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Physics Physics

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Wednesday 11 February

History and Philosophy of Physics · Cross-listed from quant-ph

Pilot-Wave Theories as Hidden Markov Models

Jacob A. Barandes

The original version of the de Broglie-Bohm pilot-wave theory, also called Bohmian mechanics, attempted to treat the wave function or pilot wave as a part of the physical ontology of nature. More recent versions of the de Broglie-Bohm theory appearing in the last few decades have tried to regard the pilot wave instead as an aspect of the theory's nomology, or dynamical laws. This paper argues that neither of these views is correct, and that the de Broglie-Bohm pilot wave is best understood as a collection of latent variables in the sense of a hidden Markov model, a construct that was not available when de Broglie and Bohm originally formulated what became their pilot-wave theory. This paper also discusses several other challenges for the ontological view of the pilot wave. One such challenge is due to Foldy-Wouthuysen gauge transformations, which connect up with the Deotto-Ghirardi ambiguity in the de Broglie-Bohm theory. Another challenge arises from the freedom to carry out canonical transformations in the wave function's own notion of phase space, as defined by Strocchi and Heslot.
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Accelerator Physics · Cross-listed from hep-ph

Unidentified falling objects in the LHC as dark matter signals

Xunyu Liang and Ariel Zhitnitsky

Unidentified Falling Objects (UFOs) refer to sporadic beam losses observed during LHC operation. The prevailing explanation is that micrometer-sized dust particles released from the beam screen produce beam losses through interactions with the protons. However, the release mechanism of these particles remains unknown. We propose that roughly $(1-10)$% of UFOs may be caused by axion quark nuggets (AQNs), macroscopic dark matter (DM) candidates with masses of order $(5-1000)\,$g. The AQN model naturally relates the dark- and visible-matter abundances ($\Omega_\mathrm{DM}\sim\Omega_\mathrm{visible}$) and provides a mechanism for generating the baryon-antibaryon asymmetry, with DM composed of both matter and antimatter AQNs. When passing underground within approximately 100km of the LHC, an antimatter AQN generates acoustic waves strong enough to trigger multiple UFO events within $2\,$s. If three correlated UFOs (placed at different locations along the LHC ring) are detected, the signal-to-noise ratio can exceed 5 across the entire allowed AQN mass range for a measurement time of about 360 hours. Practically, the LHC can serve as a large broadband acoustic detector for AQNs.
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Geophysics

Field-Deployable Hybrid Gravimetry: Projecting Absolute Accuracy Across a Remote 24km$^2$ Survey via Daily Quantum Calibration

Nathan Shettell, Kai Sheng Lee, Fong En Oon et al. (+3 more)

Absolute gravimeters deliver drift-free, high-precision measurements but are typically bulky and difficult to deploy, whereas relative gravimeters are lightweight and mobile but intrinsically limited by time-dependent drift. We demonstrate a hybrid quantum-enabled gravimetry approach in which an on-site atomic gravimeter provides routine, $\mu$Gal-level calibration of two mobile spring gravimeters during a field survey spanning 24 km$^2$ of dense tropical terrain. The atomic reference enables high-precision, asynchronous cross-comparison of relative measurements acquired over seven days, effectively suppressing instrumental drift to a level required for demanding geophysical applications. This deployment captures regional gravity gradients with high fidelity under challenging environmental conditions, illustrating how field-operable quantum sensors can extend quantum-grade gravimetry beyond laboratory settings and serve as scalable calibration backbones for large-area, high-precision geophysical surveys in remote or logistically constrained environments.
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All authors Nathan Shettell, Kai Sheng Lee, Fong En Oon, Elizaveta Maksimova, Hong Hui Chen, Rainer Dumke

Space Physics · Cross-listed from astro-ph.SR

Data-driven Magnetohydrodynamic Simulation of the Initiation of a Coronal Mass Ejection with Multiple Stages

J. H. Guo, S. Poedts, B. Schmieder et al. (+8 more)

Coronal mass ejections (CMEs) are the primary drivers of adverse space-weather events, yet their initiation and onset prediction remain insufficiently understood due to the complexity of the magnetic topology and physical processes in real solar source regions. Here, based on fully observational-data-driven magnetohydrodynamic simulation, we successfully reproduce the initiation of a CME originating from the super active region AR 13663, with only a one-minute time lag between the flare peak in observations and the velocity peak of the rising flux rope in the simulation. Moreover, the eruptive structure exhibits a multi-stage kinematic evolution: an initial slow acceleration, a plateau at a nearly stationary height, and a subsequent impulsive acceleration. These stages correspond to torus instability, the downward tension force exerted by the overlying toroidal field, and fast magnetic reconnection, respectively. Our results highlight the inherently multistage nature of CME initiation in real events. In configurations with strong overlying toroidal fields, the downward toroidal-field-induced tension force can suppress the rise of the flux rope and produce a plateau phase at a nearly stable height, even when torus instability occurs. In contrast, the subsequent fast magnetic reconnection beneath the flux rope can drive the impulsive eruption more effectively. The close agreement between the observed and simulated peak times over one minute demonstrates the strong potential of our data-driven model for predicting CME onset.
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All authors J. H. Guo, S. Poedts, B. Schmieder, Y. Guo, C. Zhou, H. Wu, Y. W. Ni, Z. Zhong, Y. H. Zhou, S. H. Li, P. F. Chen

Fluid Dynamics

Accurate simulation of pulled and pushed fronts in the nonautonomous Fisher-Kolomogorov-Piskunov-Petrovsky equation

Troy Tsubota, Smridhi Mahajan, Adrian van Kan et al. (+1 more)

We introduce a novel numerical method for direct simulation of front propagation in the Fisher-KPP equation with a time-dependent parameter on an infinite domain. The method computes a time-dependent boundary condition that accurately captures the leading-edge dynamics by coupling the nonlinear simulation region to a linear approximation region in which the dynamics can be solved exactly via the Green's function of the linearized equation. This approach enables precise front velocity measurements on relatively small computational domains for a variety of nonautonomous regimes and initial conditions for which existing numerical methods break down. We apply the method to pulled and pushed fronts in the Fisher-KPP equation with quadratic and quadratic-cubic nonlinearities, finding that it improves the accuracy of the simulated front velocity even for constant parameters and a fixed domain size. For pulled fronts with a diffusion coefficient that increases algebraically in time, our results reveal a deviation from the natural asymptotic velocity predicted by linear theory, whose explanation requires nonlinear theory. For pushed fronts with constant parameters, the method reproduces the exponential convergence to the theoretical asymptotic front speed and profile with improved precision. For a slowly time-varying linear growth parameter, we find that the pushed front velocity follows the changing parameter adiabatically if the asymptotic pushed velocity remains faster than the natural asymptotic pulled velocity. As the growth parameter moves toward the pushed–pulled transition point, the competition between the pushed and pulled fronts can result in both delayed and even premature onset of the pushed–pulled transition, depending on the form of parameter growth. The numerical method presented here proves to be an effective tool for analyzing front propagation in nonautonomous systems.
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All authors Troy Tsubota, Smridhi Mahajan, Adrian van Kan, Edgar Knobloch

Computational Physics · Cross-listed from cs.LG

A Multimodal Conditional Mixture Model with Distribution-Level Physics Priors

Jinkyo Han and Bahador Bahmani

Many scientific and engineering systems exhibit intrinsically multimodal behavior arising from latent regime switching and non-unique physical mechanisms. In such settings, learning the full conditional distribution of admissible outcomes in a physically consistent and interpretable manner remains a challenge. While recent advances in machine learning have enabled powerful multimodal generative modeling, their integration with physics-constrained scientific modeling remains nontrivial, particularly when physical structure must be preserved or data are limited. This work develops a physics-informed multimodal conditional modeling framework based on mixture density representations. Mixture density networks (MDNs) provide an explicit and interpretable parameterization of multimodal conditional distributions. Physical knowledge is embedded through component-specific regularization terms that penalize violations of governing equations or physical laws. This formulation naturally accommodates non-uniqueness and stochasticity while remaining computationally efficient and amenable to conditioning on contextual inputs. The proposed framework is evaluated across a range of scientific problems in which multimodality arises from intrinsic physical mechanisms rather than observational noise, including bifurcation phenomena in nonlinear dynamical systems, stochastic partial differential equations, and atomistic-scale shock dynamics. In addition, the proposed method is compared with a conditional flow matching (CFM) model, a representative state-of-the-art generative modeling approach, demonstrating that MDNs can achieve competitive performance while offering a simpler and more interpretable formulation.
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Plasma Physics

Bridging the Kinetic-Fluid Gap: Ion-Driven Magnetogenesis to Prime Cosmic Dynamos

X. Liu, D. Wu and J. Zhang

The origin of cosmic magnetic fields is widely attributed to the amplification of weak seed fields by turbulent dynamos. However, a critical understanding gap remains between the microscopic generation of these seeds and the macroscopic onset of the dynamo. Current kinetic models, often constrained to electron scales, predict premature saturation via magnetic trapping, leaving the generated fields potentially too weak and small-scale to effectively prime magnetohydrodynamic (MHD) processes. Here, using high-resolution kinetic simulations with a realistic mass ratio, we reveal the physics of this unexplored ion-kinetic regime. Under generalized continuous shear driving, used to simulate ubiquitous macroscopic flows, we demonstrate that the saturation of electron instabilities is not the endpoint but a precursor to a distinct, ion-dominated evolution. Massive ions, sustaining the velocity shear, trigger a subsequent filamentation instability that accesses the vast ion kinetic energy reservoir. This mechanism amplifies the magnetic energy by orders of magnitude beyond the electron-saturation limit, expanding the field coherence to ion scales. Our results establish ion kinetics as the essential ”missing link” that bridges the divide between microscopic plasma instabilities and macroscopic cosmic dynamos.
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Space Physics

Shocks, compressible perturbations, and intermittency in the very local interstellar medium: Voyager 1 and 2 observations and numerical modeling

Federico Fraternale, Nikolai V. Pogorelov, Ratan Bera et al. (+2 more)

Voyager spacecraft (V1 and V2) provide unique in situ measurements of perturbations propagating beyond the heliopause through the very local interstellar medium (VLISM), including the shocks and pressure fronts whose origin is debated. In particular, a jump in magnetic field strength, observed by V1 in 2020.4 at 149.3 au from the Sun, was followed by a distinct "hump" and persistently strong magnetic field, both requiring theoretical explanation. This paper offers an interpretation of those observations using a self-consistent, MHD model of the solar wind - LISM interaction driven by the OMNI and interplanetary scintillation data combined with a turbulence analysis of Voyager data. Our simulations convincingly demonstrate that global, solar-cycle-driven compressions, on hitting the heliopause, can reproduce those puzzling V1 observations. They appear to be associated with solar cycle 24, whereas similar interstellar magnetic field structures can occur once per cycle. The turbulence analysis reveals time-dependent magnetic compressibility that persists up to 165 au at scales below 10 days. Turbulence intermittency at scales below 1 hour is mostly confined to specific intervals, possibly associated with a broad foreshock region. The apparent disappearance of intermittency since 2022 reflects the turbulence weakening rather than a fundamental change in VLISM properties. We predict that V1 will record relatively strong magnetic field strengths until $\sim$2030, followed by weaker, infrequent perturbations. At V2, we expect multiple solar-driven compressions before 2026, followed by a major event induced by solar cycle 25 around 2030. New Horizons is expected to cross the termination shock at 80$\pm$2 au in 2031.
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All authors Federico Fraternale, Nikolai V. Pogorelov, Ratan Bera, Leonard F. Burlaga, Maciej Bzowski

Physics and Society

The selective use of physics knowledge in policy: how interdisciplinary physics bridges subfields and shapes policy influence

Jeongmin Lee and Jisung Yoon

Scientific knowledge has become central to policymaking as societies face challenges related to technological change, climate risk, and public health. Despite the growing emphasis on evidence-based policy, a systematic understanding of how science is selectively used in policy, specifically which forms of knowledge are preferred and which scientific citations translate into influence, remains limited. We address these questions by constructing a novel dataset that links policy documents from the Overton database with publications from the American Physical Society, enabling an analysis of how physics knowledge enters and circulates in policy discourse. Using subfield classifications, we provide quantitative evidence for a gap between scientific communities and policymakers. First, we find that policy documents draw on broad and interdisciplinary areas of physics, such as General Physics and Interdisciplinary Physics, rather than mirroring the structure of physics research production. Second, we identify substantial institutional heterogeneity with systematic differences in subfield preferences across policy producing organizations and topics. Third, network analysis reveals that interdisciplinary areas of physics act as a central bridge connecting specialized subfields. Finally, regression analysis reveals a clear separation between policy visibility and policy influence. While interdisciplinary areas facilitate entry into policy discourse, it does not necessarily increase downstream policy influence. Conversely, documents citing geophysics are associated with approximately 24 percent higher policy influence, likely driven by the political salience of climate change policy. Our findings underscore the distinction between scientific visibility and policy influence, contributing to a deeper understanding of the complex relationship between scientific communities and policy system.
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Optics · Cross-listed from cond-mat.mtrl-sci

Excitons in van der Waals magnetic materials

Pratap Chandra Adak, Florian Dirnberger, Swagata Acharya et al. (+3 more)

Two-dimensional magnetic semiconductors provide a unique materials platform in which long-range magnetic order coexists with strongly bound excitons. Because excitonic states and magnetic moments originate from the same electronic orbitals and are coupled through intrinsic exchange interactions, optical excitations in these systems exhibit pronounced sensitivity to magnetic order. Recent experiments have revealed unusually strong magneto-optical responses, as well as direct coupling between excitons and magnons, establishing new routes for controlling light-matter interactions with spin degrees of freedom. This Review surveys key developments in the field, focusing on representative material systems, experimental signatures of exciton-magnetism coupling, and the theoretical frameworks used to describe these phenomena. We conclude with perspectives on how this rapidly evolving field could enable next-generation optoelectronic and quantum technologies leveraging the coupled dynamics of light, charge, and spin.
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All authors Pratap Chandra Adak, Florian Dirnberger, Swagata Acharya, Akashdeep Kamra, Xiaodong Xu, Vinod M. Menon

Physics and Society

Pivoting as an Adaptive Strategy to Geopolitical Tensions in U.S. Science

Moxin Li, Yifang Ma, Yang Wang et al. (+1 more)

Geopolitical tensions increasingly reshape the structure and openness of global science, yet we still lack a clear understanding of how successfully scientists adapt their work under such pressures. Using millions of funding and publication datasets across the past ten years, we investigate how U.S. China geopolitical tensions reshaped individual research activities of U.S. based scientists, particularly those collaborating with Chinese peers. We find that although U.S. China geopolitical tensions significantly reduce funding opportunities, many scientists actively respond by pivoting their research portfolios toward alternative topics, and this adaptive reorientation partially mitigates funding losses. Crucially, the effectiveness of this adaptive strategy is highly unequal: for scientists in high risk domains, those of Asian descent, and early-career scientists, pivoting offers only limited protection against funding loss. Our results demonstrate that geopolitical tensions reshape science through shifts in scientists' strategic decisions about their research focus. Understanding this adaptive but uneven reconfiguration is essential for science policies to strengthen the resilience and inclusiveness of the scientific enterprise.
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All authors Moxin Li, Yifang Ma, Yang Wang, Dashun Wang

Optics · Cross-listed from cs.LG

Experimental Demonstration of Online Learning-Based Concept Drift Adaptation for Failure Detection in Optical Networks

Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro et al. (+4 more)

We present a novel online learning-based approach for concept drift adaptation in optical network failure detection, achieving up to a 70% improvement in performance over conventional static models while maintaining low latency.
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All authors Yousuf Moiz Ali, Jaroslaw E. Prilepsky, João Pedro, Antonio Napoli, Sasipim Srivallapanondh, Sergei K. Turitsyn, Pedro Freire

Fluid Dynamics · Cross-listed from eess.SP

Boiling flow parameter estimation from boundary layer data

Jeffrey W. Utley, Gregery T. Buzzard, Charles A. Bouman et al. (+1 more)

Atmospheric turbulence and aero-optic effects cause phase aberrations in propagating light waves, thereby reducing effectiveness in transmitting and receiving coherent light from an aircraft. Existing optical sensors can measure the resulting phase aberrations, but the physical experiments required to induce these aberrations are expensive and time-intensive. Simulation methods could provide a less expensive alternative. For example, an existing simulation algorithm called boiling flow, which generalizes the Taylor frozen-flow method, can generate synthetic phase aberration data (i.e., phase screens) induced by atmospheric turbulence. However, boiling flow depends on physical parameters, such as the Fried coherence length r0, which are not well-defined for aero-optic effects. In this paper, we introduce a method to estimate the parameters of boiling flow from measured aero-optic phase aberration data. Our algorithm estimates these parameters to fit the spatial and temporal statistics of the measured data. This method is computationally efficient and our experiments show that the temporal power spectral density of the slopes of the synthetic phase screens reasonably matches that of the measured phase aberrations from two turbulent boundary layer data sets, with errors between 8-9%. However, the Kolmogorov spatial structure function of the phase screens does not match that of the measured phase aberrations, with errors above 28%. This suggests that, while the parameters of boiling flow can reasonably fit the temporal statistics of highly convective data, they cannot fit the complex spatial statistics of aero-optic phase aberrations.
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All authors Jeffrey W. Utley, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Tuesday 10 February

Geophysics

Hearing the forest for the trees: machine learning and topological acoustics for remote sensing with seismic noise

Jiayang Wang, I-Tzu Huang, Bingxu Luo et al. (+7 more)

Monitoring remote forests is a global challenge central to climate mitigation and biodiversity conservation, yet satellite observations are frequently limited by weather, dense canopies, and solar dependency. Here we show that passive seismic sensing offers a persistent, all-weather alternative for autonomous ecosystem monitoring by capturing characteristic learnable signatures of trees within the ambient wavefield. Using seismic data from Alaska, we demonstrate that cross-correlations between stations provide a physical basis for forest detection by approximating the empirical Green's function of the medium. Supervised machine learning models applied to these data achieve a classification accuracy of 86%, identifying key discriminating frequencies (35 to 60 Hz) consistent with known forest-wave interactions. A topological acoustics analysis of the geometric phase change independently confirms the physical origin of these data-driven classifications. Together, these results provide the first demonstration that subtle forest-wave interactions manifest in ambient seismic noise and can be harnessed as a scalable tool for continuous vegetation monitoring, offering a robust solution for tracking environmental change challenging regions.
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All authors Jiayang Wang, I-Tzu Huang, Bingxu Luo, Susan L. Beck, Falk Huettmann, Skyler DeVaughn, Benjamin Stilin, Keith Runge, Pierre Deymier, Marat I. Latypov

Computational Physics

Boltzmann Generators for Condensed Matter via Riemannian Flow Matching

Emil Hoffmann, Maximilian Schebek, Leon Klein et al. (+2 more)

Sampling equilibrium distributions is fundamental to statistical mechanics. While flow matching has emerged as scalable state-of-the-art paradigm for generative modeling, its potential for equilibrium sampling in condensed-phase systems remains largely unexplored. We address this by incorporating the periodicity inherent to these systems into continuous normalizing flows using Riemannian flow matching. The high computational cost of exact density estimation intrinsic to continuous normalizing flows is mitigated by using Hutchinson's trace estimator, utilizing a crucial bias-correction step based on cumulant expansion to render the stochastic estimates suitable for rigorous thermodynamic reweighting. Our approach is validated on monatomic ice, demonstrating the ability to train on systems of unprecedented size and obtain highly accurate free energy estimates without the need for traditional multistage estimators.
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All authors Emil Hoffmann, Maximilian Schebek, Leon Klein, Frank Noé, Jutta Rogal

Biological Physics

The arrangement of anisotropic spin couplings can optimize sensitivity of the cryptochrome radical pair to the direction of geomagnetic field

Victor Bezchastnov and Tatiana Domratcheva

Sensing of the geomagnetic field direction by many living organisms is commonly thought to involve radical pairs, such as those formed photochemically between the flavin and tryptophan radicals in the cryptochrome proteins. Previous theoretical studies have shown that strongly axial hyperfine couplings in the cryptochrome radicals greatly enhance the formation of a signaling state of the protein when the magnetic field is directed perpendicular to the hyperfine axis of either of the radicals. However, further analysis led to the conclusion that sharpness of detecting those magnetic directions is strongly suppressed by the inter-radical electron spin coupling. Here, we perform theoretical simulations of the compass function for a set of arrangements of the intra- and inter-radical spin couplings in the idealized cryptochrome radical pair, and find certain arrangements that preserve the sharpness in detecting the direction of the geomagnetic field. One particular arrangement, with the hyperfine axes of the radicals orthogonal to the symmetry axis of inter-radical coupling, provides even sharper field-direction sensitivity than that contributed solely by the anisotropy of the hyperfine coupling.
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Chemical Physics

AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature

Wei Yang, Zihao Liu, Tao Tan et al. (+6 more)

This paper presents a large language model (LLM) agent named AgentCAT, which extracts and analyzes catalytic reaction data from chemical engineering papers, %and supports natural language based interactive analysis of the extracted data. AgentCAT serves as an alternative to overcome the long-standing data bottleneck in chemical engineering field, and its natural language based interactive data analysis functionality is friendly to the community. AgentCAT also presents a formal abstraction and challenge analysis of the catalytic reaction data extraction task in an artificial intelligence-friendly manner. This abstraction would help the artificial intelligence community understand this problem and in turn would attract more attention to address it. Technically, the complex catalytic process leads to complicated dependency structure in catalytic reaction data with respect to elementary reaction steps, molecular behaviors, measurement evidence, etc. This dependency structure makes it challenging to guarantee the correctness and completeness of data extraction, as well as representing them for analysis. AgentCAT addresses this challenge and it makes four folds of technical contributions: (1) a schema-governed extraction pipeline with progressive schema evolution, enabling robust data extraction from chemical engineering papers; (2) a dependency-aware reaction-network knowledge graph that links catalysts/active sites, synthesis-derived descriptors, mechanistic claims with evidence, and macroscopic outcomes, preserving process coupling and traceability; (3) a general querying module that supports natural-language exploration and visualization over the constructed graph for cross-paper analysis; (4) an evaluation on $\sim$800 peer-reviewed chemical engineering publications demonstrating the effectiveness of AgentCAT.
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All authors Wei Yang, Zihao Liu, Tao Tan, Xiao Hu, Hong Xie, Lulu Li Xin Li, Jianyu Han, Defu Lian, Mao Ye

Physics and Society

Condensed Past, Thick Present: Evolutionary Approach to the Conscious Experience

Anna Sverdlik

This paper examines the conceptual convergence between Lee Smolin's Causal Theory of Views, Karl Friston's Free Energy Principle, and contemporary psychological accounts of the functions of consciousness. Although formulated within different domains – physics, biology, and psychology – all three frameworks, in one form or another, appeal to processes of transition from uncertainty to certainty, in which novelty arises through the resolution of surprise. According to the first two approaches, these transitions are realized within particular temporo-spatial gaps, which themselves evolve and become increasingly elaborate as organization grows. By tracing the structural and functional parallels between these frameworks, the paper proposes an account of how the evolution and the gradual elaboration of novelty, surprise, and these temporo-spatial gaps may be linked to the emergence and progressive development of consciousness, up to its highest forms addressed by psychology.
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Fluid Dynamics · Cross-listed from cond-mat.soft

Shape, confinement and inertia effects on the dynamics of a driven spheroid in a viscous fluid

Aditya Bhowmik, Kevin Stratford, Oliver Henrich et al. (+1 more)

The dynamics of anisotropic particles in viscous flows underpin a wide range of processes in soft matter, microfluidics, and targeted drug delivery. Here, we investigate the motion of externally driven prolate and oblate spheroids suspended in a Newtonian fluid and confined within a square microchannel. Using lattice Boltzmann simulations, complemented by far-field hydrodynamic theory based on superposition of wall interactions, we systematically quantify how particle aspect ratio, strength of confinement, and fluid inertia influence the dynamics of a spheroid. For unconfined spheroids, we show that the translational velocity is maximized not for a sphere but for a prolate (end-on) or oblate (broadside-on) spheroid of a specific aspect ratio. Under confinement, the optimal aspect ratio shifts toward oblate shapes due to the dominant contribution of wall-induced frictional resistance. Off-center positioning introduces strong translation-rotation coupling, giving rise to two families of oscillatory trajectories - glancing and reversing - whose existence and structure are captured as closed orbits in phase space. Weak fluid inertia breaks these closed loops: glancing trajectories spiral outward and merge with reversing trajectories, and new stable fixed points emerge. Together, these results reveal how modest deviations from sphericity or creeping-flow conditions profoundly alter the dynamics of driven particles in confined geometries. The predictions offer guidelines for optimizing particle shape in microfluidic transport and highlight the rich nonlinear behavior accessible in confined suspensions of nonspherical colloids.
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All authors Aditya Bhowmik, Kevin Stratford, Oliver Henrich, Sumesh P. Thampi

Fluid Dynamics

Transonic Buffet Modeling via Invariant Manifolds

Tea Vojković, David Quero, Rahul Jayaraj et al. (+3 more)

In transonic flow over aircraft wings, shock-boundary-layer interactions can give rise to transonic buffet, which degrades maneuverability through unsteady aerodynamic loads. Beyond its practical importance, two-dimensional transonic buffet represents a canonical example of a global instability for which reduced-order modeling remains challenging due to nonlinearity, sharp spatial gradients, and the coexistence of an unstable equilibrium with an attracting limit cycle. Commonly, reduced-order models of such phenomena capture nonlinear dynamics only in aerodynamic observables, while prediction of the full flow state is achieved through linear representations valid only near the unstable equilibrium or on the limit cycle. In this work, we present a reduced-order model that predicts the nonlinear evolution of the full flow field by exploiting the existence of an attracting two-dimensional invariant manifold. We adapt an existing data-driven framework for identifying invariant manifolds and the associated reduced dynamics, making it suitable for scaling to large-scale CFD applications. The invariant manifold is identified as a graph over its tangent space using an iterative encoder-update and the reduced dynamics are obtained via least-squares regression. A subsequent extended normal-form transformation enables physical interpretability of the model through a modal decomposition of the flow. The reduced-order model is identified for transonic buffet over the OAT15A supercritical airfoil, showing that it is possible to achieve this accurately using just a single training trajectory. Validation against independent simulations demonstrates accurate prediction of nonlinear behavior, together with reliable reconstruction of the full flow field, particularly in the late-transient and limit-cycle regimes.
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All authors Tea Vojković, David Quero, Rahul Jayaraj, Christoph Kaiser, Dimitris Boskos, Abel-John Buchner

Classical Physics · Cross-listed from quant-ph

Uncertainty and Wigner negativity in Hilbert-space classical mechanics

Mustafa Amin

Classical mechanics, in the Koopman-von Neumann formulation, is described in Hilbert space. It is shown here that classical canonical transformations are generated by Hermitian operators that are in general noncommutative. This naturally brings about uncertainty relations inherent in classical mechanics, for example between position and the generator of space translations, between momentum and the generator of momentum translations, and between dynamical time and the Liouvillian, to name a few. Further, it is shown that the Wigner representation produces a quasi-probability distribution that can take on negative values. Thus, two of the hallmark features of quantum mechanics are reproduced, and become apparent, in a Hilbert-space formulation of classical mechanics.
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Optics

Second-harmonic stabilization of a bulk photonic resonator

Lindell M. Williams, Grant M. Brodnik and Scott B. Papp

The resonant modes of optical cavities provide a powerful resource for laser-frequency stabilization, underpinning high-precision metrology and coherent signal generation. Photonic resonators in which the optical mode propagates through material offer a compact alternative to vacuum Fabry-Perot cavity systems, but their performance is limited by sensitivity of the material to the ambient environment. In this work, we explore second-harmonic (SH) stabilization, which exploits the interplay of a dispersive mode structure against the strict energy conservation of second-harmonic generation. Operationally, we use two, 1550 nm lasers to PDH-detect octave-spaced resonant modes of an ultra-high-Q photonic resonator with one laser frequency-doubled to 775 nm. Under SH stabilization, the microwave frequency offset between the 1550 nm lasers, which we refer to as the SH signal ($f_{SH}$) maps the absolute frequency of the 1550 nm laser to an electronic signal. We characterize this mapping through comparison of the absolute optical frequency inference provided by $f_{SH}$ to an out-of-loop optical measurement, and our results suggest $f_{SH}$ accurately proxies frequency drift. We evaluate the sensitivity and noise floor of this technique, considering contributions from laser locking and bulk material properties, and conclude that $f_{SH}$ is sufficiently sensitive to enhance long-term laser-frequency stability with respect to the resonator. These results demonstrate SH stabilization as a useful technique that infers absolute drift, thereby enabling the increased stability of future compact, precision frequency references.
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Fluid Dynamics

Towards a full-scale version of Yakhot's model of strong turbulence

Christoph Renner

We present first elements of an extension of Yakhot's model of strong turbulence towards small scales. The analysis is based on an empirically observed relation for even order structure functions which extends from the inertial into the dissipation range. With this relation and Kolmogorov's four-fifth law, models for structure functions of orders two and three can be derived that replicate expected small scale limits and describe the transition from dissipative to inertial range scaling regimes correctly. An additional length scale parameter is introduced by the extension. It marks the crossover point from the inertial to the dissipation range and can be expressed as a function of the Reynolds number. In combination with a recently proposed large-scale extension of Yakhot's model, we ultimately obtain full-scale models for structure functions of second and third order. These expressions are closed–form, do not contain free parameters and are in good agreement with experimental data from the smallest dissipative scales up to the system scale.
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Fluid Dynamics

Comparing surface and deep horizontal distributions of depth-keeping particles in shallow fluid layers

Lenin M. Flores Ramírez, Matias Duran-Matute and Herman J. H. Clercx

This study examines whether the dispersion of passive particles at the free surface of a generic (nonturbulent) shallow flow can reliably represent the behavior of depth-keeping particles below the surface. A shallow configuration characterize many aquatic environments, such as coastal regions and lakes, where horizontal scales far exceed vertical ones, large-scale flow structures dominate, and observations are sometimes limited to the surface. We compare surface and subsurface horizontal velocities in both direction and magnitude, identifying distinct behaviors depending on the parameter $Re_F\delta^2$, where $Re_F$ is the Reynolds number based on forcing, and $\delta$ is the aspect ratio between the fluid layer depth and the horizontal forcing scale. At low $Re_F\delta^2$, deep flows match the surface flow in direction throughout the layer, but not in magnitude. At high $Re_F\delta^2$, the magnitude matches (outside the bottom boundary layer), but not always the direction. Despite these differences, for all $Re_F\delta^2$, surface particle patterns correlate with those in the upper quarter of the fluid layer. Filamentary structures caused by horizontal flow convergence remain spatially aligned within this region. Below it, at intermediate $Re_F\delta^2$, deep filaments become diffuse and eventually vanish. At high $Re_F\delta^2$, filaments persist at depth, but become spatially misaligned with surface filaments. These findings suggest that in shallow environments, surface observations can quantitatively infer subsurface transport processes in the upper quarter of the fluid layer. For the deeper part, knowledge of the vertical profiles of the mean flow yields insights into the horizontal transport processes.
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Optics · Cross-listed from quant-ph

High-performance source of indistinguishable polarization-entangled photons with a local oscillator reference for quantum networking

Michael Grayson, Shawn Meyer, Daniel Sorensen et al. (+9 more)

Optical quantum networking protocols impose stringent requirements on the states produced by sources of entanglement. We demonstrate a free-space, compact, source of indistinguishable pairs of polarization entangled photons, with an integrated local oscillator reference as a significant step towards this goal. This source achieves $(99.11 \pm 0.01) \%$ polarization entanglement visibility, $(96.3 \pm 0.6) \%$ successive-photon Hong-Ou-Mandel interference visibility, $(68.0 \pm 0.1$) % heralded efficiency as detected, and $(88.6 \pm 0.2) \%$ interference visibility with a local oscillator. This simultaneous achievement of state-of-the-art metrics demonstrates an adaptable platform for quantum networking.
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All authors Michael Grayson, Shawn Meyer, Daniel Sorensen, Abigail Gookin, Markus Allgaier, Nicholas V. Nardelli, Tara M. Fortier, Dileep V. Reddy, Martin J. Stevens, Michael D. Mazurek, Juliet T. Gopinath, L. Krister Shalm

Computational Physics · Cross-listed from cond-mat.mtrl-sci

Benchmarking of Massively Parallel Phase-Field Codes for Directional Solidification

Jiefu Tian, David Montiel, Kaihua Ji et al. (+4 more)

We present a detailed benchmark comparing two state-of-the-art phase-field implementations for simulating alloy solidification under experimentally relevant conditions. The study investigates the directional solidification of Al-3wt%Cu under high-velocity solidification conditions and SCN-0.46wt% camphor under microgravity conditions from National Aeronautics and Space Administration (NASA) DECLIC-DSI-R experiments. Both codes, one employing finite-difference discretization with uniform mesh and GPU-acceleration (GPU-PF) and the other one employing finite-element discretization with adaptive-mesh and CPU-parallelization (PRISMS-PF), solve the same quantitative phase-field formulation that incorporates an anti-trapping current for the solidification of dilute alloys. We evaluate the predictions of each code for dendritic morphology, primary spacing, and tip dynamics in both 2D and 3D, as well as their numerical convergence and computational performance. While existing benchmark problems have primarily focused on simplified or small-scale simulations, they do not reflect the computational and modeling challenges posed by employing experimentally relevant time and length scales. Our results provide a practical framework for assessing phase-field code performance as well as validating and facilitating their application in integrated computational materials engineering (ICME) workflows that require integration with realistic experimental data.
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All authors Jiefu Tian, David Montiel, Kaihua Ji, Trevor Lyons, Jason Landini, Katsuyo Thornton, Alain Karma

Atmospheric and Oceanic Physics

Insights from Ex-Typhoon Halong (2025) – An Arctic Cyclone of Tropical Origin

Mingshi Yang, Zhuo Wang, John E. Walsh et al. (+3 more)

An Arctic cyclone, Ex-Typhoon Halong, produced strong winds and devastating flooding in southwestern Alaska during 11-12 October 2025. This study examines the evolution of Halong after its transition into an extratropical cyclone through the analysis of ERA5 reanalysis and WRF model simulations. It is found that warm sea surface temperature (SST) anomalies over the western North Pacific preconditioned ex-Halong for intensification by increasing water-vapor content and reducing static stability. Quasi-geostrophic lifting associated with a subsequent interaction with another extratropical cyclone led to the rapid deepening of ex-Halong. This case demonstrates that tropical cyclones can transition into extratropical systems that are intensified by anomalously warm ocean waters, exacerbating impacts in high latitudes. Further analyses indicate that an increasing fraction of Alaskan cyclones has originated in tropical latitudes (south of 30{\deg}N) in recent decades. In particular, the frequency of Arctic cyclones of tropical origin increased by a factor of four in August and by a factor of three in September during 1980-2025 compared with 1940-1979.
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All authors Mingshi Yang, Zhuo Wang, John E. Walsh, James D. Doyle, Richard L. Thoman Jr., Alice K. DuVivier

Fluid Dynamics · Cross-listed from math.NA

Impact of Separation Distance on the Performance and Annual Energy Production of a Dual-Flap Oscillating Surge Wave Energy Converter

Alaa Ahmed

Among the different concepts for wave energy conversion, oscillating surge wave energy converters have been shown to have a high capture width ratio. The primary wave capture structure consists of a flap hinged at the seabed or to a floating platform. Different flap configurations, including single and dual-flap, have been investigated. The separation distance between the oscillating surge wave energy converters can have an impact on their response when deployed in arrays. We consider the case of a dual-flap oscillating surge wave energy converter and investigate the impact of the separation distance between them on the performance of each flap. We estimate the absorbed wave energy and the annual energy production by the two flaps when deployed at the PacWave South site. Inviscid numerical simulations were conducted to predict the response of the oscillating surge wave energy converters. The simulations are validated with experimental measurements of a 1:10 scaled model in a wave tank. The results show that for a short separation distance, the interaction between the oscillating surge wave energy converters has a destructive and constructive effect depending on the wave frequency. However, these effects tend to balance each other out when considering the broad range of wave excitations. For longer separation distances, the interaction always results in a constructive effect. The results reveal that the separation distance has an insignificant impact on annual energy production when considering all wave frequencies and amplitudes.
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Optics

Nonstationary polarization optical forces, considering the influence of dispersion and diffraction

Maria-Gabriela Zheleva, A. Dakova, V. Slavchev et al. (+2 more)

In the present work, the dynamic properties of an attractive longitudinal optical force and the applied potential, due to diffraction and dispersion of ultrashort laser pulses, propagating in air at distances of several diffraction and dispersion lengths, are presented. The results are based on an analytical solution of the linear 3D+1 paraxial amplitude equation and its application to the evolution in time of the longitudinal optical force. The current research provides valuable guidance for the development and creation of neutral particle laser accelerators with potential applications in the field of laser driven nuclear fusion.
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All authors Maria-Gabriela Zheleva, A. Dakova, V. Slavchev, L. Kovachev., D. Dakova

Instrumentation and Detectors

The MUSE Target Chamber Post Veto

R. Ratvasky, T. Rostomyan, M. Ali et al. (+46 more)

The Muon Scattering Experiment (MUSE) was developed to address the proton radius puzzle through simultaneous electron-proton and muon-proton scattering using the Paul Scherrer Institute's PiM1 secondary beamline. MUSE uses a large-solid-angle, non-magnetic spectrometer to detect beam particles scattering from a liquid hydrogen cell contained within a vacuum chamber. Due to the large scattering windows, the structural integrity of the chamber is supported by posts located at small scattering angles. While out of the acceptance, particles in the tails of the beam distribution can strike these posts, causing a significant trigger background. We describe the design and performance of the Target Chamber Post Veto (TCPV) detector installed inside the vacuum chamber to remove these background events at the trigger level.
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All authors R. Ratvasky, T. Rostomyan, M. Ali, H. Atac, F. Barchetti, J. C. Bernauer, W. J. Briscoe, A. Christopher Ndukwe, E. W. Cline, S. Das, K. Deiters, E. J. Downie, Z. Duan, A. Flannery, M. Foster, A. Friebolin, M. Gantert, R. Gilman, A. Golossanov, J. Guo, J. Hirschman, A. Hofer, N. S. Ifat, Y. Ilieva, D. Jayakodige, T. Krahulik, M. Kohl, I. Lavrukhin, W. Lin, W. Lorenzon, P. MohanMurthy, M. Nicol, M. Paolone, T. Patel, A. Prosnyakov, R. D. Ransome, R. Raymond, H. Reid, P. E. Reimer, R. Richards, G. Ron, O. M. Ruimi, K. Salamone, S. Shrestha, N. Sparveris, S. Strauch, N. Wuerfel, D. A. Yaari, C. Zimmerli