Physics and Society
What Do City Codes Say About Climate Risk?
Arianna Salazar-Miranda
Climate change is intensifying natural hazards, and preparing cities for them falls primarily to local governments. Yet what municipal codes say about hazards, and whether their requirements match each city's risk profile, has not been measured. I analyze 3.6 million sentences from 204 U.S. cities' municipal codes and compare each city's hazard text to its actual risk from FEMA's National Risk Index. I document four patterns. First, a small share of code text consists of provisions relevant for natural hazards (1.5%), and codes in high-risk cities contain marginally more. Second, hazard coverage is highly concentrated on flooding (61% of hazard-relevant text), even though flooding accounts for only 9% of the average city's risk. Third, city codes emphasize emergency response over prevention. Emergency management is the largest regulatory category, and land use is the smallest. Fourth, codes track the types of risks relevant to each location, but only loosely. The median city would need to reallocate 70% of its regulatory text to match its risk profile. The results suggest that U.S. city codes do not include regulation for most of the hazards cities face.
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Medical Physics
High-spatial resolution, high-quality white matter tractography using DTI with dynamic slice-by-slice B0 shimming in a head-only high-gradient performance 3T MRI scanner
Jerome J. Maller, Patricia Lan, Sherry Huang et al. (+4 more)
Data from conventional
diffusion tensor imaging (DTI) using single-shot echo planar imaging (SS-EPI) acquisition are substantially influenced by
magnetic field inhomogeneities (delta B0), which result in image distortion and signal dephasing. Multi-shot EPI can mitigate the delta B0-induced artifacts but at the cost of increased scan time. Recent
brain tissue-selective, dynamic slice-by-slice B0 shimming techniques have demonstrated effective reduction of local delta B0 in the
brain. When combined with DTI utilizing an echo-planar imaging (EPI) read-out, image distortion and signal dephasing are significantly reduced. The purpose of our study was to assess the impact of DTI with dynamic slice-by-slice B0 shimming technique (DySiBo) on white matter (WM) tractography. We retrospectively analyzed DTI
datasets using SS-EPI and Multi-shot EPI with 2 shots (MS-2shot-EPI) readout at two spatial resolutions (1x1x2mm3 and 2x2x2mm3) with and without DySiBo. WM tractography was generated and inspected to examine the impact upon regions typically affected by delta B0-induced artefacts. We found more WM streamlines were generated in the DTI
datasets with DySiBo in regions conventionally impacted by delta B0-induced in EPI images, including the brainstem, temporal and frontal lobes. DySiBo substantially improved the generation of WM streamlines in DTI-based tractography at both in-plane resolutions. In conclusion, DySiBo in conjunction with DTI requiring 10
diffusion tensor directions is sufficient to generate data with high enough SNR and angular resolution to resolve crossing fibers and produce high quality WM tractography in
brain regions typically affected by susceptibility-induced artefacts. This has implications for quantitative WM microstructural indices and clinical evaluation of WM tracts in patients.
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All authors Jerome J. Maller, Patricia Lan, Sherry Huang, Chitresh Bhushan, Xinzeng Wang, Ante Zhu, Vincent A. Magnotta
Plasma Physics
Applications of Poincaré Boundary Condition for 3D Ideal MHD Equilibrium and Optimization
Yigit Gunsur Elmacioglu, Dario Panici, Rory Conlin et al. (+2 more)
Stellarator ideal magnetohydrodynamic (MHD) codes that assume nested flux surfaces such as VMEC and DESC solve the
equilibrium problem by prescribing the total toroidal
magnetic flux,
plasma profiles and the last closed flux surface (LCFS), which analytically determines the unique field in
vacuum, whereas at finite $\beta$ bifurcations and distinct
equilibria sharing the same boundary have been reported in the literature. In this paper, we propose prescribing the Poincaré cross-section of the field at a single toroidal plane, and implement it in DESC, where the new condition enters only through the linear constraints and therefore costs no more than a fixed-LCFS solve. Fixing the geometry on one plane rather than on a full toroidal surface generally leaves more of the spectral coefficients free, and the ones it frees are those carrying the toroidal variation of the boundary flux surface, which a prescribed LCFS holds fixed at every toroidal angle; together these allow better-converged numerical solutions. We solve
equilibria with the cross-section held fixed, starting either from the axisymmetric shape obtained by revolving that cross-section toroidally, or from an existing fixed-LCFS solution. In the latter case, the volume-averaged normalized force error falls by an order of magnitude while the configuration stays close to the original one, and re-solving the resulting boundary with the conventional fixed-LCFS solver recovers the same
equilibrium. We further show that the Poincaré coefficients can be used directly as design variables by optimizing a quasi-helical configuration that maintains high-fidelity force balance throughout the process.
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All authors Yigit Gunsur Elmacioglu, Dario Panici, Rory Conlin, Daniel Dudt, Egemen Kolemen
Instrumentation and Detectors
Non-Ionizing Radiation Measurements for Trajectography Radars
J. Marcos Leal Barbosa Filho, Millena M. de M. Campos, Daniel L. Flor et al. (+4 more)
This work presents a Non-Ionizing Radiation (NIR) measurement campaign and proposes a specific measurement method for trajectography radars. This kind of radar has a high gain narrow beam
antenna and emits a high power signal. Power density measurements from a C-band trajectography radar are carried out using bench equipment and a directional receiving
antenna, instead of the commonly used isotropic probe. The measured power density levels are assessed for compliance test via comparison with the occupational and general public exposure limit levels of both the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Brazilian National Telecommunication Agency (Anatel). The limit for the occupational public is respected everywhere, evidencing the safe operation of the studied radar. However, the limit for the general public is exceeded at a point next to the radar's
antenna, showing that preventive measures are needed.
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All authors J. Marcos Leal Barbosa Filho, Millena M. de M. Campos, Daniel L. Flor, William S. Alves, Adaildo G. D'Assunção, Marcio E. C. Rodrigues, Vicente A. de Sousa Jr
Computational Physics
Moment hierarchy and exact steady-state solutions in a Callaway lattice Boltzmann model for phonon hydrodynamics
Shimpei Saito
We analyze the moment hierarchy of a Callaway
lattice Boltzmann model for
phonon hydrodynamics and derive exact steady-state solutions for a driven planar channel with diffuse walls. The collision operator decomposes the population space into conserved, heat-flux, and fast kinetic sectors, whose coupling through streaming determines the transport response. For the two-dimensional, eight-velocity (D2Q8)
lattice Boltzmann model, we derive a fully discrete closure that relates the heat flux to transverse kinetic moments. The higher-order transverse kinetic moment contains both a second-difference term and an explicit contribution from the imposed energy drop. Diffuse-wall population constraints then determine the heat-flux and kinetic-moment profiles without fitted parameters. The resulting solution reproduces the numerical bulk moment amplitudes and wall slip, while an exact wall relation separates the contribution of the higher-order moment from deviations from the leading gradient approximation. Finite-wave-number analysis further resolves the collision-sector mixing associated with longitudinal propagation. These results provide a unified description of collision relaxation, the moment hierarchy, and boundary response within the specified discrete model.
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Plasma Physics
Bayesian Active Learning of Ion Loss-Cone Boundaries in Tokamaks
Omar E. Lopez, Minglei Yang, Mark Cianciosa et al. (+1 more)
Loss-cone boundary determination in tokamaks is cast as an active learning problem in which a
Bayesian logistic regression model with radial basis function features acts as the learner and the guiding-center orbit integrator acts as the labeling method. The approach is applied to an analytic tokamak
equilibrium across a mesh of launch positions, producing a database of loss-probability models with approximate posterior uncertainty, each generated within a prescribed trajectory budget. Once generated, the database supports downstream applications, illustrated here with three examples. First, integrating the probability models against a Maxwellian distribution yields the lost-ion fraction and the energy and parallel momentum carried by lost ions, with posterior uncertainty propagated analytically to each integral. Second, a steady balance between the resulting orbit-loss torque and radial angular-momentum
diffusion gives co-current edge rotation whose amplitude is set mainly by the prescribed momentum diffusivity and loss-region renewal rate. Third, a neural network surrogate trained on the database learns the in-domain mapping from launch position to loss-probability image, and transport integrals computed from its predictions closely reproduce the
Bayesian reference values on held-out samples from the same mesh.
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All authors Omar E. Lopez, Minglei Yang, Mark Cianciosa, Gary M. Staebler
Plasma Physics · Cross-listed from astro-ph.HE
Fast Radio Bursts from Induced Upscattering. I. Magnetar Polar Fireballs
Rei Nishiura, Kunihito Ioka and Bing Zhang
The extreme brightness temperatures of fast
radio bursts (FRBs) demand a coherent process that converts magnetar burst energy into millisecond
radio emission. We propose that FRBs can be produced within magnetar magnetospheres by induced (stimulated) upscattering in a relativistic fireball outflow. In this paper, we focus on induced Compton upscattering in an electron–positron fireball launched from the polar region of a magnetar. Radiation from the X-ray burst accelerates the polar fireball outflow to Lorentz factors of $\Gamma\sim10$–$10^3$. Low-frequency seed waves, such as fast magnetosonic or Alfvén waves, entering the outflow from the side or against its motion undergo induced scattering and are Lorentz-boosted by the relativistic bulk motion from $\nu_0\sim10\mathrm{kHz}$ to $\nu_{\rm obs}\sim\Gamma^2\nu_0\sim\mathrm{GHz}$. Combining the polar fireball dynamics with the linear growth and nonlinear saturation of the induced scattering instability, we derive the FRB luminosity $L_{\rm FRB}^{\rm iso}$ and fractional spectral bandwidth $\Delta\nu/\nu_{\rm c}$. By considering the possible range of pair densities and temperatures, we find that this polar channel can account for the luminosity of Galactic FRB~20200428 and reach luminosities comparable to those of the brightest extragalactic FRBs. If the pair-loaded region is narrower than the relativistic beaming angle $1/\Gamma$, the model also produces a narrow spectrum and predicts $L_{\rm FRB}^{\rm iso}\propto(\Delta\nu/\nu_{\rm c})^2$, a trend consistent with observations of repeating FRBs. The induced upscattering model thus connects magnetar X-ray bursts to FRBs through a coherent emission process grounded in
plasma physics and makes observationally testable predictions.
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Space Physics
Temporal Correlation between Ionospheric Storm-Enhanced Density Plume and Plasmaspheric Plume Occurrence
Xiangning Chu, Shunrong Zhang, Jacob Bortnik et al. (+5 more)
We present a statistical evidence of a temporal correlation between ionospheric storm-enhanced density (SED) and plasmaspheric plumes during
magnetic storms. We identified SED plumes in 75 storms between 2010-2024 with sufficient total electron content (TEC) coverage. We also identified plasmaspheric plumes during these storms using a plasmapause asymmetry (PPA) index derived from the machine-learning-based DEN3D model. We found that all SED plumes coincided with plasmaspheric plumes. The start and end times of both phenomena exhibit near-zero lag within a half-hour delay, confirming their synchronized
evolution. For the first time, superposed epoch analyses reveal that plume onsets align with solar wind driving and geomagnetic activity, including peaks in the electric field, coupling function, auroral electrojet indices, and the asymmetric ring current index, all of which facilitate plume formation. This work provides timely new insights into magnetosphere-ionosphere coupling processes and demonstrates the utility of machine-learning-based diagnostics for space physics/weather.
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All authors Xiangning Chu, Shunrong Zhang, Jacob Bortnik, Naomi Maruyama, Jerry Goldstein, Kausik Chatterjee, David Malaspina, Phil Erickson
Plasma Physics
Electron Density Measurements from Stark Broadened Emission in a Sodium Plasma Produced by Laser Resonance Saturation
Mark A. Cappelli
Electron Stark broadening of the $4^2D$–$3^2P$ multiplet transition in a sodium
plasma produced by
laser resonance saturation has provided a means of undertaking the first spatial measurements of the free electron density across and along the
plasma channel created in sodium vapor of density $10^{15}$–$5\times10^{16}$~cm$^{-3}$. From these measurements and measurements of the neutral sodium density within a heat sandwich oven, we are able to deduce the corresponding electron temperature. These temperatures compare favourably with the electron temperature estimated from a Boltzmann analysis of line intensities and suggest that a highly ionized ($>$10%)
plasma of electron temperature $<$6000K can be produced within 100~ns of
laser excitation from a
laser of modest irradiance ($10^6$–$10^7$~Wcm$^{-2}$). The experimental results are in reasonable agreement with a recently developed 3-dimensional model which predicts a decrease in the degree of ionization along the path of the
laser beam as a result of significant depletion of
laser energy. These experimental results demonstrate that this LIBORS code is capable of predicting the 3-dimensional nature of this new mode of
laser ionization with reasonable accuracy, and may also explain the low electron temperatures and free electron densities observed by other research teams.
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Instrumentation and Detectors
Design and Analysis of a 2D Vernier Structure
Hüsna Yildiz and Rick Helmer
This paper presents the design and simulation of a 2D Vernier Time-to-Digital Converter (TDC) targeting less than 20 picosecond time resolution and 5-bit output resolution. The TDC comprises voltage-controlled delay buffers, NAND-based SR latches with reset functionality, and a calibration loop using a phase-frequency detector (PFD) and charge pump. The calibration loop dynamically adjusts delay mismatches to maintain consistent timing across process-voltage-temperature (PVT) corners, significantly improving linearity. Simulations show that the TDC achieves a resolution of 16.9 ps for tt corner and maintains DNL and INL below 0.5 LSB under all tested PVT conditions
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Geophysics
Climate-informed cryospheric reanalysis via hierarchical Bayesian data assimilation
Kristoffer Aalstad, Esteban Alonso-González, Joel Fiddes et al. (+7 more)
The cryosphere regulates global cycles of water, energy, and carbon, affecting societies and ecosystems. By assimilating observations into models, we can infer the past trajectory of state variables, generating a cryospheric reanalysis. Existing cryospheric reanalyses typically treat each water year independently, with no pooling of information across years. With sparse and noisy observations, such '
climate-assumed' reanalyses perform poorly, reverting to an assumed yet uncalibrated background climatology. Conversely,
Bayesian calibration with static parameters completely pools information across water years, inferring climatological parameters without capturing inter-annual variability. Here, we propose a new hierarchical
Bayesian approach using partial pooling, which we coin '
climate-informed' cryospheric reanalysis. It jointly infers state trajectories, annual parameters, and local climatological hyperparameters using a nested hybrid particle smoothing workflow. We test the approach through three experiments by assimilating in situ snow water equivalent, satellite-based fractional snow-covered area, and glacier-wide mass balance data into a temperature index model at eight study areas, from the Swiss Alps to the High Arctic. Hierarchical reanalysis with partial pooling outperforms annually independent cryospheric reanalysis (no pooling) and static parameter calibration (complete pooling) for all experiments during calibration and for all but one during validation. Overall, it yields a 51% improvement in continuous ranked probability score relative to the prior, markedly exceeding that of annual reanalysis (38%) and static calibration (19%). Compared to a particle Markov chain Monte Carlo
benchmark, our workflow reduces computational cost by several orders of magnitude through recycling and expectation maximization, with comparable or improved skill.
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All authors Kristoffer Aalstad, Esteban Alonso-González, Joel Fiddes, Brian Groenke, Gregoire Guillet, Regine Hock, Bartłomiej Luks, Norbert Pirk, Sebastian Westermann, Yeliz A. Y{\i}lmaz
Computational Physics
Permeability and microcrack geometry: Dynamic loading induced evolution
Rigoberto Moncada and Efrem Vitali
We propose a crack-geometry-based model for permeability
evolution in rocks under dynamic loading. Accurate representation of permeability is important for fluid extraction and containment in geological formations, but remains challenging because low-porosity brittle rocks are highly sensitive to changes in pore geometry and connectivity, while dynamic permeability measurements are limited. Rock void space is represented as an evolving network of penny-shaped cracks with prescribed orientations. Permeability changes are described through crack microvariables including aperture, length, and crack distance. The model accounts for crack opening and closure, fracture-energy-driven propagation, plastic-strain-driven nucleation, coalescence after full connectivity is reached, and strain-rate-dependent fracture toughening. The evolving crack network directly modifies connectivity, fluid conductance, and preferential flow paths. The formulation is implemented in the GeoDyn hydrocode and evaluated under tension, shear, compression, and symmetric impact loading. Results show a strong relation between permeability and crack length, with crack propagation playing a major role in permeability enhancement. Permeability growth can nevertheless be limited by poor connectivity and crack closure. The model captures changes of several orders of magnitude depending on stress state, strain rate, crack orientation, and connectivity, consistent with observed behavior of brittle rocks under high strain-rate loading.
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Data Analysis and Statistics · Cross-listed from hep-ph
Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios
Sean Benevedes, Mani Dehghan, Aishik Ghosh et al. (+1 more)
We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the computational cost of inference and preserving some or all of the reliability guarantees of parametric methods. The first approach is broadly applicable, while the second is tailored to a class of particle physics analyses that admit a semi-parametric NSBI formulation. With only a modest compromise in raw sensitivity, these methods represent an important step toward computationally efficient NSBI in offline analyses and also open the door to the exploration of trigger-level applications in the future. Based on our comparison studies, we recommend the use of our first approach, Latent Categories, for robust and efficient inference.
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All authors Sean Benevedes, Mani Dehghan, Aishik Ghosh, Tae Hyoun Park
Physics and Society · Cross-listed from cs.SI
Group dynamics of engagement with AI topics on Bluesky
Bradley Huynh, Moyi Tian and Nancy Rodríguez
Social media increasingly shapes everyday life, serving as both a central venue for discussion of major events and a space where online collective behavior can spill over into real-world activity, while artificial intelligence (AI) is likewise becoming increasingly influential across society. Understanding how different online communities respond to AI-related events, and disentangling the mechanisms underlying the development of such engagement, are therefore increasingly important for studying information spreading and the societal reception of AI. Our work addresses the limited connection between empirical studies of AI-related online engagement and mathematical modeling of group-level spreading dynamics. We develop a framework to collect and organize empirical Bluesky activity into distinct user groups, then use a network-based dynamics model to investigate the mechanisms underlying their engagement. We use the release of DeepSeek R1 as a case study under two complementary grouping schemes: AI-related communities and academic disciplines. For each group, we fit a network-based Susceptible-Infected-Recovered (SIR)-type model augmented with an exogenous engagement term, allowing us to quantify the relative strengths of endogenous network-driven spreading and direct external response. Across groups, we find that strong direct responses to the event do not necessarily coincide with strong network-driven propagation, revealing distinct engagement patterns that may be obscured by aggregate activity alone.
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Fluid Dynamics · Cross-listed from cond-mat.stat-mech
Nonreciprocal Chiral Automata
Andrew A. Allocca, Armin Rahmani, Pouyan Ghaemi et al. (+1 more)
Odd pressure is a parity-odd transport coefficient that gives an isotropic pressure response to vorticity in compressible two-dimensional fluids. By asymmetrically coupling vortical and compressional modes, it provides a direct mechanism for a nonreciprocal hydrodynamic response reminiscent of several biological systems. Yet microscopic models realizing odd pressure as a transport coefficient are relatively scarce. Here, we construct one such model using a
lattice-gas cellular automaton based on the Frisch-Hasslacher-Pomeau II model with rest particles and chiral collisions, whose Chapman-Enskog coarse-graining produces a nonzero odd pressure coefficient. The key ingredient is a local parity-breaking collision that weakly rotates moving particles in the presence of a rest particle. At hydrodynamic scales, this microscopic rule acts as an effective
magnetic field, converting the model's bulk viscosity into odd pressure. More generally, we derive expressions relating Hall viscosity, odd pressure, and odd torque to their parity-even counterparts in our model.
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All authors Andrew A. Allocca, Armin Rahmani, Pouyan Ghaemi, Sriram Ganeshan
Computational Physics · Cross-listed from astro-ph.EP
GameDev: GPU-accelerated model for dust evolution
Jiaqing Bi
Grain growth and fragmentation through dust collisions in protoplanetary disks are strongly coupled with dust dynamics. This is because the spatial and velocity distributions of dust set the collision rates and outcomes, while dust grain sizes set the aerodynamic coupling with gas. However, existing dust
evolution codes often rely on prescribed dust velocities and are mostly restricted to one or two spatial dimensions. In this work, we present GameDev, a dust
evolution model accelerated by graphics processing units (GPUs) that couples independently evolved three-dimensional dust dynamics with Monte Carlo collisional
evolution of dust. In GameDev, we model dust as Lagrangian representative particles in a prescribed gas disk. We integrate particle trajectories with the staggered semi-analytic method, which remains accurate for both tightly and weakly coupled dust grains. We estimate collision rates from each particle's nearest neighbors rather than on a grid, preventing physically close particles from being excluded from collision sampling because they lie across a grid boundary. Most importantly, we sample collision events against neighborhoods that remain frozen over adaptive intervals, enabling massive parallelization across particles. These implementations make GameDev an accurate and efficient tool for studying dust
evolution in protoplanetary disks. GameDev supports both NVIDIA CUDA and AMD ROCm platforms, provides a smaller-scale standalone Eulerian dust fluid model, and is publicly available on GitHub.
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Atmospheric and Oceanic Physics
A neural network-based Universal Thermal Climate Index for reliable global thermal-stress classification across extreme weather
Bikem Pastine, Milan Klöwer, Tianning Tang et al. (+2 more)
Extreme temperatures are the leading cause of
climate-related mortality world-wide.
Climate-health research and operational weather forecasting require accurate estimates of human thermal stress. The Universal Thermal
Climate Index (UTCI) is among the most sophisticated and widely used feels-like temperature metrics. However, its ubiquitous
polynomial approximation does not generalize well to extreme weather conditions. Here, we introduce Neural-UTCI, a neural network that calculates UTCI with substantially higher accuracy across global conditions at a lower computational cost for operational use. Neural-UTCI reduces the
polynomial approximation RMSE from 2.78{\deg}C to 0.36 {\deg}C, an 87% improvement, and lowers thermal stress misclassification rates from 5.3% to 1.7%, with consistent performance across resampling experiments. These differences affect thermal exposure metrics. For example, during the 2003 European heatwave summer in Rome, Italy, the number of very strong heat stress days increases from 15 to 35 days when using Neural-UTCI compared to operational products like ERA5-HEAT. Simultaneously, Neural-UTCI reliably classifies extreme cold stress conditions, allowing continuous global application. By improving UTCI accuracy, Neural-UTCI can strengthen
climate-health risk assessments and public weather warning systems, especially as global warming increases the incidence of extreme events.
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All authors Bikem Pastine, Milan Klöwer, Tianning Tang, Sarah Wilson Kemsley, Louise Slater
Fluid Dynamics
A Tensorial Extension of Fractional Dissipation at Inertial Scales
José I. H. López
We formulate a scale dependent tensorial extension of a fractional dissipation operator motivated by a macroscopic Navier Stokes correspondence. The starting point is a fractional model in which the order of dissipation decreases continuously from the
Laplacian value toward the Kolmogorov value as a local Reynolds number increases. At the critical value of the local Reynolds number, the model reduces to an isotropic operator. We then ask whether the same macroscopic description can be continued into a regime in which velocity fields have Onsager, critical or subcritical regularity without introducing an unrelated closure or an additional isotropic dissipation scale. In addition, we extend the original AFNS free, energy, construction by one nonnegative concentration order parameter c. The new term is quadratic in c and linearly coupled to the defect beta function, so that minimization leaves the original AFNS free energy exactly unchanged when the concentration branch is inactive. The resulting three regime mosaic is regular, inertial, and concentrated/anomalous. The construction uses the coarse-grained stress and its critical normalization. The normalized anisotropy tensor provides the lowest order objective tensorial information available at the critical scale, while the scale derivative of the Duchon Robert energy defect, supplies a scalar measure of departure from the Onsager threshold. We propose the minimal constitutive deformation of the critical operator: in Weyl quantization, the isotropic fractional symbol is dressed by this exponential tensorial factor, giving a pseudodifferential operator that reduces to the scalar critical operator. The exponential parametrization guarantees positive
eigenvalues and unit determinant for symmetric traceless, so the deformation redistributes dissipation among directions without introducing a new isotropic amplitude.
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Geophysics
AutoCF: An Automated LLM-Assisted Ecosystem for Compound Flood Simulation, Evaluation, and Impact Attribution
Soheil Radfar, Faezeh Maghsoodifar, Ning Lin et al. (+1 more)
Compound coastal flooding (CCF) arises from interacting coastal, precipitation, and river processes, yet modeling workflows often separate simulation, evaluation, and impact analysis. We present AutoCF, an automated ecosystem integrating data harmonization, model construction, observational evaluation, exposure analysis, complete factorial driver attribution, and cross-platform execution. The automated Hurricane Harvey simulation achieves a median root mean square error of 0.147 m and correlation of 0.951 across eight observational gauges, and a correlation of 0.942 with 55 high-water marks. Maximum water-level fields from CPU and GPU implementations agree within 0.01 m for 98.8% of
cells. Attribution analysis shows that during Harvey, precipitation dominated building and population exposure, whereas coastal forcing becomes increasingly important for deep and persistent inundation. The introduced Driver Impact Shift metric further quantifies whether each driver contributed disproportionately to societal consequences relative to its flooded-area contribution. Overall, AutoCF provides a reproducible pathway from CCF model construction to evaluation and driver-specific impact interpretation.
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All authors Soheil Radfar, Faezeh Maghsoodifar, Ning Lin, Hamed Moftakhari
Atmospheric and Oceanic Physics
Explainable Deep Learning for Probabilistic Nowcasting of Radar Reflectivity in Tornadic Storms
Nathan Erickson, Amy McGovern and Aaron Hill
Tornadoes pose substantial risk to human life and property in the United States, causing more than 50 fatalities and \$100 million of property damage on average annually. When tornadoes are likely, weather radar provides critical information for forecasters by providing information on storm morphology, storm motion, and intensity trends. Additional tools such as satellite and numerical weather prediction model runs can provide useful short-term information for understanding changes in storm characteristics. This work demonstrates a U-Net deep-learning system for nowcasting the
evolution of radar reflectivity following tornadogenesis, which can provide value to forecasters by synthesizing large amounts of input data (e.g., radar imagery, near-storm environment data) and generating predictions of radar reflectivity from its inputs. Inputs to the model are radar imagery from the Multi-Radar Multi-Sensor (MRMS)
dataset and near-storm environment data from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model. The U-Net is trained on a
dataset of tornadic storms to produce 30 minutes of probabilistic predictions of radar reflectivity following tornadogenesis, with probabilistic predictions obtained by predicting parameters of the SinhArcSinh, or SHASH, distribution. The model produces physically realistic predictions of radar
evolution, achieves comparable skill to next-hour forecasts from the HRRR, demonstrates reasonable probabilistic calibration and is accompanied by a variety of explainability methods to improve understanding by end users. Additionally, predictions from the model can be obtained much more quickly than those from a numerical weather prediction model. With further development, this model could be extended to nowcast radar reflectivity
evolution in an operational setting.
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Computational Physics · Cross-listed from astro-ph.IM
Accelerating massive ensembles of ordinary differential equations
Lawrence Berry, Will Handley, Oliver Hahn et al. (+1 more)
Solving large ensembles of small, independent ordinary differential equations (ODEs) is a common task in computational science and engineering, arising for example in
Bayesian parameter estimation, Monte Carlo uncertainty quantification, and the integration of uncoupled physical systems such as the linearised Einstein-Boltzmann equations of cosmology. Modern graphics processing units (GPUs) with thousands of cores are well suited to such parallel workloads, but realising this potential requires careful
attention to GPU-specific architectural constraints. We present modax, a Python library of GPU-accelerated ODE solvers specifically optimised for solving large ensembles of low-dimensional, independent problems. Our solvers are compatible with the JAX ecosystem but are written in a low-level, thread-based programming paradigm better suited to ensembles of highly divergent trajectories than their pure-JAX counterparts.
Benchmarks on the Lorenz, Robertson and van der Pol
lattice systems compare modax against diffrax, DiffEqGPU$.$jl and torchdiffeq across ensemble size, dimensionality, and trajectory divergence. Our explicit Tsit5 solver achieves 30x speed-up over diffrax on Lorenz systems, and our implicit Rodas5P solver achieves over 700x speed-up on Robertson systems, demonstrating the superiority of linearly implicit Rosenbrock-Wanner methods on GPUs. Our implicit solver scales well to higher dimensions thanks to the use of sparsity-exploiting techniques and data structures. We conclude by applying modax to three examples from the field of cosmology -
Bayesian parameter estimation from primordial abundances, Monte Carlo uncertainty quantification of the global 21cm signal, and the computation of uncoupled
Fourier modes in the primordial power spectrum - and demonstrate significant efficiency improvements in our ability to model physical phenomena described by low-dimensional (<200D) ODEs.
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All authors Lawrence Berry, Will Handley, Oliver Hahn, Nils Schöneberg
Instrumentation and Detectors
Electrothermal behavior of superconducting nanowires buried in a commercial CMOS process
Mohamed Gharib, Leonid Popryho, Salma Abdelzaher et al. (+14 more)
Superconducting films native to a commercial CMOS process enable co-integration of superconducting devices (high-kinetic-inductance elements and nanowire detectors) with cryogenic CMOS on one monolithic die. Such films are buried in the front-end-of-line, beneath the back-end-of-line metal stack, an environment that might quench a self-heated hot spot. Current-voltage characteristics are reported for titanium nitride (TiN) nanowires in the polycrystalline-silicon resistor layer of a 22 nm FD-SOI process, and measured retrapping currents are compared with thermal models for longitudinal conduction to the contacts and interfacial
phonon cooling into the stack. The wires are strongly hysteretic, with switching-to-retrapping current ratios I_sw/I_r of 7.4-9.8, sustaining a normal hot spot. For two wires of length ell = 50 micrometers and widths W = 0.50 and 1.00 micrometers, over bath temperatures T_b = 0.15-1.19 K, I_r follows the interfacial form (T_hs^n - T_b^n)^(1/2) with n = 4 (T_hs, the effective hot-spot temperature), and is strongly inconsistent with the (T_hs - T_b)^(1/2) constant-kappa longitudinal-conduction limit; free-exponent fits give n = approximately 4.8-5.0. An effective cooling coefficient Sigma_K = 7.9(3) W/(m^2 K^4) describes the data: 31(21) times below the acoustic- (diffuse-) mismatch value for a single clean interface, and approximately 12 times below the lowest previously reported comparable nanowire coefficient. The model-based film thermal conductivity is kappa = approximately 20 mW/(m K). Across lengths ell = 1-50 micrometers, I_r matches neither ell^(-1) of pure longitudinal conduction nor ell^0 of pure interfacial cooling; a two-channel model reproduces I_r(ell) with crossover length ell* = approximately 3.5 micrometers predicted, to an O(1) prefactor, from Sigma_K and kappa.
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All authors Mohamed Gharib, Leonid Popryho, Salma Abdelzaher, Tejas Guruswamy, Tomas Polakovic, Umeshkumar Patel, Orlando Quaranta, Thomas Cecil, Clarence Chang, Yu-Sheng Chen, Thomas H. Swift, Grayson M. Noah, Alberto Gomez-Saiz, John J. L. Morton, M. Fernando Gonzalez-Zalba, Antonino Miceli, Inna Partin-Vaisband
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Density functional perturbation theory of meta-generalized gradient approximations using algorithmic differentiation
Bruno Ploumhans, Niklas Frederik Schmitz and Michael F. Herbst
Density functional perturbation theory (DFPT) is an established framework for the computation of derivatives in plane-wave density functional theory (DFT). We present an implementation of DFPT for exchange-correlation (XC) functionals $E_\mathrm{xc}(\rho,\tau)$ that incorporate an explicit dependence on both the density $\rho$ and the kinetic energy density $\tau$. This covers the popular class of semilocal meta-generalized gradient approximations (meta-GGAs) as well as broader nonlocal parametrizations. We sidestep the derivation of cumbersome XC second energy derivative expressions by recasting these derivatives as a Jacobian-vector product of the XC potentials, which we evaluate with algorithmic differentiation (AD) techniques. Integration with our previously developed AD-DFPT framework [N. F. Schmitz et al., npj Comput. Mater. 12, 6 (2026)] provides access to derivatives of arbitrary ground state quantities with respect to arbitrary perturbations. We employ AD-DFPT to compute a range of response properties for ZnO and BaTiO3, and find that the recent r2SCAN01 meta-GGA functional generally outperforms LDA and PBE. Finally, we showcase the optimization of a neural-network meta-GGA to self-consistently reproduce hybrid-DFT reference densities of bulk silicon, using AD-DFPT gradients. Overall, these results establish AD-DFPT as a versatile route for computing DFT derivatives at the meta-GGA level, be they common response properties or the unusual derivatives required for the gradient-based training of novel XC functionals.
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Fluid Dynamics
Conservative local grid refinement for the vectorial lattice Boltzmann method
S.A. Hosseini, R. Strassle and I.V. Karlin
We present a conservative local grid-refinement coupling for the vectorial
lattice Boltzmann method (VLBM), a kinetic-type scheme for
hyperbolic conservation laws in which each conserved field is carried by its own population rather than by moment truncation of a Maxwellian. Coarse and fine regions share a common link speed and are advanced with different time steps, sub-cycled at a fixed ratio; a mean-preserving reconstruction in time supplies the missing coarse-to-fine boundary data, and a matched, Berger–Colella-style reflux returns the fine-to-coarse data, together conserving mass, momentum, and energy exactly, independent of the equation of state, the local relaxation parameter, or the time step. In addition, we propose an adaptive mesh refinement extension through a conservative pair of splitting and merging operators that require no modification to the underlying coupling. The approach is validated on a sequence of increasingly demanding two-dimensional cases, in every case recovering exact conservation and the expected accuracy gains over an equivalent uniform grid.
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Instrumentation and Detectors
A high-flux electron detection system to measure non-linear Compton scattering at LUXE
Antonios Athanassiadis, Oleksandr Borysov, Florian Burkart et al. (+16 more)
This paper presents the development and testing of a high-flux electron detection system designed to measure the energy spectrum of more than $10^9$ electrons from
laser-electron collisions at the LUXE experiment, planned at DESY. The system is intended to enable precision measurements of non-linear Compton scattering in the strong-field regime of
quantum electrodynamics. It combines a scintillating screen observed by a camera system with a spatially segmented detector based on the Cherenkov effect. Prototype tests were conducted at two accelerator facilities, where the performance of the system was evaluated under realistic beam conditions. The results demonstrate the feasibility of the detector concept, characterize its current performance and limitations, and provide input for the optimization and final design of the detection system to be used in the experiment.
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All authors Antonios Athanassiadis, Oleksandr Borysov, Florian Burkart, Hannes Dinter-Habermeier, John Hallford, Beate Heinemann, Louis Helary, Luke Hendriks, Ruth Jacobs, Max Kellermeier, Willi Kuropka, Jenny List, Frank Mayet, Gudrid Moortgat-Pick, Evan Ranken, Stefan Schmitt, Ivo Schulthess, Thomas Vinatier, Matthew Wing
Instrumentation and Detectors
Event-by-event track imaging of charged particles with an ultrafast plenoptic camera
Till Dieminger, Marco Barbieri, Vincenzo Berardi et al. (+8 more)
Modern elementary particle detectors often require high-resolution three-dimensional particle tracking in large dense active volumes, which is difficult to achieve in standard devices without an extremely fine segmentation. In recent work, a plenoptic camera instrumented with a single-
photon avalanche-diode array, called PLATON, demonstrated to image individual visible
photons generated in monolithic scintillating material and reconstruct their three-dimensional origin from a single-event exposure, opening a route to high-spatial-resolution detection of elementary particles in unsegmented scintillator. However, those tests aimed to address
photon sources of essentially zero
geometric extent. In this work we close the gap to the tracking regime. First, we calibrated the PLATON prototype using light tracks in an organic plastic scintillator induced by a femtosecond infrared
laser via two-
photon absorption and characterised its capability to reconstruct
photon-starved 3D lines with a novel
algorithm, achieving good agreement with custom Monte Carlo simulation. Finally, the PLATON prototype was exposed to a test beam of pions at the CERN
Proton Synchrotron. For the first time, a plenoptic detector system was successfully used to detect and reconstruct the 3D tracks of elementary particles from 2D
photon-starved images on an event-by-event basis marking a transformative approach to high-resolution measurements.
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All authors Till Dieminger, Marco Barbieri, Vincenzo Berardi, Saúl Alonso-Monsalve, Kodai Kaneyasu, Paul Mos, Tim Weber, Johannes Wüthrich, Claudio Bruschini, Edoardo Charbon, Davide Sgalaberna
Chemical Physics · Cross-listed from quant-ph
Improving the Stability of the Hierarchical Equations of Motion for Open Quantum Systems with Strong Coupling to Structured Bosonic Baths
Salvatore Gatto, Samuel L. Rudge, Bokang Hou et al. (+2 more)
The hierarchical equations of motion (HEOM) approach is one of the most powerful methods avail- able to simulate the dynamics of open
quantum systems. Although the HEOM approach has been shown to be stable and efficient in many parameter regimes and physical scenarios, it is also well known that the unavoidable finite truncation of the hierarchy can lead to fundamental numeri- cal instabilities for bosonic environments. In this work, we apply recently developed techniques to analyze these issues. We use an auxiliary Fock-space picture of the hierarchy to first identify the unbalanced hierarchy-raising terms responsible for the strong transient amplification associated with the non-normal algebraic structure of the HEOM generator. We then apply a non-
unitary similarity transformation that converts these terms into balanced combinations of hierarchy-raising and hierarchy-lowering terms, thereby suppressing their numerical impact. We first demonstrate the efficacy of this approach via a
spin-
boson model with a simple Brownian oscillator spectral den- sity and subsequently extend the analysis to a structured spectral density, showing for both cases that the transformed HEOM approach allows simulations of much larger system-bath coupling than would otherwise be possible.
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All authors Salvatore Gatto, Samuel L. Rudge, Bokang Hou, Eran Rabani, Michael Thoss
Optics
Plasmon-Enhanced Second-Harmonic Generation in Atomically Thin Crystalline Silver Nanostructures
Saad Abdullah, Philipp K. Jenke, Andrew P. Weber et al. (+8 more)
The intrinsically weak nonlinear optical response of existing materials, further constrained by
symmetry-forbidden second-order processes in centrosymmetric media, severely limits efficient frequency conversion in deeply subwavelength, ultrathin volumes. Addressing this challenge is crucial for the development of nonlinear nanophotonics. Here, we show that atomically thin, epitaxially grown crystalline silver films circumvent these restrictions through the interplay of vertical electronic
quantum confinement and lateral plasmonic enhancement. We fabricate atomically thin films that exhibit an enhanced nonlinear response associated with electronic
quantum wells, and subsequently pattern them into periodic nanoribbon and nanotriangle arrays sustaining infrared localized surface plasmon resonances. Strong near-field confinement in these structures further boosts second-harmonic generation compared to unpatterned films. Precise control over nanostructure geometry enables spectral tuning of the plasmonic resonance, and consequently, the enhanced harmonic frequency. Our findings establish an approach for activating robust second-order nonlinearities in
quantum-confined metals, where intrinsic size effects and plasmonic resonances act synergistically. The compatibility of high-quality epitaxial growth with microchip fabrication technology offers a scalable route toward ultracompact nonlinear optical components for on-chip frequency conversion, sensing, and
quantum photonic applications.
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All authors Saad Abdullah, Philipp K. Jenke, Andrew P. Weber, Álvaro Rodríguez Echarri, Vahagn Mkhitaryan, Fadil Iyikanat, Frederik Schiller, Philip Walther, J. Enrique Ortega, Lee A. Rozema, F. Javier García de Abajo
Atmospheric and Oceanic Physics
A Reduced-Order Coupled Oscillator Model for the Emergence of Episodic Convection
Sooman Han, Soong-Ki Kim, Bowen Fan et al. (+3 more)
Extreme precipitation is a societal concern, and understanding tropical moist convection is increasingly important in a warming
climate.
Climate simulations show that, under hothouse Earth, convection can transition from quasi-steady precipitation to an episodic regime characterized by intense rainfall bursts separated by dry intervals, although the mechanisms governing this transition remain debated. Here we develop a reduced-order framework that represents tropical convection through column-integrated moisture (q) and thermal stratification (Delta), rather than bulk measures of convective instability. Analysis of cloud-resolving model (CRM) simulations shows that these variables evolve together: during dry periods, surface fluxes recharge moisture, while radiative and dynamical processes erode stratification generated by previous convection. We couple this
evolution to the nonlinear moisture dependence of tropical precipitation (P), whereby rainfall increases sharply above a critical moisture threshold. A third prognostic variable, C, represents convective persistence, allowing convection to continue below its onset threshold and thereby producing hysteresis. With parameters constrained by CRM output, the model reproduces the
evolution of q, Delta, and P in both regimes, representing quasi-steady convection as stable, noise-driven oscillations and episodic convection as an unstable, self-sustained limit cycle. Linear stability analysis shows that the transition depends on moisture-recharge and stratification-adjustment timescales, thermal-moisture sensitivity, and convective persistence. Because radiative and dynamical processes enter through their effects on thermal stratification, the framework is not tied to a specific mechanism, providing a unified dynamical link between moisture-threshold precipitation behavior and the emergence of episodic convection under warming.
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All authors Sooman Han, Soong-Ki Kim, Bowen Fan, Jérôme Vialard, Alexey V. Fedorov, Juan M. Lora
Physics and Society
A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality
Marc Sadurní, Martín F. Díaz, Julián Vicens et al. (+4 more)
This article describes a behavioural
dataset from a collective-risk dilemma public experiment carried out in Barcelona, Spain, within the citizen science xAire air quality project. Participants played a ten-round game in groups of six, each deciding every round how many monetary units to contribute from a private endowment toward a shared target; groups that fell short forfeited all remaining capital. Three endowment treatments held the group total fixed: an equal condition and two unequal conditions in which low-endowment participants formed either the minority or the majority of the group. Data were collected at two public outdoor venues using a tablet-based interface under lab-in-the-field protocols. Participants were recruited on-site from a demographically heterogeneous pool of individuals passing through the venues, mostly local residents. The
dataset comprises 462 participants across 77 six-player games, 4\,620 contribution decisions in total. Each participant record links the full ten-round contribution trajectory to initial endowment, wealth treatment, venue, district of residence and its measured nitrogen-dioxide concentration, and socio-demographic and attitudinal survey items covering gender, age, education, economic and working status, air-quality perception,
fairness norms, environmental-justice beliefs, residential mobility, and community participation. The release provides raw and cleaned participant tables, a variable codebook, the survey instrument, the district-pollution linkage, and the preprocessing code.
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All authors Marc Sadurní, Martín F. Díaz, Julián Vicens, Anna Cigarini, Isabelle Bonhoure, Miquel Montero, Josep Perelló