally yields the phase boundaries. The model exhibits asymptotic consistency with the classic Asakura-Oosawa result in the large-particle flat-surface limit. Stiffer
cells lead to longer engulfment times and narrower size windows. Strikingly, the optimal size matches HIV-1 dimensions under physiologically realistic parameters. This work provides a variational foundation for cellular uptake with implications for virology, nanotechnology, and drug delivery.
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Biological Physics
On seasonal trunk thermal buffering and its electrical signature in mature trees
Jean-Baptiste Boulé, Vincent Courtillot, Dominique Gibert et al. (+4 more)
Tree trunks contain living tissues whose functioning depends on their thermal environment, yet the processes governing trunk temperature under field conditions remain poorly understood. In particular, it is unclear whether hydraulic transport contributes to buffering trunk temperature against atmospheric variability. We investigated this question by continuously monitoring sapwood temperature, local air temperature, soil temperature at 1~m depth, and spontaneous electrical potential (SP) in six mature trees, comprising three oaks and three hornbeams, over multiple years in a temperate urban forest garden. trunk temperature exhibited a smoother seasonal cycle than air temperature and remained consistently closer to deep-soil temperature, indicating substantial thermal buffering. Seasonal components extracted from the time series revealed a coherent delayed relationship between SP and the trunk-soil temperature difference. Phase-space analysis showed reproducible hysteresis across individuals, and instantaneous phase estimates indicated a lag of approximately 100~days in five of the six trees. A minimal energy-balance model further showed that trunk heat storage alone was insufficient to reproduce the observed seasonal dynamics. Positive effective soil-coupling coefficients were obtained for most individuals, although their magnitude varied markedly among trees. These results are consistent with a contribution of vertically mediated, hydraulically linked heat transfer to seasonal trunk thermal regulation. They further suggest that spontaneous electrical potentials may provide a non-invasive, integrative indicator of slow hydraulic and thermal processes within trees. Such thermo-hydraulic coupling may influence the thermal environment of the cambium and phloem and could therefore contribute to tree responses to seasonal heat and climatic variability.
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All authors Jean-Baptiste Boulé, Vincent Courtillot, Dominique Gibert, Fernando Lopes, Alexis Maineult, Pierpaolo Zuddas, Jean de Bremond d'Ars
History and Philosophy of Physics · Cross-listed from astro-ph.IM
A genetic algorithm for peer-review panel composition
Ferdinando Patat
The composition of scientific review panels is a constrained optimization problem in which a finite pool of experts must be distributed among multiple panels while balancing scientific expertise and demographic diversity. As the number of possible panel configurations grows very rapidly with the number of reviewers, exhaustive searches rapidly become computationally impractical. In this paper I present a genetic
algorithm designed to optimize panel composition for the European Southern Observatory (ESO) proposal evaluation process. Panel assignments are represented through a chromosome-based encoding. Candidate solutions are evaluated using a fitness function based on four imbalance indicators: scientific expertise, gender, country affiliation, and professional seniority. The method is tested using real reviewer data from the ESO proposal handling system. The results show that the genetic
algorithm rapidly identifies panel configurations with substantially lower imbalance than those obtained from random assignments and progressively improves the quality of the overall population. Beyond producing a single optimized configuration, the approach generates a set of high-quality panel realizations that can subsequently be filtered according to additional operational constraints not explicitly included in the fitness function. Although developed for ESO, the methodology is general and applicable to a wide range of panel-based peer-review systems.
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