Physics and Society · Cross-listed from cs.DL
Consensus and fragmentation in academic publication preferences
Ian Van Buskirk, Marilena Hohmann, Ekaterina Landgren et al. (+3 more)
Academic publishing requires solving a collective coordination problem: among thousands of possible publication venues, which deserve a community's
attention? A clear consensus helps scholars allocate
attention, match submissions to appropriate outlets, and evaluate scholars for hiring and promotion. Yet preferences are not centrally coordinated–they emerge within each field over time. Here we ask whether all fields have arrived at similar solutions to this coordination problem, and whether preferences vary systematically with individual characteristics. Using an adaptive survey of 3,510 US tenure-track faculty yielding 163,002 pairwise comparisons across 8,044 venues, we show that fields occupy a wide spectrum of coordination. Economics, Chemistry, and Physics exhibit strong consensus, with respondents agreeing on elite venues and accurately predicting one another's choices. Computer Science and Engineering show fragmented preferences distributed across hundreds of outlets with minimal overlap. Within fields, preferences correlate with institutional prestige–faculty at elite institutions prefer higher-ranked venues–and with gender, as men prefer higher-ranked venues than women even after accounting for prestige and career stage. Scholars realize their personal preferences more successfully than their respective fields' consensus preferences, indicating that heterogeneity, not just selective hierarchy, shapes publishing outcomes. Journal Impact Factors explain only 64% of preference choices, systematically undervaluing what fields actually prefer. These results quantify how publication preferences vary across the structural diversity of academic fields.
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All authors Ian Van Buskirk, Marilena Hohmann, Ekaterina Landgren, Johan Ugander, Aaron Clauset, Daniel B. Larremore
Fluid Dynamics · Cross-listed from cond-mat.soft
Autophoresis of a Janus particle near a planar wall: a lubrication limit
Tachin Ruangkriengsin, Günther Turk and Howard A. Stone
We study the self-diffusiophoresis of a spherical chemically active particle near a planar, impermeable wall, with a focus on the influence of particle orientation on propulsion. We analyze a Janus particle with asymmetric surface chemical activity, consisting of a small inert region within a catalytically active cap. While numerical simulations have been used to study such particles, they encounter difficulties resolving the flow and transport in the near-wall regime due to
geometric confinement and steep solute concentration gradients. We address this limitation through an asymptotic analysis in the lubrication limit, where the gap between the particle and the wall is narrow. In particular, we consider the distinguished limit in which the inert region is asymptotically comparable in size to the lubrication region. We analyze an axisymmetric configuration in which the inert face is oriented parallel to the wall and extend the analysis to slightly tilted orientations. We find that the cap size determines whether a tilted particle rotates back toward the axisymmetric state or continues to reorient, thereby characterizing its rotational stability in the near-contact regime.
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Applied Physics
Aeroacoustic signatures reveal fast transient dynamics of vapor-jet-driven cavity oscillations in metallic additive manufacturing
Haolin Liu, S. Kiana Naghibzadeh, Zhongshu Ren et al. (+12 more)
Aeroacoustic emissions from intense evaporation are widely measured yet often treated as noisy byproducts and used mainly in empirical monitoring. Here, we show that airborne sound encodes physics-governed sub-millisecond fingerprints of vapor-jet dynamics in excessive vaporization, exemplified by vapor keyholes in
laser metal processing. From first principles, we develop a vapor-jet-cavity oscillation framework and incorporate it into an aeroacoustic formulation, thereby coupling measured sound to transient cavity depth and oscillation frequency. Reconciled with synchronized
multimodal in-situ data, airborne acoustics enable accurate tracking of vapor-cavity properties within tens to hundreds of microseconds. Combined with newly discovered correlations, cavity-jet-acoustic theory recasts the transition from steady, pore-free to pore-shedding vaporizations as a critical-frequency event. Aeroacoustic emissions thus become scalable, physics-guided, and cost-efficient probes of rapidly evolving
liquid-vapor systems.
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All authors Haolin Liu, S. Kiana Naghibzadeh, Zhongshu Ren, Yanming Zhang, Jiayun Shao, Samuel J. Clark, Kamel Fezzaa, Xuzhe Zeng, Lin Gao, Wentao Yan, Noel Walkington, Kaushik Dayal, Tao Sun, Anthony D. Rollett, Levent Burak Kara
Space Physics
Areostationary Satellite Station Keeping Via a Natural Motion Trajectory and Predictive Control
Nathan A. Gall, Robert D. Halverson and Ryan J. Caverly
Areostationary Mars orbit (AMO) satellites will play an important role in future expeditions to the Martian surface due to their strength as
navigation and communication satellites. Perturbative forces experienced by an AMOR satellite will cause it to drift from its nominal orbit, necessitating station keeping. This note presents a novel approach to AMO station keeping that bridges the gap seen in prior predictive control methods between fuel-efficiency and computational-efficiency. The method proposed in this notes involves the discovery and use of a fuel-free natural motion trajectory that maintains the satellite within one degree of longitude from a areostationary orbit. Two of these natural motion trajectories exist as limit cycles about Mars' stable
equilibrium longitudes. They are the resulting motion in the presence of Mars' non-homogeneous gravitational field, accounting for Keplerian and higher-order gravitational perturbations. The proposed MPC policy uses a linear time-varying (LTV) dynamic model that is derived by linearizing the satellite's dynamics relative to the appropriate natural motion trajectory. The result is a station keeping policy that minimizes the fuel consumed, maintains thrust and station-keeping constraints, and is computationally tractable for on-board implementation as a quadratic program.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Competing adsorption of H and CO on Pd-alloy surfaces: Mechanistic insight into the mitigating effect of Cu on CO poisoning
Pernilla Ekborg-Tanner and Paul Erhart
Multi-component
alloys offer broad tunability for addressing challenges in materials science, but their vast configurational space makes their surface chemistry highly sensitive to operating conditions, for example through adsorption and segregation. Here, we study Pd-Au-Cu
alloy surfaces in H$_2$ and CO environments motivated by their use in H technologies, in particular plasmonic H$_2$ sensing, where alloying can mitigate limitations intrinsic to Pd such as hysteresis and CO poisoning. Modeling multicomponent surfaces with multiple adsorbate species under realistic conditions is challenging. To this end, we establish an accurate and efficient framework that combines machine-learned interatomic potentials trained on density functional theory data to generate training data for cluster expansions with effectively no limitations on training set size. By constructing continuous surface phase diagrams for H-CO coadsorption we find that coadsorption under operating conditions is governed primarily by the H coverage during annealing. Au-rich surfaces, formed under H-poor conditions, suppress both CO and H adsorption, while H-rich conditions yield Pd-rich surfaces that maintain higher H coverages compared to Pd at relevant CO partial pressures, indicating improved CO poisoning resistance. This effect is insensitive to relative amounts of Au and Cu, despite experimental evidence of the mitigating effect of specifically Cu on CO poisoning. Kinetic barriers for dilute
alloy surfaces indicate that absorption pathways near Au are highly unfavorable, while Cu leave the energetics unchanged compared to pure Pd. This finding suggests that Cu in the surface region provides viable pathways to shuttle H into the material when Pd-dominated paths are blocked by CO.
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Medical Physics
Data-driven Synthesis of Magnetic Resonance Spectroscopy Data using a Variational Autoencoder
Dennis M.J. van de Sande, Julian P. Merkofer, Sina Amirrajab et al. (+4 more)
The development of deep learning methods for
magnetic resonance spectroscopy (MRS) is often hindered by limited availability of large, high-quality training
datasets. While physics-based simulations are commonly used to mitigate this limitation, accurately modeling all in-vivo signal components remains challenging. In this work, we propose a data-driven framework for synthesizing in-vivo MRS data using a variational autoencoder (VAE) trained exclusively on measured single-voxel spectroscopy data. The model learns a low-dimensional latent representation of complex-valued spectra and enables generation of new samples through latent-space sampling and interpolation. The generative performance of the proposed approach is evaluated using a comprehensive set of complementary analyses, including reconstruction quality, feature-level similarity using low-dimensional
embeddings, application-based signal quality metrics, and metabolite quantification agreement. The results demonstrate that the VAE accurately reconstructs dominant spectral patterns and generates synthetic spectra that occupy the same feature space as in-vivo data. In an example application targeting GABA-edited spectroscopy, augmenting limited subsets of transients with synthetic spectra improves signal quality metrics such as signal-to-noise ratio, linewidth, and shape scores. However, the results also reveal limitations of the generative approach, including under-representation of
stochastic noise and reduced accuracy in absolute metabolite quantification, particularly for applications sensitive to concentration estimates. These findings highlight both potential and limitations of data-driven MRS synthesis. Beyond the proposed model, this study introduces a structured evaluation framework for generative MRS methods, emphasizing the importance of application-aware validation when synthetic data are used for downstream analysis.
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All authors Dennis M.J. van de Sande, Julian P. Merkofer, Sina Amirrajab, Mitko Veta, Gerhard S. Drenthen, Jacobus F.A. Jansen, Marcel Breeuwer
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Deformation mechanisms and compressive response of NbTaTiZr alloy via machine learning potentials
Hongyang Liu, Bo Chen, Rong Chen et al. (+2 more)
Refractory multi-principal element
alloys (MPEAs) are key research focus for excellent high-temp properties and engineering potential. Deformation mechanisms/mechanical behaviors of quaternary NbTaTiZr MPEA under high strain rates/extreme temps remain unclear. We built a variable-composition ML potential for NbTaTiZr, combined with MD simulations to study effects of
crystal orientation, strain rate, temp, composition on compressive mechanics. NbTaTiZr shows structural/mechanical anisotropy in compression [111] max yield strength, [110] min (prone to twinning), [100] via local disorder/dislocation slip (dominant 1/2<111> dislocations). At 10^10 s^-1, yield strength rises sharply, disordered structures increase; high strain rates suppress dislocations to promote disordering. Retains high strength at 2100 K. Higher Nb/Ta boosts yield strength, Ti/Zr reduce it. Reveals MPEA mechanical anisotropy and strain-rate-dependent disordering, guiding high-performance refractory
alloy design.
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All authors Hongyang Liu, Bo Chen, Rong Chen, Dongdong Kang, Jiayu Dai
Geophysics · Cross-listed from gr-qc
Analysis of Tidal Perturbations Due to Asymmetric Response of LARES 2 and LAGEOS
Xizhi Hu, Xiaodong Chen, Jianqiao Xu et al. (+3 more)
Earth
tidal perturbations affecting
laser-ranged satellites are critical for refining satellite orbital dynamics modeling, and their accurate computation represents a prerequisite for high-precision fundamental physical effects and geodetic investigations based on satellite orbit analysis. This study focuses on the
tidal perturbations induced by the asymmetric responses of LARES 2 and LAGEOS on their orbital nodes and inclinations. Perturbations induced by a total of 402 (392 2nd and 10 3rd-order) earth tide constituents on the two satellites were calculated, based on Kaula's orbital perturbation theory and Lagrange's planetary equations for satellites, considering the frequency dependence of Love numbers. The asymmetric characteristics of
tidal perturbations between the two satellites were quantitatively analyzed. The minimum resolutions of orbital inclinations and nodes, used as screening thresholds for significant constituents, were derived from the RMS of overlapping orbit differences using orbital geometry and error propagation law. With these thresholds, 83 significant constituents were identified from the 402. The cumulative effect of the 319 minor constituents was further evaluated, and it was found that their total impact, from coherent superposition, noticeably exceeds the thresholds, thus becoming non-negligible. The results of this study provide accurate
tidal perturbation parameters for LARES 2 and LAGEOS, and offer methodological references for the screening of Earth tide constituents in high-precision satellite orbital dynamics research, laying a foundation for subsequent studies on inverting geophysical parameters from satellite orbits and verifying fundamental physical effects, particularly the relativistic Lense-Thirring effect.
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All authors Xizhi Hu, Xiaodong Chen, Jianqiao Xu, Ignazio Ciufolini, Wei-Tou Ni, Antonio Paolozzi
Chemical Physics · Cross-listed from cond-mat.str-el
General linear correction method for DFT+X energy: application to U-M (M=Al, Ga, In) alloys under high pressure
X. L. Pan, H. X. Song, Y. Sun et al. (+6 more)
DFT+X methods, such as DFT+U and DFT+DMFT, are important supplements to standard density functional theory when strong on-site Coulomb interactions are present. However, the involvement of external parameters in the underlying model
Hamiltonian introduces intrinsic ambiguity when comparing the total energies obtained with different model parameters. This renders DFT+X approaches semi-empirical and severely hinders their capability to describe phase ordering and phase stability, especially when reliable experimental
benchmarks are unavailable, such as under high pressure. In this work, we resolve this longstanding problem by proposing a general linear correction method that eliminates the ambiguous energy contributions introduced by the model
Hamiltonian in DFT+X approaches, thereby enabling direct comparison of their energies calculated with different interaction parameters. The method is demonstrated and validated within the framework of DFT+U, an important member of the DFT+X family. It is then applied to important
nuclear materials of uranium-based binaries U-M (M=Al, Ga, In)
alloys. With this approach, we resolve the long-standing discrepancy between theoretical predictions and experimental observations of phase stability with unprecedented accuracy, and predict several previously unknown stable intermetallic compounds under high pressure. The broad applicability of the method is further confirmed by accurate predictions of formation enthalpies for diverse systems, including Np-Al, U-Si, and Cu-O binaries, the ternary MnSnAu compound, and oxygen adsorption on the Cu(111) surface. This work establishes linear-corrected DFT+U as a fully first-principles approach and validates the linear correction method as a robust and general scheme that can be readily extended to other DFT+X methods.
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All authors X. L. Pan, H. X. Song, Y. Sun, F. C. Wu, H. Wang, Y. F. Wang, Y. Chen, X. R. Chen, Hua Y. Geng
Applied Physics
Broadband multilayer metasurface absorbers with MXene resonators and topology optimized substrates
Maria Thaleia Passia, Yilin Zhao, Haozhe Wang et al. (+1 more)
We present the synthesis of broadband multilayer metamaterial absorbers (MMA) based on MXenes, which are novel two-dimensional conductive materials with higher ohmic losses than copper. MXene resonator of different conductivity can be implemented at each layer or across the same layer, offering increased design flexibility. We examine the possibility of utilizing
topology-optimized stereolithography (SLA) 3D-printed substrates as a complementary means for enhancing absorption. Combining MXenes with
topology optimized 3D-printable structures paves the way for realizing MMAs of enhanced absorption.
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All authors Maria Thaleia Passia, Yilin Zhao, Haozhe Wang, Steven A. Cummer
Chemical Physics · Cross-listed from quant-ph
Exact Semiclassical Dynamics in a Multidimensional Quartic Potential: Multi-Flavor Instantons and Pre-Factor Dominance at Strong Coupling
Pervez Hoodbhoy, M. Haashir Ismail and M. Mufassir
We present an exact semi-classical analysis of a coupled multi-degree-of-freedom
quantum system governed by a symmetric quartic potential with four degenerate minima. Starting from the Euclidean path integral, we identify distinct paths that are longitudinal, transverse, and diagonal, each corresponding to distinct instanton configurations that mediate tunneling between
vacua. The continuous translational zero mode for each coupled trajectory is extracted rigorously by transforming the fluctuation operator into a comoving rotating frame, explicitly incorporating
curvature-induced fictitious forces. By evaluating the exact functional determinants via the Gelfand-Yaglom method and mapping the multi-
flavor dilute instanton gas onto a weighted $K_4$ adjacency
matrix, we analytically derive the transition amplitudes and ground-state energy splittings. Crucially, our exact continuum treatment reveals that for strong coupling, the usual exponential can be overpowered in certain parameter ranges by the "pre-factor". This quantity, which arises from quadratic level fluctuations in the direction transverse to the free direction, turns out to have an essential singularity that would be hard to spot in standard discretized instanton approximations.
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Instrumentation and Detectors
Precise Measurement and Control of Radon Progeny on Detector Surfaces
C.B.Z. Luo, C. Guo, L.P. Xiang et al. (+5 more)
In low-background particle physics experiments, surface deposition of radon progeny presents a significant background challenge. To characterize this contamination, a high-sensitivity surface $\alpha$-activity measurement system was developed, which employs a 3$\times$3 Si-PIN array operating in
vacuum to perform $\alpha$-spectroscopy on samples. The system was calibrated using Poly(Methyl MethAcrylate) (PMMA) plates exposed to a controlled high-radon atmosphere, achieving an energy resolution of 2.09 % for 5.30~MeV $\alpha$ particles and a one-day measurement sensitivity of 1.27~$\mu$Bq/cm$^2$ for $^{210}$Po surface activity. Using this system and a self-built high radon concentration chamber, the deposition behavior of radon progeny on PMMA surfaces was investigated. Results indicate a non-monotonic dependence on exposure time, a significant enhancement of deposition with increasing negative surface electrostatic potential, and a strong modulation by ambient humidity. This paper details the apparatus design, calibration, and experimental study of radon progeny deposition dynamics on PMMA surfaces.
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All authors C.B.Z. Luo, C. Guo, L.P. Xiang, Y.H. Niu, F.G. Mo, J.C. Liu, Y.P. Zhang, C.G. Yang
Applied Physics
Computationally-efficient synthesis of inversely-designed 3D-printable all-dielectric devices
Maria-Thaleia Passia and Steven A. Cummer
We present a systematic, computationally efficient approach for synthesizing 3D-printable all-dielectric devices. Inverse-design optimization methods lead to devices of a continuous dielectric constant profile with complex and conformal shapes. However, stereolithography 3D printers have a limited range of materials; usually, only resin and air are available. As the size and complexity of the devices increase, performing simulations of the entire detailed manufacturable device becomes computationally challenging or even prohibitive. We introduce the LOCABINACONN methodology for transforming an optimized device of a continuous material profile to a manufacturable one while preserving performance as close as possible to the continuous case. The LOCABINACONN is a local and computationally efficient methodology where we identify suitable air/resin configurations that will substitute non-manufacturable material components without simulating the entire manufacturable device. This work paves the way for synthesizing optimized larger-scale 3D-printable devices in a computationally tractable manner.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Retrodictive Forecasting: A Proof-of-Concept for Exploiting Temporal Asymmetry in Time Series Prediction
Cedric Damour
We propose a retrodictive
forecasting paradigm for time series: instead of predicting the future from the past, we identify the future that best explains the observed present via inverse MAP optimization over a Conditional Variational Autoencoder (CVAE). This conditioning is a statistical modeling choice for
Bayesian inversion; it does not assert that future events cause past observations. The approach is theoretically grounded in an information-theoretic arrow-of-time measure: the symmetrized Kullback-Leibler divergence between forward and time-reversed trajectory ensembles provides both the conceptual rationale and an operational GO/NO-GO diagnostic for applicability. We implement the paradigm as MAP inference over an inverse CVAE with a learned RealNVP normalizing-flow prior and evaluate it on six time series cases: four synthetic processes with controlled temporal asymmetry and two ERA5 reanalysis
datasets (wind speed and
solar irradiance). The work makes four contributions: (i) a formal retrodictive inference formulation; (ii) an inverse CVAE architecture; (iii) a model-free irreversibility diagnostic; and (iv) a falsifiable validation protocol with four pre-specified predictions. All pre-specified predictions are empirically supported: the diagnostic correctly classifies all six cases; the learned flow prior improves over an isotropic Gaussian baseline on GO cases; the inverse MAP yields no spurious advantage on time-reversible dynamics; and on irreversible GO cases, it achieves competitive or superior RMSE relative to forward baselines, with a statistically significant 17.7% reduction over a forward MLP on ERA5
solar irradiance. These results provide a structured proof-of-concept that retrodictive
forecasting can constitute a viable alternative to conventional forward prediction when statistical time-irreversibility is present and exploitable.
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Chemical Physics
Designing the Haystack: Programmable Chemical Space for Generative Molecular Discovery
Yuchen Zhu, Donghai Zhao, Yangyang Zhang et al. (+10 more)
Chemical space exploration underlies drug discovery, yet most generative models treat chemical space as a fixed, implicitly learned distribution, focusing on sampling molecules rather than deliberately designing the space itself. We introduce SpaceGFN, a generative framework that elevates chemical space to a programmable computational object: a controllable degree of freedom enabling explicit construction and adaptive traversal of structured molecular universes. SpaceGFN decouples space definition from exploration. Users specify building blocks and reaction rules to construct chemically and synthetically coherent spaces, while a GFlowNet performs efficient, property-biased sampling within them. In Discovery mode, we demonstrate programmable space design through two strategies. A pseudo-natural product space assembles natural product-like architectures. An
evolution-inspired (Evo) space recombines endogenous metabolite fragments via enzyme-consistent transformations, introducing an evolutionary prior into chemical generation. This bias yields favorable shifts in predicted metabolic and toxicological profiles while preserving pharmacological diversity, supported by broad docking enrichment across therapeutic targets. In Editing mode, SpaceGFN enables reaction-consistent lead optimization through a curated toolkit of executable synthetic transformations, allowing local, synthesis-aware modification of existing compounds instead of unrestricted graph mutation. Across 96 drug targets, SpaceGFN achieves strong optimization performance while maintaining structural diversity under synthetic constraints. By integrating programmable chemical universe construction with flow-based exploration and reaction-level editing, SpaceGFN establishes a general paradigm for deliberate
navigation of therapeutic chemical space.
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All authors Yuchen Zhu, Donghai Zhao, Yangyang Zhang, Yitong Li, Xiaorui Wang, Shuwang Li, Yue Kong, Beichen Zhang, Ricki Chen, Chang Liu, Xingcai Zhang, Tingjun Hou, Chang-Yu Hsieh
Optics
Depth-adapted adaptive optics for three-photon microscopy
Qi Hu, Jingyu Wang, Huriye Atilgan et al. (+2 more)
Three-
photon (3-P) fluorescence microscopy enables deep in vivo imaging with subcellular resolution, but its performance is fundamentally constrained by the maximum permissible
laser power required to avoid tissue heating and photodamage. Under these power-limited conditions, fluorescence signal generation, image contrast, and achievable imaging depth are strongly affected by the illumination beam profile and aberration correction strategy. In this paper, we showed that using a fixed illumination beam size was suboptimal across different imaging depths. We further showed that conventional Zernike-based adaptive optics (AO) correction degrades under reduced Gaussian illumination beam sizes due to loss of modal orthogonality. This degradation results in slow convergence, unintended focal and field-of-view shifts, and excessive wavefront deformations. To overcome these limitations, we introduced a depth-adapted AO framework in which both the illumination beam profile and the aberration correction basis were dynamically matched to the imaging conditions. By combining depth-optimised beam underfilling with a bespoke set of illumination-matched aberration modes, we achieved faster and more stable AO convergence, enhanced fluorescence signal and image quality during deep in vivo multi-channel neuroimaging. Together, these results established a practical and robust AO-enabled three-
photon microscopy strategy that maximised imaging performance under realistic power constraints.
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All authors Qi Hu, Jingyu Wang, Huriye Atilgan, Armin Lak, Martin J. Booth
Geophysics
Physics-Based Seismic Hazard and Risk Assessment: A New Paradigm for Earthquake Forecasting
Davide Zaccagnino and Didier Sornette
Epistemic uncertainty in probabilistic seismic hazard assessment (PSHA) is commonly addressed through a logic-tree framework that combines weighted alternative models to characterize the range of plausible hazard outcomes. Implicit in this approach is a critical assumption: that the available model class provides an adequate representation of the underlying physics governing fault networks. Yet current formulations remain highly simplified, neglecting nonlinear interactions, diverse fault slip modes, multi-scale coupling, and the emergent dynamics that govern the nucleation and
evolution of large earthquakes. As a result, the standard treatment of epistemic uncertainty may introduce systematic hazard bias and substantially underestimate forecast uncertainty. To formalize this limitation, we introduce SHARP (Seismic Hazard Assessment and Risks with Physics), a new framework that shifts the focus from selecting among imperfect models to quantifying their collective distance from physical and observational constraints. Central to SHARP is the Model Adequacy Distance (MAD), a quantitative metric of model inadequacy. MAD combines (i) a moment-weighted scoring function scaling with seismic moment to reflect the disproportionate social and economic impact of large events and (ii) compatibility measures derived from geodetic observations and statistical properties of seismicity. We illustrate the approach with an application to the frequency-magnitude distribution of Southern California seismicity. SHARP establishes a rigorous foundation for moving beyond conventional epistemic uncertainty toward a physics-grounded framework for seismic hazard and risk assessment.
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Physics and Society · Cross-listed from q-bio.PE
Modulating biodiversity through higher-order interactions and intraspecific competition in rock-paper-scissors dynamics
Chunpeng Du, Haoshu Wang, Yikang Lu et al. (+2 more)
Understanding the mechanisms that govern species coexistence and biodiversity represents a fundamental challenge in ecology. This study extends the classic rock-paper-scissors model by introducing a context-dependent higher-order interaction mechanism where intraspecific competition is dynamically regulated by local resource availability. Crucially, our quantitative analysis reveals that higher-order interactions significantly modulate the system's structural organization: Enhanced strength of higher-order interactions leads to a decrease in spatial wavelength, resulting in the formation of more compact species domains. However, this structural change makes the system more sensitive to mobility, shifting the extinction threshold to lower values. These findings highlight the dual role of resource-mediated higher-order regulation: it promotes local pattern formation but alters the system's resilience to dispersal, providing new theoretical perspectives for biodiversity conservation.
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All authors Chunpeng Du, Haoshu Wang, Yikang Lu, Lijuan Qin, Junpyo Park
Optics
Polarization Engineering of Second-Harmonic Generation in 3R-MoS$_2$ Waveguides
Renkang Song, Junbo Xu, Yanzhen Yin et al. (+15 more)
Chip-scale nonlinear optics enables strong light-matter interactions within compact devices, serving as a fundamental platform for multifunctional integrated photonics from classical optical signal processing to
quantum information technologies. Transition metal dichalcogenide (TMDC) waveguides have recently emerged as a highly promising platform owing to their
giant material nonlinearity and extended interaction lengths. To date, however, research has predominantly focused on conversion efficiency, leaving the mechanisms governing the polarization state of nonlinear signal largely unexplored. Here, we establish a comprehensive framework for engineering the polarization of second-harmonic generation (SHG) in 3R-MoS$_2$ waveguides. By synergizing polarization-resolved measurements with theoretical modeling, we reveal that the SHG polarization is determined by guided-mode interactions constrained by waveguide geometry and
crystal symmetry, and further reshaped during propagation. We demonstrate that thickness-dependent guided-mode confinement and in-plane
crystal symmetry provide robust, static control over SHG polarization, while propagation length offers a dynamic tuning knob for continuously tailoring the nonlinear output. Our findings provide a deterministic approach for on-chip polarization engineering, opening opportunities for reconfigurable nonlinear light sources and
quantum photonic
circuits.
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All authors Renkang Song, Junbo Xu, Yanzhen Yin, Yu Yin, Xu Jiang, Zhichen Zhao, Lei Zhou, Jintian Lin, Gaozhong Wang, Vasily Kravstov, Kyoung-Duck Park, Ivan Iorsh, Yuerui Lu, Jun Wang, Guangwei Hu, Zhanshan Wang, Di Huang, Tao Jiang
Fluid Dynamics · Cross-listed from quant-ph
A Stable and General Quantum Fractional-Step Lattice Boltzmann Method for Incompressible Flows
Yang Xiao, Liming Yang, Chang Shu et al. (+1 more)
Quantum computing shows substantial potential in accelerating simulations and alleviating
memory bottlenecks in computational fluid dynamics (CFD), owing to its inherent properties of superposition and
entanglement. The
lattice Boltzmann method (LBM), being largely algebraic in nature, has inspired the development of various
quantum LBMs. However, most existing approaches fix the relaxation time at $\tau$ = 1, thereby confining a given mesh resolution to simulations at a single Reynolds number. Although our earlier
quantum lattice kinetic scheme (LKS) lifted this restriction, it suffers from instability at high Reynolds numbers. To address this challenge, we propose a
quantum fractional-step LBM (FS-LBM). In this framework, the predictor step is implemented on a
quantum circuit using the standard LBM formulation, while the corrector step is performed classically. The relaxation time is retained at $\tau$ = 1 to ensure seamless compatibility with existing
quantum LBMs.
Benchmark simulations of representative two- and three-dimensional incompressible isothermal and thermal flows demonstrate that the
quantum FS-LBM achieves accuracy and convergence orders consistent with its classical counterpart, while significantly outperforming the
quantum LKS in both precision and stability. Notably, this work presents the first
quantum LBM simulation of three-dimensional incompressible thermal flows.
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All authors Yang Xiao, Liming Yang, Chang Shu, Yinjie Du
Chemical Physics
Laser-induced, blackbody-radiation-assisted rovibrational cooling of symmetric-top molecular ions: NH3+ and ND3+
Archisman Sinha, Brianna R. Heazlewood and Nabanita Deb
Quantum-state preparation of molecular ions is a prerequisite for precision spectroscopy and controlled studies of cold ion-molecule dynamics. While such control has been extensively developed for diatomic ions and proposed for linear polyatomic ions, corresponding strategies for symmetric-top molecular ions remain largely unexplored. We present a theoretical investigation of blackbody-radiation (BBR)-assisted rovibrational dynamics and
laser cooling in the symmetric-top ions NH3+ and ND3+, prepared in specific ro-vibrational states by resonance enhanced multiphoton ionization (REMPI) of the neutral precursor. State-resolved radiative lifetimes and equilibration times are computed, revealing that vibrationally excited states decay rapidly, while the ground-state redistribution is dominated by slow BBR-driven ro-vibrational transitions as pure rotational transitions are forbidden in the non-polar NH3+ and ND3+ ions. BBR-assisted
laser pumping via the nu2 umbrella-bending mode efficiently cools rotational levels within fixed K
manifolds; however, Delta K = 0 selection rules induce a bottleneck, limiting access to the absolute rovibrational ground state for some initially prepared states. Isotopic substitution to ND3+ further slows dynamics due to reduced transition dipoles. At room temperature, these cooling schemes yield more than 90% and 85% of the population in selected rovibrational states of the NH3+ and ND3+ ions, respectively. In contrast, at temperatures below 100 K, BBR-induced redistribution is strongly suppressed for ions initially produced in the rovibrational ground state (v=0, J, K), effectively freezing the population for extended storage times. In comparison, vibrationally excited states exhibit lifetimes on the order of a few milliseconds, independent of the temperature of the BBR field.
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Fluid Dynamics
Fluid flow in low aspect-ratio curved channels: from small to moderate Dean numbers
Ezzahrae Jaafari, Pascale Magaud and Micheline Abbas
The pressure-driven flow is numerically investigated in curved channels at low aspect ratio, where centrifugal forces act along the largest dimension. The dynamics is studied numerically, as a function of the characteristic Dean number, $\mathrm{De}=\mathrm{Re}\sqrt{\delta}$, by varying independently the Reynolds number $\mathrm{Re}$ and the
curvature ratio $\delta$, the ratio between the hydraulic diameter and the radius of
curvature. A wide range of dimensionless numbers is considered; $\mathrm{De}\lesssim200$ and $0.005\leq\delta\leq0.15$. For $\mathrm{De}\lesssim 100$, the flow remains steady, whereas at larger Dean numbers, the flow is stable for several turns before transient structures developed. While investigating the flow features in the stable regime, only one pair of counter-rotating
vortices is observed. At small $\mathrm{De}$ and large $\delta$, the peak of the streamwise velocity and the center of the
vortices are located near the inner channel wall. They both shift toward the outer wall as $\mathrm{De}$ is increased and/or $\delta$ is decreased, a feature that is expected to affect the transport of particles in curved channels. A scaling law for the secondary flow is formulated from dimensional analysis, rather than relying on empirical correlations. The friction coefficient of the flow as well as the development angle are also rationalized in terms of both $\mathrm{Re}$ and $\delta$.
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Fluid Dynamics
Control and synchronization of capillary flows in stepped microchannels
Harsha Desu, Niladri S. Satpathi, Lokesh Malik et al. (+1 more)
Capillary-driven transport offers a simple, self-sustained alternative to externally pumped microfluidic systems, yet achieving precise control of such flows remains challenging. We experimentally and theoretically investigate capillary flow in rectangular microchannels when a
liquid meniscus encounters a
geometric step with varying channel width and height. Depending on the contact angle and step dimensions, the meniscus either pins or advances, defining distinct flow and no-flow regimes. Introducing a lateral offset between channel sidewalls provides an additional
geometric control that enables reversible switching from a pinned to a flowing state, even for
liquids with relatively high contact angles. We rationalize these transitions using numerical simulations and an energy-based scaling model that captures the balance between surface tension and Laplace pressure at the step. Finally, we demonstrate synchronization of capillary fronts in parallel microchannels by combining stepped and offset geometries. These results establish a simple, geometry-mediated mechanism for passive control and synchronization of capillary flows, expanding the design space for microfluidic systems.
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All authors Harsha Desu, Niladri S. Satpathi, Lokesh Malik, Ashis K. Sen
Optics
Observation of Chiral Bound States in the Continuum in Self-biased Magneto-optical Photonic Crystals
Maohua Gong, Qiutong Zhen, Yujie Tang et al. (+5 more)
Chiral bound states in the continuum (BICs) are confined photonic modes with infinite quality factors and
chiral response, offering significant potential for
chiral optics. Although a novel type of
spin-orbital-locking
chiral BIC was recently predicted in magneto-optical (MO) photonic
crystals (PhCs) that break time-reversal
symmetry (TRS), its experimental realization has remained elusive. Here, we report the first experimental observation of such
chiral BICs in self-biased MO PhCs, which operate without external
magnetic fields. Moreover, we experimentally demonstrate that the chirality and the surrounding near-circular polarization of these
chiral BICs can be switched simply by reversing the remanent magnetization, without any structural changes. Unlike conventional
chiral BICs that preserve TRS, these magnetically induced
chiral BICs exhibit exceptional robustness against structural imperfections and perturbations. This work represents a significant advancement in the topological photonics of
chiral BICs, opening new pathways toward robust
chiral optical devices.
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All authors Maohua Gong, Qiutong Zhen, Yujie Tang, Peng Hu, Qing-An Tu, Yan Meng, Peiheng Zhou, Zhen Gao
Biological Physics · Cross-listed from q-bio.PE
Hostility prevents the tragedy of the commons in metapopulation with asymmetric migration: A lesson from queenless ants
Joy Das Bairagya and Sagar Chakraborty
A colony of the queenless ant species, Pristomyrmex punctatus, can broadly be seen as consisting of small-body sized worker ants and relatively larger body-sized cheater ants. Hence, in the presence of inter-colony migration, a set of constituent colonies act as a metapopulation exclusively composed of cooperators and defectors. Such a set-up facilitates an evolutionary game-theoretic replication-selection model of population dynamics of the ants in a metapopulation. Using the model, we analytically probe the effects of territoriality induced hostility. Such hostility in the ant-metapopulation proves to be crucial in preventing the tragedy of the commons, specifically, the workforce, a social good formed by cooperation. This mechanism applies to any metapopulation – not necessarily the ants – composed of cooperators and defectors where inter-population migration occurs asymmetrically, i.e., cooperators and defectors migrate at different rates. Furthermore, our model validates that there is evolutionary benefit behind the queenless ants' behavior of showing more hostility towards the immigrants from nearby colonies than those from the far-off ones. In order to calibrate our model's parameters, we have extensively used the data available on the queenless ant species, Pristomyrmex punctatus
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Atomic Physics
A compact vapor-cell optical frequency reference with fractional frequency instability around $10^{-16}$
Siqi Wu, Zhenqi Zhang, Xingyue Liu et al. (+12 more)
Compact optical frequency reference with high stability is essential for field applications such as
navigation and geodesy, yet vapor
cell systems have remained confined to fractional instabilities over $10^{-15}$. Here, we report a molecular iodine reference that reaches an instability of $7 \times 10^{-16}$ at 1000 s and operates at the $10^{-16}$ level from 200 to 2000 s, surpassing the best reported vapor
cell standards by approximately a factor of three. This achievement is enabled by a monolithic, drift immune spectroscopic unit bonded to an ultra low expansion glass substrate with precision control of key parameters.The entire system occupies only 25 L.The system achieves $5 \times 10^{-15}$ instability at 1 s and reaches the $10^{-16}$ level over the 200 to 2000 s averaging-time range, representing the first medium term stability at the $10^{-16}$ level from a compact, field ready vapor-
cell reference. Our work demonstrates that $10^{-16}$ instability can be engineered into portable systems, opening a path to high precision time-keeping beyond the laboratory.
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All authors Siqi Wu, Zhenqi Zhang, Xingyue Liu, Chuanshuai Zhu, Zhiyuan Wang, Zhiyu Ma, Hongli Liu, Wenhao Yuan, Xiaochi Liu, Pengfei Wang, Feng Zhao, Jan Hrabina, Jie Zhang, Zehuang Lu, Ke Deng
Optics · Cross-listed from cs.LG
Exact and Asymptotically Complete Robust Verifications of Neural Networks via Ising Solvers
Wenxin Li, Wenchao Liu, Anzhe Jiang et al. (+6 more)
We present an Ising-compatible framework for formal neural-network robustness verification under bounded input perturbations. For piecewise activations (both continuous piecewise-linear and discrete piecewise-constant), the Exact Logarithmic Piecewise Model (Log-PW) provides an exact, sound, and complete formulation with a state-optimal logarithmic encoding, reducing the binary variables per
neuron from linear $O(\kappa)$ to information-theoretically minimal logarithmic complexity $O(\lceil \log_2 \kappa \rceil)$ via logarithmic SOS2 (Log-PWL) and SOS1 (Log-PWC) constraints. For general element-wise activations, the Asymptotic Step-Envelope Model (Step-Env) leverages Log-PWC to construct sound, refinable endpoint enclosures. An exact monotonic reduction based on Jordan decomposition further extends this framework to arbitrary non-monotonic activations. We further develop a hybrid Benders solver with output-sensitive iteration bounds, leveraging a Helly-based conflict compression theory to avoid generic exponential cut explosion. In particular, for shallow networks with fixed input dimension, this establishes an unconditionally
polynomial Benders iteration complexity in network size. Interval
pruning, certificate transfer for pruned networks, and layerwise classical–Ising partitioning further reduce
spin requirements. Experiments demonstrate exact certification fidelity for piecewise-linear networks and near-reference accuracy for non-linear activations under compact
spin budgets. On MNIST
benchmarks, Log-PW halves binary decision
spins over One-Hot formulations, while Helly-based cuts achieve up to a $13.41\times$ speedup and an $87.6\%$ reduction in master queries over standard baselines.
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All authors Wenxin Li, Wenchao Liu, Anzhe Jiang, Weihao Li, Chuan Wang, Qi Gao, Yin Ma, Hai Wei, Kai Wen
Fluid Dynamics
Spatial instability analysis and mode transition of a viscoelastic jet in a co-flowing gas stream
Jiawei Li, Ming Wang, Kai Mu et al. (+2 more)
Spatial linear instability analysis is employed to investigate the instability of a viscoelastic
liquid jet in a co-flowing gas stream. The theoretical model incorporates a non-uniform axial base profile represented by a
hyperbolic tangent, capturing the shear layer. The Oldroyd-B model discretized with Chebyshev
polynomials is employed, and energy budget analysis is used to interpret underlying mechanisms.At low Weber numbers, the jet evolves axisymmetrically and the instability is governed by interfacial gas-pressure fluctuations; as the Weber number increases, the growing inertia drives a transition of the predominant mode from axisymmetric to helical. At weak elasticity, the instability is also primarily governed by gas-pressure fluctuations. As elasticity increases, the predominant mode transitions from axisymmetric to helical. This transition is accompanied by a migration of disturbance structures from the interface toward the jet interior and an enhanced coupling between velocity perturbation and the basic flow. These trends reveal a new predominant instability mechanism – the elasticity-enhanced shear-driven instability – which is distinct from capillary or Kelvin-Helmholtz instabilities in Newtonian jets. A We-El phase diagram delineates the boundary between predominant modes, and experimental results obtained in a flow-focusing configuration validate the theoretical predictions.
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All authors Jiawei Li, Ming Wang, Kai Mu, Zhaodong Ding, Ting Si
Atomic Physics · Cross-listed from quant-ph
Low-entropy arrays of microwave-shielded molecules prepared by interaction blockade
Tijs Karman, Sebastian Will and Zoe Yan
Ultracold molecules are becoming an increasingly important technology for
quantum simulation, computation, and sensing, but their state preparation in large, low-
entropy arrays remains a key challenge. We propose to deterministically load single molecules into optical tweezer arrays or
lattices from either thermal or degenerate gases, with a high probability of occupying the tweezer's motional ground state. Strong repulsion between microwave-shielded molecules prevents multiparticle occupancy. Our proposal represents a robust scheme for deterministic single molecule preparation directly in the motional ground state with expected fidelities exceeding 99 percent for small trap volumes and highly polar species. This method can be scaled to thousands of traps limited by the reservoir molecule number, opening the door to large, low-
entropy polar molecule arrays for
quantum computation,
quantum simulation, and precision measurement.
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Geophysics
Dual-space posterior sampling for Bayesian inference in constrained inverse problems
Ali Siahkoohi, Kamal Aghazade and Ali Gholami
Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniqueness. A prominent example is full waveform inversion (FWI), which estimates Earth's subsurface properties by fitting seismic measurements subject to the wave equation, where ill-conditioning stems from noisy, band-limited, finite-aperture measurements and complex geological structures. A
Bayesian framework describes the solution more comprehensively: instead of a single estimate, a posterior distribution of plausible solutions characterizes the non-uniqueness and can be sampled to quantify uncertainty. However, no clear procedure exists for translating hard physical constraints, such as the wave equation, into priors amenable to existing sampling techniques. We address this by sampling the posterior in the dual space via an augmented Lagrangian formulation, which converts hard constraints into penalties suited to sampling
algorithms while enforcing them progressively through multiplier updates, so they are satisfied in the limit. We integrate the alternating direction method of multipliers (ADMM) with Stein variational gradient descent (SVGD), a particle-based sampler: the constraint is relaxed at each iteration and the multiplier updates progressively enforce its satisfaction. This enables posterior sampling under hard constraints while inheriting the favorable conditioning of dual-space solvers, where partial constraint relaxation permits productive updates even when the current model is far from the true solution. We validate the method on a stylized Rosenbrock conditional inference problem and on frequency-domain FWI for a Gaussian anomaly model and the Marmousi II
benchmark, demonstrating physically consistent uncertainty estimates and posterior contraction with increasing data coverage.
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