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Physics Physics

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Tuesday 17 March

Chemical Physics

Free complement method with Gaussian expanded complements: hierarchical decontraction to mitigate the exponential wall before selection

Cong Wang

The previous work (arXiv:2508.04635) of the free complement (FC) method with Gaussian expanded complement functions adopts the Slater initial wavefunction. This may introduce an exponential complexity of the variational coefficients associated to the Gaussian complement functions with respect to the number of electrons at a given order before the overlap matrix based selection, for more than one Gaussian function used in the expansion. The present work uses decontractions via the distinct exponents introduced by the $g$ functions to avoid this scenario at low order of the FC method. The exponential number of the variational parameters is postponed to higher orders of the FC expansion.
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Optics

Design and analysis of MoTe2-based efficient photonic devices for the solar cell and photodetector applications

Md. Naeemur Rahman, Md. Alamin Hossain Pappu, Md. Islahur Rahman Ebon et al. (+3 more)

A systematic survey and subsequent research have been made on MoTe2-based n-CdS/p-MoTe2/p+-CGS device in solar cell and photodetector field. The optimization has been established by altering the various properties of each constituent layer through numerical computation. The performance of the MoTe2 photonic device has been probed with and without CGS back surface field (BSF) layer in details. The proposed n-CdS/p-MoTe2/p+-CGS photonic device exhibits markedly improved cell efficiency, {\eta} of 32.92 % with VOC of 0.97 V, JSC of 41.21 mA/cm2, FF of 82.73% and responsivity, R of 0.74 A/W as well as detectivity, D* of 2.36x1016 Jones at a wavelength of 1000 nm. These simulation outcomes reveal the strong potential of MoTe2 absorber along with the novel and improved structure for highly-efficient solar cells and photosensors that capable of high detection capability.
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All authors Md. Naeemur Rahman, Md. Alamin Hossain Pappu, Md. Islahur Rahman Ebon, Abdul Kuddus, Dinesh Pathak, Jaker Hossain

Fluid Dynamics

Flow of yield stress fluid in a percolating network

Nathan Abitbol, Alex Hansen, Alberto Rosso et al. (+1 more)

We study the flow of a Bingham yield-stress fluid in a pore network model where the throats have radii drawn from a uniform distribution. We consider the case in which a fraction of the largest radii is blocked. The fluid can flow only through the percolating cluster that exists when the fraction is above the percolation threshold. Two distinct flow regimes are identified: above the percolation threshold the flow curve can be characterized by deterministic values of the critical pressure drop, permeability, and other observables, with subleading fluctuations that we quantify. At the percolation threshold these quantities become non-self-averaging, and their scaling is governed exclusively by the critical percolation backbone, independent of the specific realization of the radii.
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All authors Nathan Abitbol, Alex Hansen, Alberto Rosso, Laurent Talon

Optics

High-Bandwidth 940 nm VCSEL with Zn-diffusion for Optical Communications

Fu-He Hsiao, Yu-Jie Lin, Chia-Jung Tsai et al. (+7 more)

We present a systematic design methodology, combining simulation and experimental validation, for high-speed 940 nm vertical-cavity surface-emitting lasers (VCSELs). A comprehensive simulation study was conducted to optimize the device structure, focusing on the number of oxide layers and the aperture size, which predicted a maximum modulation bandwidth of over 35 GHz. To validate this approach, an optimized device with a 4-{\mu}m double-oxide aperture was fabricated and characterized. Crucially, during the fabrication process, a Zn-diffused region was incorporated to further enhance device performance. The experimental results demonstrate a modulation bandwidth of 34 GHz and successful 100 Gbit/s PAM-4 data transmission. The excellent agreement between the simulated and measured performance validates the effectiveness of our design meth-odology, providing a reliable framework for developing next-generation optical inter-connects.
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All authors Fu-He Hsiao, Yu-Jie Lin, Chia-Jung Tsai, Chia-Chen Li, Yun-Han Chang, Chih-Ting Chang, Jr-Hau He, Chun-Liang Lin, Yu-Heng Hong, Hao-Chung Kuo

General Physics

A Binary Classifier-Based Wire Resistance Attack on the KLJN Secure Key Exchanger

Mehmet Yildirim, Fahrettin Ay and Laszlo B. Kish

The statistical fluctuations of the mean-square noise voltages measured at Alice's and Bob's ends in the KLJN scheme are used to implement a binary classifier for a new type of wire resistance-based attack. The data are plotted on a two-dimensional graph, where the x- and y- axes represent the mean-square voltages at Alice's and Bob's ends, respectively. When the wire resistance is nonzero, the data form distinct lines for the LH and HL cases, allowing Eve to extract the secure bits with nearly 100% success. Further analysis shows that swapping the x and y axes for the LH data reproduces the curve for the HL case, effectively reducing the number of independent measurements by half. These results suggest that machine learning tools could exploit this property for enhanced detection performance, although such methods are unnecessary here since the LH and HL cases are completely separable. The only effective defense against this attack remains the traditional approach: properly increase the noise temperature on the side with lower resistance, or equivalently, scale down the noise temperature on the higher-resistance side. All claims are confirmed through computer simulations.
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Atomic Physics · Cross-listed from cond-mat.quant-gas

Tuning Topological Charge and Gauge Field Anisotropy in a Spin-1 Synthetic Monopole

Nicholas Milson, Arina Tashchilina, Kathleen Tamura et al. (+2 more)

Higher-dimensional Hilbert spaces in quantum simulation, as in all quantum science, expand the range of accessible phenomena. In this work, we experimentally realize a synthetic monopole using an ultracold spin-1 ensemble, where the monopole charge is quantified by the topologically invariant first Chern number and sources a synthetic magnetic field quantified by the Berry curvature. By using a three-level system with tunable spin-tensor coupling, we introduce anisotropy to the field, directly measure the Chern number, and observe a topological phase transition. We verify the robustness of the monopole's topological charge under deformation, and observe signatures of the topological phases using spin-texture and Majorana-star measurements. This work demonstrates spin-tensor coupling as a tuning parameter for engineering both geometric anisotropy and a rich topological phase space.
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All authors Nicholas Milson, Arina Tashchilina, Kathleen Tamura, Douglas Florizone, Lindsay J. LeBlanc

Fluid Dynamics

Nonlinear dynamics involving multiple modes in high-speed transitional boundary layer

Xiao-Bai Li, Yifeng Chen, Chihyung Wen et al. (+1 more)

Extensive studies have investigated the transition mechanism of boundary layers initiated by a single primary instability. In a real-world scenario, however, multiple primary instabilities of different physical nature would coexist and generate more complicated stages of mode–mode interactions. For this scenario, conventional secondary stability analysis may not be applicable. In this work, a general framework is established to decompose the input–output system and to quantify the transfer of energy involving various modes. The linearized governing equation with nonlinear forcings is applied in a Mach 6 boundary layer, where two different types of primary instabilities are added simultaneously. As the primary-wave amplitudes increase to certain threshold, the nonlinear effect causes the saturation of the second mode and secondary growth of the first mode. In the generation stage of each higher-order mode, a specific leading triadic forcing term can be identified. These higher-order waves manifest solely in response to the identified dominant forcing during their generation. At the moderate and late transitional stages, the forcings are, however, not equally transferred to the response via the resolvent operator. In other words, the base-flow-associated resolvent operator exerts different levels of `leverage' to transfer different forcings to responses. The nonlinear energy transfer via triadic forcings also drives the higher-order instability to inherit physical signature from the associated lower-order instability. Finally, the interplay between secondary/tertiary waves and primary waves occurs notably earlier then one may expect, namely before transition onset or in the early transitional region. This differs from the traditional secondary instability analysis that a large-amplitude primary wave is developed first to perform the bi-global analysis in the distorted base flow.
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All authors Xiao-Bai Li, Yifeng Chen, Chihyung Wen, Peixu Guo

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

PFP/MM: A Hybrid Approach Combining a Universal Neural Network Potential with Classical Force Fields for Large-Scale Reactive Simulations

Yu Miyazaki, Atsuhiro Tomita, Akihide Hayashi et al. (+3 more)

Universal machine-learning interatomic potentials (uMLIPs) enable reactive molecular simulations with near-DFT accuracy, yet applying them efficiently to large, realistic condensed-phase systems remains computationally demanding. Here we present PFP/MM, a hybrid approach that combines a uMLIP, PreFerred Potential (PFP), with molecular mechanics (MM) to enable both large-scale and long-time simulations that are challenging for uMLIP-only calculations. Using an alanine dipeptide in explicit water, we achieve multi-ns/day enhanced sampling and obtain a Ramachandran plot consistent with established basins. For an intramolecular nucleophilic addition reaction in a polar solvent environment, we reproduce the expected solvent-induced stabilization in the free-energy profile. We further apply the approach to a cytochrome P450 Compound I hydroxylation reaction and obtain a free-energy landscape consistent with the accepted reaction mechanism. These results demonstrate that uMLIP-based reactive simulations can be applied to diverse condensed-phase processes in large, realistic environments.
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All authors Yu Miyazaki, Atsuhiro Tomita, Akihide Hayashi, So Takamoto, Mizuki Takemoto, Hodaka Mori

Computational Physics · Cross-listed from quant-ph

Qudit Implementation of the Rodeo Algorithm for Quantum Spectral Filtering

Julio Cesar Siqueira Rocha and Rodrigo Alves Dias

Qudits, the multi-level generalization of qubits, provide a natural extension of the binary paradigm in quantum computation and offer new opportunities to enhance algorithmic performance. Beyond their direct applicability to the simulation of multi-level quantum systems, higher-dimensional ancillae can improve sampling efficiency in quantum algorithms by enabling the simultaneous implementation of multiple control operations, thereby reducing circuit complexity. In this work, we pursue three main objectives. First, we present a formulation of the Rodeo algorithm employing a general $d$-level ancilla qudit. Second, we introduce the concept of the Rodeo kernel, defined as a two-frequency interferometer, which acts as a spectral filter in the energy domain. Finally, we propose a microcanonical protocol for the Rodeo algorithm. This protocol enables the estimation of entropic quantities through a single energy sweep and admits a natural interpretation as a Gaussian convolution of the density of states. To support the theoretical analysis, we perform numerical evaluations of the corresponding quantum circuit using ancilla qudits of dimensions three, four, and five. The simulations are performed for the one-dimensional Ising model, considering both spin-$\sfrac{1}{2}$ and spin-$1$ particles. The ancilla qutrit implementation exhibits an $18\%$ reduction in fluctuations compared to the qubit implementation. Our results show that qudits provide a framework for spectral analysis and thermodynamic characterization of multi-level quantum systems.
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Atomic Physics · Cross-listed from quant-ph

Monolithic Segmented 3D Ion Trap for Quantum Technology Applications

Abhishek Menon, Michael Straus, George Tomaras et al. (+12 more)

Monolithic three-dimensional (3D) Paul traps combine the high-precision microfabrication of two-dimensional (2D) chip traps with the deep trapping potentials and low heating rates characteristic of macroscopic 3D Paul traps, which are typically machined by traditional means and mechanically assembled. However, achieving low motional heating rates and optical access with a high numerical aperture (NA) while maintaining the high radio-frequency (RF) voltages required for trapping heavy ionic species, such as Yb$^{+}$ and Ba$^{+}$, remains a significant technical challenge. In this work, we present a fused-silica, monolithic segmented 3D Paul trap with an ion-electrode distance of 250 $\mu$m, and stable operation at high RF voltages. We benchmark the performance of the trap using Yb$^{+}$ ions, demonstrating axially homogeneous trapping potentials spanning over 200 $\mu$m about the axial center of the trap, high multi-directional optical access (up to 0.7 NA), and radial motional heating as low as $\dot{\bar n}=1.1 \pm 0.1 $ quanta/s at radial trap frequencies about 3 MHz near room temperature. Furthermore, we observe a motional Ramsey coherence time, ${T}_{2}$, of about 95 ms for the radial center-of-mass mode. We demonstrate the generation of a two-qubit Bell state with a parity contrast of ${99.3}^{+0.7} _{-1.5}$% with state preparation and measurement correction. These results establish fused-silica monolithic 3D Paul traps as a scalable, modular platform for quantum simulation, computation, metrology, and networking with heavy ionic species.
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All authors Abhishek Menon, Michael Straus, George Tomaras, Liam Jeanette, April X. Sheffield, Devon Valdez, Yuanheng Xie, Visal So, De Luo, Midhuna Duraisamy Suganthi, Mark Dugan, Philippe Bado, Norbert M. Linke, Guido Pagano, Roman Zhuravel

Biological Physics

On the Analytic Origin of Two Species of Cochlear Eigenmodes

Asheesh S. Momi, Isabella R. Graf, Michael C. Abbott et al. (+1 more)

After entering the ear, sound waves propagate as surface waves along the cochlea's basilar membrane. In recent work, we showed numerically that the system supports two types of modes: localized resonant modes, which underpin the modern understanding of cochlear mechanics, and a novel class of spatially extended modes. Here, we develop an analytic framework that explains the emergence of this mode structure. We show that extended modes arise from globally continuous standing-wave solutions, whereas localized modes result from internal resonance requiring matching across a singular point. These results clarify the generic structure of cochlear wave equations.
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All authors Asheesh S. Momi, Isabella R. Graf, Michael C. Abbott, Benjamin B. Machta

Atmospheric and Oceanic Physics

Transition path theory insights into hurricane rapid intensification

F.J. Beron-Vera, G. Bonner, M.J. Olascoaga et al. (+2 more)

We explore hurricane and ocean reanalysis data to understand how rapid intensification (RI) of tropical cyclones is impacted by the upper ocean density structure, with an emphasis on barrier layer (BL) thickness and thermocline depth in the eastern Caribbean Sea and adjacent western tropical North Atlantic. This analysis leverages transition path theory (TPT), supported by basic statistical methods. In TPT, Markov chains are constructed by discretizing data series related to weather system intensity, changes in intensity, translational speed, and BL thickness and thermocline depth. These series are viewed as trajectories in abstract state spaces, following a memoryless stochastic process. RI imminence is rigorously framed using a newly derived TPT statistic, which gives the time distribution to first reach a target – the RI state – from a source – for instance, the state determined by a certain BL range and system intensity – conditional on connecting paths exhibiting minimal detours. Increased RI frequency is observed in the eastern Caribbean and nearby Atlantic, influenced by river runoff, primarily in tropical storms and category 2 hurricanes. RI frequently correlates with a well-developed BL; however, increased translational speed is necessary for RI. TPT shows a stronger connection between RI and thermocline depth than BL presence, with RI likelihood rising for hurricanes with a thin BL, especially category 1. Across all strength categories, a deep thermocline consistently elevates RI probability, a factor missed by basic statistical analysis. Furthermore, translational speed is crucial, with faster, stronger hurricanes more susceptible to RI, while slower systems are less so.
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All authors F.J. Beron-Vera, G. Bonner, M.J. Olascoaga, S. Dong, H. Lopez

General Physics

Ringdown bounds and spectral density limits from GWTC-3

Christian Balfagon

We establish the first observational bounds on causal nonlocal extensions of gravity characterized by retarded Stieltjes-type kernels with positive spectral density rho(mu) >= 0, using two complementary gravitational-wave channels. From a Bayesian ringdown analysis of 17 binary black hole events in the LIGO-Virgo GWTC-3 catalogue, we set an observational ceiling on universal fractional quasi-normal mode deformations of |epsilon_Omega| < 0.05 (90% C.L.), with a cumulative log Bayes factor ln B = -0.46 +/- 0.77. By mapping published GWTC-3 modified dispersion relation bounds together with the GW170817 propagation speed constraint onto the Stieltjes spectral parameter space (mu_char, M0), we exclude a broad class of infrared-extended spectral densities with mu <= 10^{-6} m^{-2}, thereby ruling out non-trivial regions of the nonlocal kernel parameter space for the first time. The theoretically motivated fiducial range mu_char ~ M_*^2 ~ 10^8-10^10 m^{-2} satisfies all current bounds. We further show that sub-millimetre gravity experiments, which already operate at the predicted causal scale l_* ~ 10^{-4} m, provide the most promising path toward a direct test. These results define quantitative benchmarks against which future observations across the gravitational-wave, short-range gravity, and cosmological sectors can be compared.
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Monday 16 March

General Physics

A Kähler and quaternion-Kähler spacetime structure

R. Vilela Mendes

When real Lorentzian spacetime is embedded into a manifold parametrized by higher division algebras (complex or quaternion with Hermitean metric) and the representation constraints of their symmetry groups are made compatible, a set of quantum numbers is generated that is evocative of those of the standard model of particle physics. This is taken here as a hint that in spacetime there is a pseudo-Kähler or pseudo-quaternion-Kähler structure, real spacetime being a submanifold that inherits the symmetry contraints of the larger ambient manifold.
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Atmospheric and Oceanic Physics

Structure-preserving stochastic parameterization of a barotropic coupled ocean-atmosphere model with Ornstein–Uhlenbeck noise

Kamal Kishor Sharma and Peter Korn

We present the first application of the stochastic advection by Lie transport (SALT) framework to an idealized coupled ocean-atmosphere system. SALT derives stochastic fluid equations from Hamilton's variational principle under a stochastic Lagrangian kinematic assumption, thereby preserving the geometric structure – Kelvin circulation theorem, Lie-derivative advection operators, and local conservation laws – of the underlying deterministic equations. The atmospheric component is rendered stochastic while the ocean remains deterministic, following Hasselmann's paradigm of a fast stochastic atmosphere driving a slow climate. The spatial correlation vectors encoding unresolved subgrid transport are estimated from high-resolution simulations via EOF analysis of Lagrangian trajectory differences. A central contribution is the replacement of the standard white-noise temporal model with Ornstein-Uhlenbeck (OU) processes, motivated by strong autocorrelation (decorrelation times of 50-150 time steps) in the dominant EOF modes; the OU process is the unique stationary Gaussian Markov process capable of capturing this temporal memory with a single parameter. Ensemble forecasts exhibit good spread-error agreement over 10-15 time units. Evaluated via the Continuous Ranked Probability Score – a strictly proper scoring rule measuring discrepancy between the forecast measure and the true conditional distribution – the stochastic ensemble consistently outperforms a size-matched deterministic ensemble, despite carrying higher RMSE. Well-posedness of the coupled stochastic system is identified as an important open problem.
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Computational Physics · Cross-listed from cs.CE

SCALE-TRACK: Asynchronous Euler-Lagrange particle tracking on heterogeneous computing architecture

Silvio Schmalfuß, Sergey Lesnik, Henrik Rusche et al. (+1 more)

Euler-Lagrange (EL) simulations provide a direct and robust framework for modeling disperse multiphase flows. However, they are computationally expensive. While various approaches have attempted to leverage heterogeneous computing architectures, they have encountered scalability limitations. We present SCALE-TRACK, a scalable two-way coupled EL particle tracking algorithm, designed to exploit heterogeneous exascale computing environments. With asynchronous coupling, cache-friendly data structures, and chunk-based partitioning, we address key limitations of existing EL implementations. Validations against an analytical solution and a conventional EL implementation demonstrate the accuracy of the proposed algorithms. On a local workstation, we simulated 1.4 billion particles in a test case featuring a single graphics processing unit (GPU). Scaling runs on an HPC (high-performance computing) cluster show excellent strong and weak scaling, with up to 256 billion particles being tracked on up to 256 GPUs. This represents a significant advancement for EL simulations, enabling high-fidelity simulations on local workstations and pushing the limits on HPC systems. The software is released as open source and is publicly available.
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All authors Silvio Schmalfuß, Sergey Lesnik, Henrik Rusche, Dennis Niedermeier

Biological Physics · Cross-listed from q-bio.NC

Black Hole-Inspired Horizon Model for Neural Signal Dynamics

E. Canessa

Electroencephalographic (EEG) signals provide macroscopic observables of complex neural dynamics. We introduce a horizon-inspired framework in which measured EEG signals are modeled as projections of a complex wave-like representation constrained by an effective boundary analogous to an event horizon. In this formulation the signal amplitude obeys a renormalization-group scaling relation while EEG spectral entropy parameterizes the accessibility of observable modes. The resulting solutions generate oscillatory structures whose geometry and spectral signatures can be explored through signal analysis and sonification. This mapping between entropy-based neural observables and wave-like signal representations provides a physically motivated framework linking entropy measures, scale-dependent dynamics, and observable neural oscillations, and suggests testable connections between spectral entropy and the amplitude scaling of EEG modes.
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Data Analysis and Statistics

A complex network approach to characterize clustering of events in irregular time series

Ambedkar Sanket Sukdeo, K. Shri Vignesh, Sachin S. Gunthe et al. (+3 more)

In complex systems, events occur at irregular intervals that inherently encode the underlying dynamics of the system. Analyzing the temporal clustering of these events reveals critical insights into the non-random patterns and the temporal evolution. Existing techniques can effectively quantify the overall clustering tendency of events using global statistical measures. However, these macroscopic approaches leave a critical gap, as they do not attempt to investigate the dynamics of individual clusters. Analyzing individual clusters is essential, as it helps comprehend the local interactions that actively drive the system dynamics, which may be obscured by global averaging, while simultaneously revealing the time scales involved. To address these limitations, we propose a complex network-based framework for analyzing clustering of events occurring at irregular intervals. The framework establishes connections using arrival times, transforming the time series into a network. Network properties are then used to quantify the clustering. Further, a community detection algorithm is used to identify individual clusters in time series. We illustrate the method by applying it to standard arrival processes, such as the Poisson process and the Markov-modulated Poisson process. To further demonstrate its scope, we apply the method to two diverse systems: the time series of droplet arrivals in turbulent flows and the R-R intervals in electrocardiogram (ECG) signals.
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All authors Ambedkar Sanket Sukdeo, K. Shri Vignesh, Sachin S. Gunthe, T Narayan Rao, Amit Kumar Patra, R. I. Sujith

Geophysics

Comprehensive VLBI observations of Galileo satellites with the AuScope array

David Schunck, Lucia McCallum, Jamie McCallum et al. (+1 more)

Interest in the topic of geodetic co-location in space and space ties has recently intensified within the geodetic community, particularly following the approval of the European Space Agency's (ESA) Genesis mission. From the perspective of Very Long Baseline Interferometry (VLBI), observations of Earth-orbiting satellites are not standard practice yet. To enable VLBI support for future colocation satellite missions, such observations must be integrated into the VLBI processing chain. In this study, we present comprehensive VLBI observations of Galileo navigation satellites conducted with the Australian AuScope VLBI array. Using the 12-m antennas in Hobart, Katherine and Yarragadee equipped with VLBI Global Observing System (VGOS) instrumentation, Galileo E1 and E6 signals were observed in test experiments and a series of four full-scale 24-hour observing sessions. We present the estimation of VLBI station coordinates from observations to navigation satellites, thereby demonstrating, for the first time, inter-technique ties between the VLBI and Global Navigation Satellite System (GNSS) frame. We describe the processing strategy, including correlation, fringe fitting, precision assessment and satellite tracking approach. Delay observables achieve precisions of a few picoseconds in the E1 band and several tens of picoseconds in the E6 band for 1-s integration times. However, unmodelled signals on the order of several hundred picoseconds are found in the residual delays. Estimated station coordinates agree with a priori values at the metre level, while baseline lengths agree at the sub-metre level. These results demonstrate the feasibility of large-scale VLBI observations to GNSS satellites and provide critical groundwork for future co-location satellite missions such as Genesis.
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All authors David Schunck, Lucia McCallum, Jamie McCallum, Tiege McCarthy

Geophysics

In situ U Pb chronology and chemistry of zirconolite in the andesitic meteorite Erg Chech 002

Jun Sakuma, Hisashi Asanuma, Naoto Takahata et al. (+2 more)

Precise and accurate ages for asteroidal crusts are fundamental for reconstructing the timeline of magmatic, metamorphic, and impact events in the early Solar System. Zirconolite (CaZrTi2O7) is an accessory mineral found in a wide range of crustal rocks on both the Earth and Moon, and has proven to be a potentially useful U Pb chronometer. However, this mineral is rare in asteroidal meteorites, and its use for early Solar System chronology has been limited. We present the in situ occurrence, U Pb chronology, and chemistry of zirconolite in the andesitic meteorite Erg Chech 002, which represents a sample of the oldest known asteroidal crust. The zirconolite occurs as needle- and fiber-shaped, stubby crystals, with widths of 3 micrometers and lengths of up to 30 micrometers. Electron and ion microprobe analyses yielded concordant U Pb data with a weighted mean 207Pb 206Pb age of 4557.9 4.3 Ma 2sigma, rendering it the Solar System's oldest known zirconolite. Yet, this age is distinctly younger than reported high-precision 207Pb 206Pb ages varying from 4565.6 to 4566.2 Ma, which were obtained by acid leaching of pyroxene and whole rock samples of the meteorite. From its mineralogical and REE (U+Th) (Nb+Ta) characteristics, we argue that the zirconolite age represents the timing of a shock metamorphism of the parent asteroid's crust. Our results suggest that 207Pb 206Pb dating for acid-leached samples can be affected by including even a tiny amount of metamorphic zirconolite, calling for caution in interpreting the high-precision 207Pb 206Pb age data. On the basis of thermodynamic and geochemical considerations, we infer further occurrences of zirconolite in alkali-silica-rich asteroidal rocks that rapidly cooled from high temperatures.
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All authors Jun Sakuma, Hisashi Asanuma, Naoto Takahata, Akira Yamaguchi, Tsuyoshi Iizuka

Geophysics

A Framework for Modeling Liquefaction-Induced Road Disruptions After Earthquakes: Implications for Emergency Response and Access in the Cascadia Region of North America

Morgan D. Sanger, Olyvia B. Smith, Brett W. Maurer et al. (+3 more)

Large earthquakes along the Cascadia Subduction Zone (CSZ) are expected to trigger widespread soil liquefaction that could disrupt transportation systems across the U.S. Pacific Northwest. However, past regional assessments have relied on simple geologic screening methods and binomial shaking thresholds that are only loosely informed by liquefaction science. This study introduces a mechanics-informed, data-driven framework for estimating liquefaction-induced road closures and service reductions, and the framework is applied to a magnitude-9 CSZ earthquake. Predicted liquefaction severity is translated into segment-level probabilities of closure and reduced service using empirically derived fragility relationships. These probabilities are mapped at 90-m resolution and propagated through the National Highway System using a spatially correlated Monte Carlo simulation to estimate link-level disruption. Results show that impacts are concentrated in low-lying coastal zones, river valleys, and urban waterfronts, with major disruptions expected along critical routes including U.S. Route 101. Local mobility is further examined in Pacific and Grays Harbor counties, Washington, where limited network redundancy, strong shaking, and high liquefaction susceptibility lead to elevated probabilities of isolation and loss of hospital access. Socioeconomic analysis reveals modest but statistically significant associations between road impacts and demographic indicators, suggesting that liquefaction impacts may compound with existing social vulnerabilities. While not a substitute for site-specific analysis, the results provide a regional baseline for emergency planning, risk communication, and prioritization of more advanced geotechnical sampling and analysis. Moreover, the methodology proposed here is not specific to the CSZ, but rather, could be applied to analogous studies of road impacts elsewhere.
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All authors Morgan D. Sanger, Olyvia B. Smith, Brett W. Maurer, Liam Wotherspoon, Marc O. Eberhard, Jeffrey W. Berman

Data Analysis and Statistics

Automatic Termination Strategy of Inelastic Neutron-scattering Measurement Using Bayesian Optimization for Bin-width Selection

Kensuke Muto, Hirotaka Sakamoto, Kenji Nagata et al. (+2 more)

Currently, an excessive amount of event data is being obtained in four-dimensional inelastic neutron-scattering experiments. A method for automatic bin-width optimization of multidimensional histograms has been developed and recently validated on real inelastic neutron-scattering data. However, measuring beyond the equipment resolution leads to inefficient use of valuable beam time. To improve experimental efficiency, an automatic termination strategy is essential. We propose a Bayesian-optimization-based method to compute a stopping criterion that can support online decisions on whether to continue or terminate an experiment. In the proposed method, the bin-width optimization is performed using Bayesian optimization to efficiently compute the optimal bin widths. The experiment is terminated when the optimal bin widths become smaller than the target resolutions. In numerical experiments using real inelastic neutron-scattering data, the optimal bin widths decrease as the number of events increases. Even the optimal bin widths for data downsampled to 1/5 are comparable with the resolutions limited by the sample size, choppers, and so on. This implies excessive measurement of the inelastic neutron experiments for the moment. Moreover, we found that Bayesian optimization can reduce the search cost to approximately 10% of an exhaustive search in our numerical experiments.
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All authors Kensuke Muto, Hirotaka Sakamoto, Kenji Nagata, Taka-hisa Arima, Masato Okada

Physics and Society

Heterogeneous Returns and Wealth Tax Neutrality: A Fokker-Planck Framework

Anders G Frøseth

We extend the Fokker-Planck framework of Froseth (2026, arXiv:2603.05283) to populations of investors with heterogeneous, persistent return-generating ability. When the drift coefficient in the Langevin equation for log-wealth varies across investors, the proportional wealth tax remains a uniform drift shift but ceases to be neutral in the economic sense: its real incidence differs across ability types, and the stationary wealth distribution changes shape. We derive the extended Fokker-Planck equation on the joint space of log-wealth and ability, characterise the conditions under which the drift-shift symmetry breaks, and identify the consequences for asset prices and portfolio allocations. The analysis connects the neutrality results of Froseth (2026, arXiv:2603.05264) and the Fokker-Planck dynamics of Froseth (2026, arXiv:2603.05283) to the heterogeneous-returns literature, notably the "use-it-or-lose-it" mechanism of Guvenen, Kambourov, Kuruscu, Ocampo-Diaz and Chen (2023).
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2603.16006 · 16 Mar · 24 pages, 1 figure, 1 table. v3: Guvenen et al. citation updated to the published QJE 2023 numerics; Guvenen et al. 2024 added as companion reference; several results restated in formal environments (content unchanged). v2: citation and gross-wealth corrections; phi decomposition formalised

Abstract PDF $SYMM ×1

Accelerator Physics

Advanced Control of Electron Beams: Tailoring X-ray Production with Programmable Laser Shaping

Jack Hirschman, Randy Lemons, Hao Zhang et al. (+23 more)

Leveraging the full scientific capabilities of next-generation high-repetition-rate free-electron lasers requires programmable control over electron-beam properties at their source. The photoinjector drive laser defines the electron beam's initial six-dimensional phase-space distribution, yet has historically been limited to Gaussian or static flat-top profiles, with most manipulation occurring downstream. Here we demonstrate software-programmable ultraviolet pulse shaping at the LCLS-II photoinjector as a source-level actuator that complements traditional accelerator controls. Using a coupled architecture combining dispersion-controlled nonlinear frequency conversion with spatial-light-modulator spectral shaping, we generate user-defined temporal structures and observe their imprint on electron bunches through high-resolution time-domain diagnostics. Laser-imposed multi-peaked modulation persists through acceleration, magnetic compression, and undulator transport with shot-to-shot repeatability, producing clearly resolved current structure in the compressed beam. Variance-based reconstruction from transverse deflecting cavity measurements reveals structured X-ray emission profiles exhibiting temporal features consistent with the programmed laser waveform. By providing rapid, software-controlled reconfiguration of electron-beam initial conditions, this source-level control approach establishes a programmable upstream actuator for future adaptive optimization and autonomous facility operation at high-repetition-rate light sources.
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All authors Jack Hirschman, Randy Lemons, Hao Zhang, Razib Obaid, River Robles, Paris Franz, Benjamin Mencer, Nicole Neveu, Matthew Britton, David Cesar, Nicolas Sudar, Zhen Zhang, Justin Baker, Chad Pennington, Kurtis Borne, Taran Driver, Kirk A. Larsen, Veronica Guo, Yuantao Ding, Gabriel Just, Feng Zhou, James Cryan, Joseph Robinson, Ryan Coffee, Agostino Marinelli, Sergio Carbajo

Fluid Dynamics

Physics-Constrained Neural Closure for Lattice Boltzmann Large-Eddy Simulation

Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao et al. (+1 more)

We present a physics-constrained, data-driven subgrid-scale (SGS) stress closure for large-eddy simulation (LES) in the lattice Boltzmann method (LBM). Trained on filtered-downsampled (FD) data from LBM direct numerical simulation (DNS) of forced homogeneous isotropic turbulence (FHIT) spanning multiple filter widths, a compact neural network maps nine macroscopic derivative inputs - six strain-rate and three vorticity components - to the six independent components of the SGS stress tensor; a deviatoric projection is applied post-inference to obtain the traceless stress used in the solver. Training combines a stress data loss with physics terms for SGS energy-transfer (Pi) matching, rotational equivariance under cube rotations, and compatibility of the implied SGS forcing with the divergence-based coupling. The predicted stress is coupled to the solver through a split strategy: a dissipative, strain-aligned contribution is represented through an effective-viscosity projection, while the remaining anisotropic residual is applied through a forcing term. This construction is intended to retain both backscatter (via the effective viscosity) and non-dissipative anisotropic effects (via the residual forcing), while remaining compatible with LBM deployment. In the cases considered here, a priori results show good agreement with FD references across stress components and SGS-transfer statistics, and a posteriori rollouts improve several energetic and statistical measures relative to static and dynamic Smagorinsky baselines. A preliminary transfer test in turbulent channel flow is also reported without retraining. Finally, we demonstrate production deployment via ONNX Runtime, with throughput comparable to a dynamic Smagorinsky baseline in the tested configuration.
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All authors Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao, Giacomo Falcucci

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

Mechanical Control of Polar Order

Pushpendra Gupta, Peter Meisenheimer, Xinyan Li et al. (+5 more)

BiFeO3 is a model multiferroic in which the ferroelectric polarization is coupled to ferroelastic lattice distortions, yet deterministic control of its domain structure remains limited by high switching fields and competing polarization variants. Here, we identify a mechanically assisted polarization switching pathway in epitaxial BiFeO3 thin films that fundamentally alters the switching energetics. Using just out-of-plane electric fields, polarization reversal requires voltages of approximately 4 V and stabilizes coexisting polarization states. In contrast, when mechanical pressure is applied concurrently, the coercive voltage can be significantly reduced (even to 0V), resulting in spontaneous switching. Piezoresponse force microscopy measurements reveal that applied mechanical pressure suppresses ferroelastic domain competition, indicating a decrease in the required electrical energy barrier associated with polarization rotation and domain wall motion. These results demonstrate that stress acts as an active thermodynamic control parameter, enabling access to switching pathways that are inaccessible under only an electric field. By directly coupling lattice distortions to polarization reversal, mechanically assisted switching provides a general framework for controlling coupled order parameters in multiferroic oxides, which can be directly applied in the device-level architecture, where a small mechanical pressure can help in achieving lower switching energy of ferroelectric polarization. This work advances the fundamental understanding of electromechanical coupling in complex ferroics and establishes mechanical energy as a powerful tool for probing and manipulating ferroelastic ferroelectric interactions.
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All authors Pushpendra Gupta, Peter Meisenheimer, Xinyan Li, Sajid Husain, Vishantak Srikrishna, Ashley Cortesis, Yimo Han, Ramamoorthy Ramesh

Geophysics

Elastic waveform inversion for double-couple microseismic source estimation in vertically fractured transversely isotropic media

Ujjwal Shekhar, Einar Iversen, Florin A. Radu et al. (+2 more)

Accurate characterization of microseismic events during fluid injection in sedimentary formations is essential to mitigate environmental risks. The source mechanism for microseismic events related to a slip on a fault plane is given by a double-couple. Waveform inversion has emerged as a promising technique for estimating the moment tensor and the position vector of double-couple sources. In most applications of waveform inversion for the moment tensor of double-couple sources, the formation is typically assumed to be isotropic or, less frequently, transversely isotropic. Modification of the moment-tensor representation to account for anisotropy created by aligned vertical fractures in transversely isotropic formations has not been included while inverting microseismic waveform data. In this study on synthetic microseismic data, we present a waveform inversion algorithm that includes this modification, considering the formation in the focal region to be vertically fractured transversely isotropic (VFTI) and possessing orthorhombic symmetry. Since VFTI media lack rotational symmetry, no assumptions have been made about the orientation of the fault plane where the slip occurred. The moment tensor of double-couple sources is formulated in terms of the elastic parameters of the VFTI medium and geometrical parameters which are slip magnitude, slip angle, fault dip, and azimuth angle of the fault-normal. Source inversion is treated as a local optimization problem, and we invert for the source location and the geometrical parameters. These geometrical parameters are more directly constrained by seismic data than the moment tensor components and offer geologically meaningful insights. This approach enhances microseismic monitoring in fractured formations and can be extended to more complex anisotropic media, such as monoclinic systems.
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All authors Ujjwal Shekhar, Einar Iversen, Florin A. Radu, Inga Berre, Morten Jakobsen

Optics · Cross-listed from eess.IV

Standardizing Medical Images at Scale for AI

Callen MacPhee, Yiming Zhou, Koichiro Kishima et al. (+1 more)

Deep learning has achieved remarkable success in medical image analysis, yet its performance remains highly sensitive to the heterogeneity of clinical data. Differences in imaging hardware, staining protocols, and acquisition conditions produce substantial domain shifts that degrade model generalization across institutions. Here we present a physics-based data preprocessing framework based on the PhyCV (Physics-Inspired Computer Vision) family of algorithms, which standardizes medical images through deterministic transformations derived from optical physics. The framework models images as spatially varying optical fields that undergo a virtual diffractive propagation followed by coherent phase detection. This process suppresses non-semantic variability such as color and illumination differences while preserving diagnostically relevant texture and structural features. When applied to histopathological images from the Camelyon17-WILDS benchmark, PhyCV preprocessing improves out-of-distribution breast-cancer classification accuracy from 70.8% (Empirical Risk Minimization baseline) to 90.9%, matching or exceeding data-augmentation and domain-generalization approaches at negligible computational cost. Because the transform is physically interpretable, parameterizable, and differentiable, it can be deployed as a fixed preprocessing stage or integrated into end-to-end learning. These results establish PhyCV as a generalizable data refinery for medical imaging-one that harmonizes heterogeneous datasets through first-principles physics, improving robustness, interpretability, and reproducibility in clinical AI systems.
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All authors Callen MacPhee, Yiming Zhou, Koichiro Kishima, Bahram Jalali

Physics and Society

Flow Taxes, Stock Taxes, and Portfolio Choice: A Generalised Neutrality Result

Anders G Frøseth

A proportional wealth tax - a levy on the stock of wealth - preserves portfolio neutrality by acting as a uniform drift shift in the Fokker-Planck equation for wealth dynamics. We extend this result to the full system of ownership taxes (eierkostnader) that a shareholder faces: a corporate tax on gross profits, a capital income tax on the risk-free return, a dividend and capital gains tax on the excess return, and a wealth tax on net assets. Each tax modifies the drift of the wealth process in a distinct way - multiplicative rescaling, constant shift, or regime-dependent compression - while leaving the diffusion coefficient unchanged. We show that the combined system preserves portfolio neutrality under three conditions: (i) the capital income tax rate equals the corporate tax rate, (ii) the shielding rate equals the risk-free rate, and (iii) the wealth tax assessment is uniform across assets. When these conditions hold, the after-tax excess return is a uniform rescaling of the pre-tax excess return by the factor $(1-\tau_c)(1-\tau_d)$, and the drift-shift symmetry of the wealth-tax-only case generalises to a drift-shift-and-rescale symmetry. We classify the distortions that arise when each condition fails and show that flow-tax distortions and stock-tax distortions are additively separable: they do not interact. The shielding deduction - a feature of several real-world tax systems, including the Norwegian aksjonaermodellen - emerges as the mechanism that restores the symmetry between equity and debt taxation within this framework. Calibrated to the Norwegian dual income tax, conditions (i) and (ii) hold by institutional design; the only binding distortion is non-uniform wealth tax assessment, which generates portfolio tilts roughly 300 times larger than any residual flow-tax channel.
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Optics · Cross-listed from quant-ph

Simultaneous amplitude and phase spectroscopy using two-photon interference

Kyle M. Jordan, Yingwen Zhang, Frédéric Bouchard et al. (+5 more)

Quantum spectroscopy seeks to probe chemical systems using nonclassical light, which has properties that are qualitatively and quantitatively different than conventional light sources. One promising technique uses intensity-correlated twin beams of light to reduce the noise sources inherent to absorption spectroscopy. However, measurements of the phase shift imparted by the chemical sample, which provides complementary information to the absorption, continue to be a challenge. Here, we propose and demonstrate a scheme using entangled photon pairs that can simultaneously measure both the absorption and phase shift of a sample with extremely low optical intensities and with relatively fast few-minute acquisition times. This method combines the previous use of intensity correlations with a broadband quantum interferometer utilizing two-photon interference to measure the complete linear optical response of the sample. Our work shows that precise measurements of absorption can also be made phase-sensitive using suitable choices of probe beam and detection scheme. This enables a new class of quantum spectroscopy schemes which measure absorption and phase with a single probe. Our technique is relevant to the characterization of a wide array of chemical and biological samples, such as quantum dots and organic fluorophores, and may be useful for spectroscopic measurements that are otherwise constrained in intensity.
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All authors Kyle M. Jordan, Yingwen Zhang, Frédéric Bouchard, Duncan England, Philip J. Bustard, Benjamin J. Sussman, Jeff S. Lundeen, Andrew H. Proppe