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Physics Physics

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Friday 14 November

Fluid Dynamics · Cross-listed from cond-mat.soft

Emergent Synchronization and Defect Dynamics in Confined Chiral Active Suspensions

Zaiyi Shen, Leilei Wang, Shishuang Zhang et al. (+4 more)

Hydrodynamic interactions can generate rich emergent structures in active matter systems. Using large-scale hydrodynamic simulations, we demonstrate that hydrodynamic coupling alone can drive spontaneous self-organization across a hierarchy of spatial and temporal scales in confined suspensions of torque-driven particles at moderate Reynolds numbers. Spinners first self-assemble into dimers, which crystallize into a hexatic lattice and subsequently undergo a collective tilting instability. The resulting tilted dimers rotate and synchronize through hydrodynamic repulsion, which can be tuned by the Reynolds number. Upon synchronization, the polar director develops splay and bend deformations and nucleates topological defects with charges of $\pm1$. These defects induce long-wavelength concentration gradients and drive crystal vortex dynamics spanning hundreds of particle diameters. Our results reveal a purely hydrodynamic route to synchronization and defect-mediated dynamics in chiral active matter, without explicit alignment rules or interparticle forces.
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All authors Zaiyi Shen, Leilei Wang, Shishuang Zhang, Chenlu Li, Kaili Xie, Xu Zheng, Juho S. Lintuvuori

Atomic Physics

Characterizing resonances in positron-sodium scattering

Ning-Ning Gao, Hui-Li Han, Ting-Yun Shi et al. (+1 more)

We investigate resonances in positron-sodium scattering using the $R$-matrix propagation method formulated in hyperspherical coordinates. The interaction between the sodium core and the valence electron is described by analytical model potentials. High partial-wave resonances are calculated for collision energies up to the Na($4f$) threshold. Several resonant states of debated character are identified, and their behavior is analyzed through phase-variation studies, the associated structures in the calculated cross sections, and the characteristic patterns observed in the stability plots. The calculated dipole series of resonances, supported by the ion-dipole interaction between Na$^{\scriptscriptstyle+}$ and Ps($n=2$), shows good agreement with recent complex-scaling calculations. In addition, a sequence of quasi-dipole resonances is found to arise from the near degeneracy of the Na($4d$) and Na($4f$) states in the e$^{+}$-Na system, which accumulate geometrically toward the Na($4d$) threshold.
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All authors Ning-Ning Gao, Hui-Li Han, Ting-Yun Shi, Li-Yan Tang

Biological Physics

Advanced Data Analysis of Spontaneous Biophoton Emission: A Multi-Method Approach

M. Benfatto, L. De Paolis, L. Tonello et al. (+1 more)

Ultra-weak photon emission (UPE) from living systems is widely hypothesized to reflect un-derlying self-organization and long-range coordination in biological dynamics. However, distin-guishing biologically driven correlations from trivial stochastic or instrumental effects requires a robust, multi-method framework. In this work, we establish and benchmark a comprehensive anal-ysis pipeline for photon-count time series, combining Distribution Entropy Analysis, Rényi entro-py, Detrended Fluctuation Analysis, its generalization Multifractal Detrended Fluctuation Analysis, and tail-statistics characterization. Surrogate signals constructed from Poisson processes, Fractional Gaussian Noise, and Renewal Processes with power-law waiting times are used to validate sensitivity to memory, intermittency, and multifractality. Across all methods, a coherent hierarchy of dynamical regimes is recovered, demonstrating internal methodological consistency. Application to experimental dark-count data and attenuated coherent-laser emission confirm Poisson-like behavior, establishing an essential statistical baseline for UPE studies. The combined results show that this multi-resolution approach reliably separates trivial photon-counting statistics from struc-tured long-range organization, providing a validated methodological foundation for future biological UPE measurements and their interpretation in the context of non-equilibrium statistical physics, information dynamics, and prospective markers of biological coherence.
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All authors M. Benfatto, L. De Paolis, L. Tonello, P. Grigolini

Chemical Physics

Van-der-Waals exchange-correlation functionals and their high pressure and warm dense matter applications

Jan Vorberger, Gabriel J. Smith, William Z. Van Benschoten et al. (+4 more)

We investigate basic hydrogen quantities like the molecular bond length, the molecular dissociation energy and the van-der-Waals interaction in idealized situations in an effort to discern a suitable exchange-correlation functional for the molecular to metal transition in warm dense hydrogen. The best reproduction of bond length and dissociation energy is given by the r2SCAN functional, several vdW functionals and also HSE06 fair qualitatively and quantitatively no better than PBE or worse. In addition we investigate quantities like the static and dynamic ion structure factor, and the electronic DOS to determine differences between exchange-correlation functionals with and without van-der-Waals corrections in the transition region from the molecular to the metallic regime of hydrogen.
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All authors Jan Vorberger, Gabriel J. Smith, William Z. Van Benschoten, Hayley R. Petras, Zhandos Moldabekov, Tobias Dornheim, James J. Shepherd

Instrumentation and Detectors · Cross-listed from astro-ph.HE

Measurement of cosmic-ray muon flux at CJPL-II

P. Zhang, H. Ma, W. Dai et al. (+5 more)

In China Jinping Underground Laboratory (CJPL), the deepest and largest underground laboratory globally, the cosmic-ray muon flux is significantly reduced due to the substantial shielding provided by the overlying mountain. From 2016 to 2020, we measured the muon flux in the second phase of CJPL (CJPL-II) with a plastic scintillator muon telescope system, detecting 161 muon events over an effective live time of 1098 days. The detection efficiency was obtained by simulating the underground muon energy and angular distributions and the telescope system's response to underground muons. The cosmic-ray muon flux is determined to be (3.03 $\pm$ 0.24 (stat) $\pm$ 0.18 (sys)) $\times$ 10$^{-10}$ cm$^{-2}$s$^{-1}$, which is the lowest among underground laboratories worldwide.
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All authors P. Zhang, H. Ma, W. Dai, M. Jing, L. Yang, Q. Yue, Z. Zeng, J.Cheng

Optics · Cross-listed from astro-ph.IM

Surface figure metrology for reflective membrane mirrors based on phase-measuring deflectometry

Xin Yan, Zhi-Kang Zhuang, Fu-Jia Du et al. (+4 more)

Reflective membrane mirrors provide a lightweight, low-cost alternative to traditional optics for next-generation large-aperture telescopes, but their non-rigid, thin structure poses challenges for surface metrology. We present a phase-measuring deflectometry (PMD) system enhanced with tailored ray-tracing and iterative reconstruction to enable non-contact measurement of large membrane optics. The system successfully characterizes the surface figure and evaluates the dynamic stability of a 1-meter Hencky-type membrane mirror. Our results demonstrate the effectiveness of PMD as a practical metrology tool for future membrane-based telescope systems.
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All authors Xin Yan, Zhi-Kang Zhuang, Fu-Jia Du, Wen Duan, Peilin Yin, Mo-Nong Yu, Guang Yang

Instrumentation and Detectors

In-situ environmental radiation background measurement in the second phase of CJPL

P. Zhang, Z. Zeng, J. Cheng et al. (+1 more)

China Jinping Underground Laboratory (CJPL), the deepest and largest underground laboratory worldwide, provides a low radiation background environment, which is necessary to frontier scientific research, such as the experimental studies of rare-event physics. Due to the almost filled space of CJPL-I and the requirement of future physics experiments, the construction of the second phase of CJPL (CJPL-II) was started in 2020 and all finished in 2024. In this work, we report the measured results of major environmental radiation in CJPL-II, including cosmic-ray muons, radon, gamma rays, and neutrons. Results indicate that the rock overburden and the radioactive background control effectively minimize the environmental radiation background. The scientific data presented also serve as an important basis to detector background modeling for the physics experiments in CJPL-II.
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All authors P. Zhang, Z. Zeng, J. Cheng, H. Ma

Optics · Cross-listed from quant-ph

Memory-Assisted Nonlocal Interferometer Towards Long-Baseline Telescopes

Bin Wang, Xi-Yu Luo, Bo-Feng Gao et al. (+12 more)

Quantum networks and remote quantum entanglement serve as vital future quantum communication resources with broad applicability. A key direction lies in extending the baseline of optical interferometers to enhance angular resolution in interferometric imaging. Here, by measuring a simulated thermal light field, we report the demonstration of a memory-assisted nonlocal interferometer achieving a fiber-link baseline up to 20 km while simultaneously showing its capability to compensate for a geometric delay equivalent to 1.5 km. This result demonstrates potential for enhancing the angular resolution of interferometric imaging in the optical band with delocalized single-photon entanglement, and paves the way for future application of quantum memories in astronomical observation.
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All authors Bin Wang, Xi-Yu Luo, Bo-Feng Gao, Jian-Long Liu, Chao-Yang Wang, Zi Yan, Qiao-Mu Ke, Da Teng, Ming-Yang Zheng, Yuan Cao, Jun Li, Cheng-Zhi Peng, Qiang Zhang, Xiao-Hui Bao, Jian-Wei Pan

Optics · Cross-listed from quant-ph

Towards Global Quantum Key Distribution

Haoran Zhang, Haotao Zhu, Ruihua He et al. (+4 more)

Quantum Key Distribution (QKD) supports the negotiation and sharing of private keys with unconditional security between authorized parties. Over the years, theoretical advances and experimental demonstrations have successfully transitioned QKD from laboratory research to commercial applications. As QKD expands its reach globally, it encounters challenges such as performance limitations, cost, and practical security concerns. Nonetheless, innovations in satellite-based QKD and the development of new protocols are paving the way towards a worldwide network. In this review, we provide an overview of QKD implementations, with a focus on protocols, devices, and quantum channels. We discuss the challenges of practical QKD and explore long-haul QKD. Additionally, we highlight the future research directions that are expected to significantly advance the realization of a global QKD network.
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All authors Haoran Zhang, Haotao Zhu, Ruihua He, Yan Zhang, Chao Ding, Lajos Hanzo, Weibo Gao

Plasma Physics

Studies of laser stimulated photodetachment from nanoparticles for particle charge measurements

Y.A. Ussenov, M. N. Shneider, S. Yatom et al. (+1 more)

Determining nanoparticle charge is more challenging than that for microparticles due to change in the particle size during the synthesis substantial plasma property variations, and difficulties in visualizing individual particles, rendering conventional microparticle charge diagnostics ineffective in dusty plasma. In this work, we utilized laser-stimulated photodetachment (LSPD) to deduce the mean charge of nanoparticles. Nanoparticles were grown in an Ar and C2H2 mixture using a capacitively coupled RF discharge and the LSPD induced changes in the electron current monitored by a cylindrical Langmuir probe. LSPD signals were obtained and analyzed across different dust growth phases. The prolonged decay of electron current pulses was attributed to the presence of residual negative ions, caused by the effective electrostatic trapping of these ions and the potential post - LSPD re-formation of new ones. The particle charge was estimated by combining the laser-stimulated photodetachment signal from the probe with the dust density obtained from laser-light extinction using the measured nanoparticle size distribution. For a nanoparticles size range of approximately 100_-_250 nm and mean diameter of Dp ~154.37 nm, the effective mean charge was estimated to be Qd ~37 elementary charge units. The measured charge values are lower than those predicted by orbital motion limited (OML) theory, which may be attributed to significant electron depletion in the nanodusty plasma. LSPD results in Ar and C2H2 nano-dusty plasma confirm the applicability of this method for estimating individual nanoparticle charges. However, it has also been demonstrated that electron detachment from residual background negative ions can influence the detachment current decay and must be carefully considered.
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All authors Y.A. Ussenov, M. N. Shneider, S. Yatom, Y. Raitses

Plasma Physics

Decomposition of Methane Diluted with Inert Gas in an RF Discharge Cell

Sophia Gershman, Mikhail N. Shneider and Yevgeny Raitses

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2 to 3 torr. The discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with 5 percent or less CH4. The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH4 remained diffuse. A 0-D model for Ar/CH4 discharge established a threshold for contraction while also asserting the importance of Ar metastable in the dissociation and ionization processes. The highest degree of methane decomposition, 99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with 5% or less CH4. We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.
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Optics

Nanoscale Femtosecond Coherent Radiation and Spatiotemporally Shaped free electron Wavefunction

Wu Wen, Jing Li and Yunquan Liu

We study tunable nanoscale femtosecond coherent radiation based on a coupled nanowire pair (CNP) structure that is excited by a strong laser. The structure functions as a nanoscale undulator (NU): the electrons moving through the nanogap are driven by a spatially periodic, transverse optical near-field. We show that the transverse near-field can actively shape the electron wavefunction by inducing both a periodic oscillation and a quantum squeezing of its width. We then validate this theoretical framework by numerically solving the relativistically corrected time-dependent Schrödinger equation (RC-TDSE). The generated femtosecond pulse trains can be spectrally, temporally, and spatially controlled. This framework establishes the transverse optical near-field interaction as a novel mechanism to spatiotemporally shape electron wavefunctions, which illuminates a path to versatile platform for on-chip femtosecond coherent light source and the application in free-electron quantum optics.
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Fluid Dynamics

Subgrid Stress Modelling with Multi-dimensional State Space Sequence Models

Andy Wu and Sanjiva K. Lele

Large Eddy Simulations (LES) are becoming increasingly viable due to the growth in computational power the last few decades, and subgrid stress modelling plays a large role in the accuracy of LES. A new class of neural network models, S4 and S4ND models, allow for learning a continuous representation of the discrete dataset, which facilitates a principled approach to incorporating grid dependence in neural network subgrid stress modelling. A S4ND Unet neural network architecture is proposed and trained on both forced Homogeneous Isotropic Turbulence (HIT) and channel flow, where a priori, it is shown to generalize to grid spacings that are coarser than the training set grid spacings, while simpler artificial neural network (ANN) models fail. A posteriori tests on both forced HIT and channel flow indicate that the S4ND model is more accurate than traditional models and ANN-based models on grid sizes that are in the training set. The S4ND model is also able to generalize to grid sizes that are coarser than the training set a posteriori, and is more accurate than many traditional and neural network subgrid stress models. Finally, the proposed model is also evaluated on flows at increasing Reynolds numbers, where it is seen that the proposed neural network remains stable even at a Reynolds number that is 500,000 times that seen in the training set.
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Plasma Physics · Cross-listed from astro-ph.SR

In situ Evidence of 5-minute Oscillations from Parker Solar Probe

Zesen Huang, Marco Velli, Olga Panasenco et al. (+19 more)

The Sun's surface vibrates in characteristic 5-minute oscillations, known as p-modes, generated by sound waves trapped within the convection zone. Although these oscillations have long been hypothesized to reach into the solar wind, direct in situ evidence has remained elusive, even during previous close encounters by Parker Solar Probe (PSP). Here, we present the first promising in situ detection of 5-minute oscillations in the upper solar corona, based on observations from PSP's three closest perihelia. In two events at 9.9 solar radii, we identify statistically significant ($\sim$ 6 $\sigma$) 3.1-3.2 mHz peaks in the magnetic field power spectrum, each appearing as a large-amplitude, spherically polarized Alfvénic wave train lasting approximately 35 minutes. These results demonstrate that global solar oscillations can reach and potentially influence the solar wind.
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All authors Zesen Huang, Marco Velli, Olga Panasenco, Richard J. Morton, Chen Shi, Yeimy J. Rivera, Benjamin Chandran, Samuel T. Badman, Yuliang Ding, Nour Raouafi, Stuart D. Bale, Michael Stevens, Tamar Ervin, Chuanpeng Hou, Kristopher G. Klein, Orlando Romeo, Jia Huang, Mingzhe Liu, Davin E. Larson, Marc Pulupa, Roberto Livi, Federico Fraschetti

Fluid Dynamics

Stability of SQG Kolmogorov Flow

Mac Lee and Stefan Llewellyn Smith

Stability analysis is performed on surface quasigeostrophic systems subjected to a Kolmogorov-type "shear force" on the boundaries using linear and nonlinear approaches. For a SQG system of semi-infinite depth forced on the upper boundary, the most linearly unstable mode is 2.74 the energy injection length scale. This is contrary to two-dimensional fluid systems, where the linear instability is greatest for long waves. In the presence of damping, the most linearly unstable mode shifts toward shorter length scales. The nonlinear critical Reynolds number across different damping strengths is found to be qualitatively similar to that of Euler 2D systems. For an SQG system of finite thickness being forced on both boundaries, its behaviour approaches that of a semi-infinite SQG system at the large thickness limit. In the small thickness limit, the behaviour of a symmetrically forced fluid layer approaches that of a 2D system, while an antisymmetrically forced fluid layer is not susceptible to both linear and nonlinear instabilities. With ageostrophic effects, an SQG+ system of semi-infinite depth is much more prone to instabilities than an otherwise identical SQG system in the absence of damping due to the instability of long-wave modes. However, damping significantly suppresses such instabilities. With increasing damping, the most linearly unstable mode moves toward a smaller length scale. Contrary to the zero damping case, when the damping is sufficiently large, ageostrophic effects have a small but measurable stabilising effect.
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Plasma Physics

Bremsstrahlung constraints on proton-Boron 11 inertial fusion

I. E. Ochs, E. J. Kolmes, A.S. Glasser et al. (+1 more)

Proton-Boron 11 (pB11) fusion is relatively safe and clean, but difficult to use for net power production, since bremsstrahlung radiation tends to radiate away power more quickly than it can be generated by fusion power, particularly once poisoning by alpha particles is taken into account. While in magnetic confinement fusion (MCF), this problem can be addressed by deconfining the alphas, in inertial confinement fusion (ICF) the alphas that heat the plasma linger for the duration of the reaction. Thus, it becomes essential to trap the bremsstrahlung radiation in the hotspot. Through burn simulations incorporating bremsstrahlung emission and reabsorption, we infer the necessary conditions to capture enough radiation to produce scientific breakeven in a pB11 ICF plasma. We find that breakeven requires a stagnation areal density roughly two orders of magnitude higher than the current state-of-the-art, at pressures three orders of magnitude higher.
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All authors I. E. Ochs, E. J. Kolmes, A.S. Glasser, N. J. Fisch

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

Lead-Free Europium Halide Perovskite Nanoplatelets

Sebastian Fernández, Divine Mbachu, Manchen Hu et al. (+9 more)

Metal halide perovskites possess desirable optical, material, and electrical properties which have had substantial impact on next-generation optoelectronics. However, given the toxicity of lead, alternative lead-free perovskite semiconductors are needed. By fully replacing lead with rare-earth elements, one can simultaneously address toxicity concerns and achieve comparable optoelectronic performance. Here, we demonstrate the synthesis of two-dimensional europium halide perovskite nanoplatelets governed by the formula $\mathrm{L_{2}EuX_{4}}$ where L is an organic ligand and X is a halide anion. The structure, morphology, and composition of the nanoplatelets are confirmed by XRD, AFM, and XPS. Deep blue-emitting $\mathrm{PEA_{2}EuBr_{4}}$ perovskite nanoplatelets are synthesized in both the solution- and solid-states with photoluminescence emission centered at 446 nm and CIE color coordinates of (0.1515, 0.0327) and (0.1515, 0.0342), respectively. Additionally, near-ultraviolet $\mathrm{PEA_{2}EuCl_{4}}$ perovskite nanoplatelets are synthesized in both the solution- and solid-states with photoluminescence emission centered at 400 nm and 401 nm, respectively. Overall, europium halide perovskite nanoplatelets offer a lead-free alternative for deep blue, violet, and near-ultraviolet light emission $\unicode{x2013}$ charting new pathways for optoelectronics in this energy regime.
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All authors Sebastian Fernández, Divine Mbachu, Manchen Hu, Han Cui, William Michaels, Pournima Narayanan, Tyler K. Colenbrander, Qi Zhou, Da Lin, Ona Segura Lecina, Guosong Hong, Daniel N. Congreve

Thursday 13 November

Physics Education

gr-Orbit-Toolkit: A Python-Based Software for Simulating and Visualizing Relativistic Orbits

Milagros Delgado and Wladimir E. Banda-Barragán

Creating software dedicated to simulation is essential for teaching and research in Science, Technology, Engineering, and Mathematics (STEM). Physics lecturing can be more effective when digital twins are used to accompany theory classes. Research in physics has greatly benefited from the advent of modern, high-level programming languages, which facilitate the implementation of user-friendly code. Here, we report our own Python-based software, the gr-orbit-toolkit, to simulate orbits in classical and general relativistic scenarios. First, we present the ordinary differential equations (ODEs) for classical and relativistic orbital accelerations. For the latter, we follow a post-Newtonian approach. Second, we describe our algorithm, which numerically integrates these ODEs to simulate the orbits of small-sized objects orbiting around massive bodies by using Euler and Runge-Kutta methods. Then, we study a set of sample two-body models with either the Sun or a black hole in the center. Our simulations confirm that the orbital motions predicted by classical and relativistic ODEs drastically differ for bodies near the Schwarzschild radius of the central massive body. Classical mechanics explains the orbital motion of objects far away from a central massive body, but general relativity is required to study objects moving at close proximity to a massive body, where the gravitational field is strong. Our study on objects with different eccentricities confirms that our code captures relativistic orbital precession. Our convergence analysis shows the toolkit is numerically robust. Our gr-orbit-toolkit aims at facilitating teaching and research in general relativity, so a comprehensive user and developer guide is provided in the public code repository.
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2511.19442 · 13 Nov · Author's accepted manuscript of a chapter published in Information and Communication Technologies (TICEC 2025 Proceedings), Communications in Computer and Information Science, vol. 2707, Springer Nature Switzerland AG, 2026. The final authenticated version is available at: https://doi.org/10.1007/978-3-032-08366-1_20 15 pages, 4 figures

Abstract PDF $ALGO ×1$LANG ×1

Instrumentation and Detectors

PlatonSPAD: A novel SPAD sensor for large-scale high-resolution particle detectors

Kodai Kaneyasu, Till Dieminger, Matthew Franks et al. (+3 more)

High-resolution 3D tracking with sub-nanosecond timing is required for the detection of elementary particles, such as neutrinos. Conventional detectors, which utilize analog silicon photomultipliers, face challenges in balancing spatial resolution and scalability. To address this issue, a CMOS single-photon avalanche diode (SPAD)-based high-resolution particle detector is being developed. This work presents a study on SPAD layout optimization and a 4x4 SPAD macropixel module, fabricated in 110 nm CIS technology. Measurement results confirm that high-fill-factor designs improve photon detection efficiency without significant noise degradation. Furthermore, event-driven photon mapping and time stamping, enabled by time-to-digital converters and dedicated pixel circuits integrated into the 4x4 SPAD macropixel, were successfully demonstrated. This work is an essential step towards a sensor that detects probabilistic particle interactions and it lays the groundwork for the development of future large-scale SPAD-based particle detectors.
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All authors Kodai Kaneyasu, Till Dieminger, Matthew Franks, Davide Sgalaberna, Claudio Bruschini, Edoardo Charbon

Physics and Society

Temporal and Spatial Analysis of Crime Patterns in New York City: A Statistical Investigation of NYPD Complaint Data (1963-2025)

Fnu Gaurav

This study presents a comprehensive statistical analysis of criminal complaint data from the New York City Police Department (NYPD) spanning 47 years (1963-2025) [1]. Using a dataset of 438,556 complaint records, we employed exploratory data analysis (EDA), descriptive statistics, and multiple statistical hypothesis tests to investigate the spatial, temporal, and categorical patterns of urban crimes. Our findings revealed significant associations between crime types and geographic locations, temporal variations in criminal activity, and differences in crime severity across time. The results demonstrate that Brooklyn experiences the highest crime volume, petit-larceny constitutes the most common offense, and criminal activity peaks during the evening hours on weekdays, particularly Fridays. Statistical tests, including chi-square tests, Kruskal-Wallis H-test, and Mann-Whitney U test, confirmed highly significant relationships (p < 0.001) across all examined dimensions, providing evidence-based insights for law enforcement resource allocation and urban safety policy development.
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Plasma Physics

Relativistic resistive magnetohydrodynamics for a two-component plasma

Khwahish Kushwah, Caio V.P. de Brito and Gabriel S Denicol

We derive relativistic resistive magnetohydrodynamics for a two-component ultrarelativistic plasma directly from kinetic theory. Starting with the Boltzmann–Vlasov equation and using the 14-moment approximation in the Landau frame, we obtain coupled evolution equations for the charge diffusion four-current and the shear-stress tensor. Benchmarking against the usual Israel-Stewart type relaxation form shows that this simplified description is accurate for small viscosity to entropy ($\eta/s$) ratio, vanishing magnetic field, and not so strong electric field. Outside this regime the dynamics depart in a controlled way, i.e., strong electric fields introduce nonlinear back-reaction that delays and reduces current peaks, and a sizable shear-stress is produced even without a flow profile.
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Physics and Society

Understanding Mode Choice Behavior of People with Disabilities: A Case Study in Utah

Megh Bahadur KC, Ziqi Song, Keunhyun Park et al. (+1 more)

Despite the growing recognition of the importance of inclusive transportation policies nationwide, there is still a gap, as the existing transportation models often fail to capture the unique travel behavior of people with disabilities. This research study focuses on understanding the mode choice behavior of individuals with travel-limited disabilities and comparing the group with no such disability. The study identified key factors influencing mode preferences for both groups by utilizing Utah's household travel survey, simulation algorithm and Multinomial Logit model. Explanatory variables include household and socio-demographic attributes, personal, trip characteristics, and built environment variables. The analysis revealed intriguing trends, including a shift towards carpooling among disabled individuals. People with disabilities placed less emphasis on travel time saving. A lower value of travel time for people with disabilities is potentially due to factors like part-time work, reduced transit fare, and no or shared cost for carpooling. Despite a 50% fare reduction for the disabled group, transit accessibility remains a significant barrier in their choice of Transit mode. In downtown areas, people with no disability were found to choose transit compared to driving, whereas disabled people preferred carpooling. Travelers with no driving licenses and disabled people who use transit daily showed complex travel patterns among multiple modes. The study emphasizes the need for accessible and inclusive transportation options, such as improved public transit services, shorter first and last miles in transit, and better connectivity for non-motorized modes, to cater to the unique needs of disabled travelers. The findings of this study have significant policy implications such as an inclusive mode choice modeling framework for creating a more sustainable and inclusive transportation system.
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All authors Megh Bahadur KC, Ziqi Song, Keunhyun Park, Keith Christensen

Physics and Society

Generalized Friendship Paradoxes in Network Science

Desmond J. Higham, Francesco Hrobat and Francesco Tudisco

Generalized friendship paradoxes occur when, on average, our friends have more of some attribute than us. These paradoxes are relevant to many aspects of human interaction, notably in social science and epidemiology. Here, we derive new theoretical results concerning the inevitability of a paradox arising, using a linear algebra perspective. Following the seminal 1991 work of Scott L. Feld, we consider two distinct ways to measure and compare averages, which may be regarded as global and local. For global averaging, we show that a generalized friendship paradox holds for a large family of walk-based centralities, including Katz centrality and total subgraph communicability, and also for nonbacktracking eigenvector centrality. However, we also find counterexamples for centralities based on walks of even length. For local averaging we establish a paradox for nonbacktracking eigenvector centrality and we characterize the cases where the paradox holds with equality for the walk-based case. Defining loneliness as the reciprocal of the number of friends, we show that for this attribute the generalized and local friendship paradoxes always hold in reverse. In this sense, we are always more lonely, on average, than our friends. We also derive global and local averaging paradoxes for the case where the arithmetic mean is replaced by the geometric mean. As well as unifying and adding to the literature in this area, we highlight some open questions.
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Fluid Dynamics

A validated lumped-element model for bioinspired acoustic flow sensing toward the performance limit

Wei Sun, Wanyin Zheng, Xiangyu Wei et al. (+3 more)

Flow sensing is fundamental to both biological survival and technological innovation. Inspired by biological mechanoreceptors, artificial flow sensors detect subtle fluid motion using slender, viscous-driven structures. Among these, acoustic flow sensors that mimic nature's velocity-sensitive ears have the potential to transform vector sound detection. Yet, despite their potential, understanding of how design parameters determine ultimate sensor performance remains limited. To effectively guide flow sensor design, we develop and experimentally validate a lumped-element model that captures the broadband motion of slender microcantilevers immersed in fluid, combining analytical simplicity with quantitative accuracy. The model predicts flow-induced motion, thermomechanical noise, and the minimum detectable signal level, showing strong agreement with experimental measurements in air over a broad frequency range from 100 Hz to 10,000 Hz. This validated model provides a straightforward theoretical framework for designing high-performance micro- and nanomechanical sensors for flow and vector sound detection.
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All authors Wei Sun, Wanyin Zheng, Xiangyu Wei, David A. Czaplewski, Ronald N. Miles, Jian Zhou

Chemical Physics

Enhanced sensitivity to variations of fundamental constants in highly charged molecules from analytic perturbation theory

Carsten Zülch, Konstantin Gaul and Robert Berger

Quasi-forbidden electronic transitions in atoms and vibronic transitions between quasi-degenerate states in molecules serve as powerful probes of hypothetical temporal variations of fundamental constants. Computation of the sensitivity of a transition to a variation of the fine-structure constant is conventionally performed by numerical variation of the speed of light in sophisticated electronic structure calculations, and therewith several individual calculations have to be performed. An approach is presented herein that obtains sensitivity coefficients as perturbation to the Dirac-Coulomb Hamiltonian and allows, for instance, computation of their leading-order contributions as expectation values of the relativistic kinetic energy and rest-mass operators. These are available in essentially all ab initio relativistic electronic structure codes. Additionally, the corresponding operators for two-component Hamiltonians are derived, explicitly for the zeroth order regular approximation Hamiltonian. The approach is applied to demonstrate great sensitivity of highly charged polar molecules that were recently proposed for high-precision spectroscopy in [Zülch et al., arXiv:2203.10333[physics.chem-ph]]. In particular, a high sensitivity of a wealth of quasi-degenerate vibronic transitions in \ce{PaF^3+} and \ce{CeF^2+} to temporal variations of the fine-structure constant and the electron-proton mass ratio is shown.
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2511.10791 · 13 Nov · 17 pages, 5 figures, 7 tables; 6 pages of supplemental material with 1 figure, 9 tables; v2: text edits; corrected sign of electron-proton mass ratio contributions in eqs. (4,5), tables (VI,VII) and figure 5; more consistent use of power series and Taylor series in eqs. (15,28,29); improved description of ZORA transformation in Section IIC; improved linewidth model affecting tables VI and VII

Abstract PDF $HAML ×3$PRTN ×1

Chemical Physics · Cross-listed from quant-ph

Correlated Purification for Restoring $N$-Representability in Quantum Simulation

Yuchen Wang, Irma Avdic, Michael Rose et al. (+4 more)

Classical shadow tomography offers a scalable route to estimating properties of quantum states, but the resulting reduced density matrices (RDMs) often violate constraints that ensure they represent $N$-electron states – known as $N$-representability conditions – because of statistical and hardware noise. We present a correlated purification framework based on semidefinite programming to restore accuracy to these noisy, unphysical two-electron RDMs. The method performs a bi-objective optimization that minimizes both the many-electron energy and the nuclear norm of the change in the measured 2-RDM. The nuclear norm, often employed in matrix completion, promotes low-rank, physically meaningful corrections to the 2-RDM, while the energy term acts as a regularization term that can improve the purity of the ground state. While the method is particularly effective for the ground state, it can also be applied to excited and non-stationary states by decreasing the weight of the energy relative to the error norm. In an application to fermionic shadow tomography of large hydrogen chains, correlated purification yields substantial reductions in both energy and 2-RDM error, achieving chemical accuracy across dissociation curves. This framework provides a robust strategy for tomography in many-body quantum simulations.
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All authors Yuchen Wang, Irma Avdic, Michael Rose, Lillian I. Payne Torres, Anna O. Schouten, Kevin J. Sung, David A. Mazziotti

Geophysics

Seismic quiescence and activation prior to the 2025 M8.8 Kamchatka, Russia earthquake

K. Z. Nanjo, J. Yazbeck, I. T. Baughman et al. (+1 more)

The 2025 M8.8 Kamchatka earthquake in the Kamchatka-Kuril subduction system provides a unique opportunity to investigate the preparatory processes of a great subduction event. Despite Kamchatka's high seismic activity, the long-term evolution of seismicity preceding major ruptures has been poorly documented. Identifying temporal patterns-such as multiyear quiescence and short-term activation-is essential for understanding megathrust failure processes. We applied the Epidemic-Type Aftershock Sequence model and change-point analysis to earthquakes with M5+ within a 100-km radius of the 2025 mainshock epicenter, using the Advanced National Seismic System catalog spanning 1975-2025. This approach quantified temporal variations in the seismicity rate and detected statistically significant change points. We found a pronounced approximately 20-year quiescent interval beginning around mid-2003, followed by an abrupt activation that commenced with the M7.4 foreshock on 20 July 2025. Similar quiescence-to-activation sequences near the eventual hypocenter have been reported in previous studies for the 1997 M7.8 Kronotsky and 2006 M8.3 Simushirskoe earthquakes, which ruptured segments immediately north and south of the 2025 rupture, respectively. Together with these earlier studies, our findings suggest that such quiescence-to-activation transitions may represent a recurring preparatory process for megathrust earthquakes in the Kamchatka-Kuril subduction system, although this inference is based on a small number of events. Decadal-scale quiescence has also been reported off Hokkaido, Japan, overlapping the area assessed as having an elevated likelihood of a 17th-century-type M9-class earthquake. Given that Hokkaido is in the Kamchatka-Kuril subduction system, tracking a possible transition from quiescence to activation is important for situational awareness and time-dependent hazard assessment.
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All authors K. Z. Nanjo, J. Yazbeck, I. T. Baughman, J. B. Rundle

Physics and Society · Cross-listed from astro-ph.IM

Practical Author Name Disambiguation under Metadata Constraints: A Contrastive Learning Approach for Astronomy Literature

Vicente Amado Olivo, Wolfgang Kerzendorf, Bangjing Lu et al. (+3 more)

The ability to distinctly and properly collate an individual researcher's publications is crucial for ensuring appropriate recognition, guiding the allocation of research funding and informing hiring decisions. However, accurately grouping and linking a researcher's entire body of work with their individual identity is challenging because of widespread name ambiguity across the growing literature. Algorithmic author name disambiguation provides a scalable approach to disambiguating author identities, yet existing methods have limitations. Many modern author name disambiguation methods rely on comprehensive metadata features such as venue or affiliation. Despite advancements in digitally indexing publications, metadata is often unavailable or inconsistent in large digital libraries(e.g. NASA/ADS). We introduce the Neural Author Name Disambiguator, a method that disambiguates author identities in large digital libraries despite limited metadata availability. We formulate the disambiguation task as a similarity learning problem by employing a Siamese neural network to disambiguate author names across publications relying solely on widely available publication metadata-author names, titles and abstracts. We construct the Large-Scale Physics ORCiD Linked dataset to evaluate the Neural Author Name Disambiguator by cross-matching NASA/ADS publications ORCiD. By leveraging foundation models to embed metadata into features, our model achieves up to 94% accuracy in pairwise disambiguation and over 95% F1 in clustering publications into their researcher identities. We release the testing dataset as a benchmark for physics and astronomy, providing realistic evaluation conditions for future disambiguation methods. The Neural Author Name Disambiguator algorithm demonstrates effective disambiguation with minimal metadata, offering a scalable solution for name ambiguity in large digital libraries.
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All authors Vicente Amado Olivo, Wolfgang Kerzendorf, Bangjing Lu, Joshua V. Shields, Andreas Flörs, Nutan Chen

Optics

Broadband ultrafast self-heterodyned chiro-optical spectroscopy

Francesco Gucci{\dag}, Andrea Iudica{\dag}, Andres Valladares Y Tacchi{\dag} et al. (+12 more)

Ultrafast chiro-optical spectroscopy provides unique access to the structural dynamics of molecules, spin-valley relaxation in semiconductors, and the non-equilibrium optical response of chiral nanophotonic systems. Yet, because chiral signals are intrinsically weak and time-resolved spectroscopy probes small photoinduced changes, transient chiro-optical responses are often difficult to isolate from parasitic achiral contributions. Here, we introduce a broadband ultrafast chiro-optical spectroscopy technique that integrates a birefringent common-path interferometer with an optical polarization bridge to sensitively detect photoinduced changes in the polarization state of light. Phase-sensitive self-heterodyned detection enables simultaneous measurement of transient circular dichroism and optical rotatory dispersion across a broad spectral range with ultrafast temporal resolution. Balanced detection suppresses excess laser noise, enabling exceptional sensitivity (<50 ${\mu}$deg) close to shot-noise limit. We demonstrate this approach on an array of gold nano-helicoids, supported by a full-wave time-resolved model of the spatiotemporal dynamics of plasmonic non-equilibrium carriers and their associated optical nonlinearities. The model traces the system's transient chiro-optical response back to photoinduced modulations of the electric-magnetic dipole interaction in the nano-helicoid, elucidating the connection of near- and far-field dynamics in the non-equilibrium regime. We further investigate spin excitation, thermalization, and relaxation in a lead halide perovskite, establishing a novel approach to broadband time-resolved Faraday rotation. The simplicity, sensitivity, and wide applicability of this detection scheme provide a powerful platform for broadband ultrafast chiro-optical spectroscopy, opening new opportunities in biochemistry, solid-state physics, and nanophotonics.
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All authors Francesco Gucci{\dag}, Andrea Iudica{\dag}, Andres Valladares Y Tacchi{\dag}, Andrea Schirato, Giulia Crotti, Ryeong Myeong Kim, Soo Min Lee, Jeong Hyun Han, Andrea Villa, Dawar Ali, Aurora Rizzo, Margherita Maiuri, Ki Tae Nam, Giuseppe Della Valle, Giulio Cerullo

Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Oya: Deep Learning for Accurate Global Precipitation Estimation

Emmanuel Asiedu Brempong, Mohammed Alewi Hassen, MohamedElfatih MohamedKhair et al. (+7 more)

Accurate precipitation estimation is critical for hydrological applications, especially in the Global South where ground-based observation networks are sparse and forecasting skill is limited. Existing satellite-based precipitation products often rely on the longwave infrared channel alone or are calibrated with data that can introduce significant errors, particularly at sub-daily timescales. This study introduces Oya, a novel real-time precipitation retrieval algorithm utilizing the full spectrum of visible and infrared (VIS-IR) observations from geostationary (GEO) satellites. Oya employs a two-stage deep learning approach, combining two U-Net models: one for precipitation detection and another for quantitative precipitation estimation (QPE), to address the inherent data imbalance between rain and no-rain events. The models are trained using high-resolution GPM Combined Radar-Radiometer Algorithm (CORRA) v07 data as ground truth and pre-trained on IMERG-Final retrievals to enhance robustness and mitigate overfitting due to the limited temporal sampling of CORRA. By leveraging multiple GEO satellites, Oya achieves quasi-global coverage and demonstrates superior performance compared to existing competitive regional and global precipitation baselines, offering a promising pathway to improved precipitation monitoring and forecasting.
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All authors Emmanuel Asiedu Brempong, Mohammed Alewi Hassen, MohamedElfatih MohamedKhair, Vusumuzi Dube, Santiago Hincapie Potes, Olivia Graham, Amanie Brik, Amy McGovern, George J. Huffman, Jason Hickey