Fluid Dynamics
A generalized, quasi-universal subgrid model for macroscopic moving contact line flows
Vyankatesh Manoj Mundhada and Manoj Kumar Tripathi
Predictions of moving contact line flows are challenging due to the stress singularity associated with the no-slip boundary condition on solid surfaces and the inherently multiscale nature of the phenomenon. Resolving the microscopic length scale renders the numerical simulations intractable for macroscopic flows due to extremely high computational costs. Affordable and predictive numerical solutions for macroscopic flows require a subgrid model, free of case-specific calibration, that mitigates the grid-dependence observed otherwise. We demonstrate a coupling between Cox's matched asymptotic relation and the empirical contact angle models to obtain a quasi-universal subgrid model. The coupling requires a one-time knowledge of the observation length scale or resolution of the experiments used to formulate the empirical models. The present model eliminates the need for prescribing phenomenological parameters such as the microscopic slip length and wall contact angle, allowing for the predictive simulations of such flows. We demonstrate the reduction in error due to grid-dependence by conducting axisymmetric simulations of droplet spreading for a wide range of Reynolds and Weber numbers for three different contact angle models in the advancing and receding contact line motion scenarios.
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Applied Physics
Far-field excitation of symmetry-protected bound states in the continuum by nonlinear virtual sources
Marc Martí-Sabaté, Yijie Zhang, Shengming Sun et al. (+4 more)
Bound states in the continuum (BICs) enable complete wave confinement within open systems through destructive interference or
symmetry protection, giving rise to ideally infinite quality factors and extreme field enhancement. Their practical exploitation, however, is hindered by a fundamental paradox: the same mechanism that suppresses radiation also prevents efficient excitation from the far field. Existing experimental approaches typically overcome this limitation by introducing external coupling channels that inevitably perturb the protected state and reduce its confinement. Here we demonstrate the non-invasive excitation of a
symmetry-protected acoustic BIC through nonlinear virtual sources generated directly at the surface of the structure. By focusing time-modulated ultrasonic beams onto a metamirror, nonlinear demodulation produces localized low-frequency sources whose spatial phase matches the
symmetry of the target mode while avoiding any physical coupling to the resonator. This approach injects energy into the BIC without opening additional radiative channels, preserving its intrinsic non-radiative character. We develop a theoretical framework describing the formation and
symmetry protection of the mode, realize a compact experimental implementation through
symmetry reduction, and directly measure the confined pressure field and its quality factor. Our results establish nonlinear virtual sources as a route to accessing
symmetry-protected states in open systems while maintaining their exceptional confinement properties, providing a general strategy for wave manipulation and high-sensitivity resonant devices across physical platforms.
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All authors Marc Martí-Sabaté, Yijie Zhang, Shengming Sun, Ruxin Li, Yabin Jin, Junfei Li, Daniel Torrent Martí
Geophysics
Toward Enhanced Water Detection in SWOT Pixel Clouds using Dynamic Graph Neural Networks
Christoph Baumann, Junyang Gou, Christian Schwatke et al. (+3 more)
The Surface Water and Ocean Topography (SWOT) mission offers unprecedented freshwater monitoring capabilities through its innovative wide-swath measurement system, which generates several data products, including the high-resolution pixel cloud (PIXC) product. However, the native PIXC water classification remains prone to systematic misclassification in urban environments, where strong radar returns from non-water surfaces are the predominant error sources. We present a deep learning approach that enhances land-water classification directly on SWOT PIXC data based on a dynamic graph convolutional neural network that simultaneously exploits spatial proximity and feature similarity to derive binary land-water class labels. The model is trained on a full year of PIXC data for the Dallas-Fort Worth metropolitan area using pixel-level ground-truth class labels derived from the DSWx-HLS product, which provides water-class labels based on Landsat and Sentinel-2 at a 30\,m spatial resolution. Against the DSWx-derived reference, the proposed method increases the mean scene-level F1 score against the DSWx-derived reference from 0.52 to 0.86 on the temporally independent test set and from 0.43 to 0.74 on the spatiotemporal test set, relative to the native PIXC classification. These results demonstrate that dynamic graph neural networks are well-suited to the irregular, point-cloud-like structure of PIXC data and offer a scalable path toward more reliable urban flood monitoring and freshwater mapping at the high spatial resolution provided by the SWOT PIXC product.
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All authors Christoph Baumann, Junyang Gou, Christian Schwatke, Mohammad J. Tourian, Florian Seitz, Benedikt Soja
Plasma Physics · Cross-listed from astro-ph.HE
Jet Forecast: Timing of Discrete Jet Ejections of Stellar-Mass Black Holes Anticipated via X-ray Properties
Toshihiro Kawaguchi and Kazutaka Yamaoka
The
radio – soft $\gamma$-ray data of the Galactic black hole binary XTE J1859+226 showed that discrete jets are launched when the inner radius of the
accretion disk ($R_{\rm in}$) rapidly approaches the innermost stable circular orbit (ISCO). Given the correlations among the X-ray fractional variability amplitude (rms), $R_{\rm in}$, and the X-ray hardness, previous phenomenological findings related to jet ejections (“jet line” and sharp drops of rms) also indicate that the rapid shrinkage of $R_{\rm in}$ down to the ISCO turns on the jet formation. In order to make clear how these properties appear in other objects, we investigated the X-ray and
radio data of XTE J1550-564, GX 339-4, and MAXI J1820+070. We found that all the four sources show drops of $R_{\rm in}$ and rms 1-10 days ahead of a jet activity, and exhibit no huge jumps of the
accretion rates prior to jet ejections. XTE J1859 and MAXI J1820 show the jet activities under sub-Eddington
accretion. Models for the jet production that require an enhancement of $\dot{M}$ or a super-Eddington
accretion rate are unlikely. Another behavior common to multiple sources is the curved shape of the rms–$R_{\rm in}$ correlation. Therefore, monitoring of $R_{\rm in}$ seems to be suitable to predict the timing of jet ejections. When both $R_{\rm in}$ and rms continuously decrease and when $R_{\rm in}$ is about to reach the ISCO, alerts can be circulated as a “jet forecast” for triggering Target-of-Opportunity observations.
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Accelerator Physics
Terahertz-driven electron acceleration from subrelativistic to fully relativistic energies in stepped dielectric-lined waveguides
Filip J. Peczek, Laurence J. R. Nix, Graeme Burt et al. (+6 more)
The short wavelength of terahertz (THz) waves makes the acceleration of electrons, from typical electron gun energies to fully relativistic energies, challenging due to the need to match the velocities over comparably long distances. However, the inherent
laser synchronisation of a photogun to the THz drive
laser offers significant advantage in applications where timing is critical. We present a novel design process for high-gradient THz-driven dielectric-lined waveguide injectors and demonstrate designs for rectangular and cylindrical geometries. These structures utilize novel tapering and stepping schemes to manipulate the phase velocity, controlling the position of the electron bunch relative to the phase of the accelerating field. We demonstrate a hybrid optimisation method utilizing firstly a multi-objective genetic
algorithm based on analytic models of the waveguide accelerating modes, and then high-detail particle-in-
cell simulations. Our example designs achieve electron acceleration from 100 keV to 1 MeV over a distance of 20 mm by interacting with a multicycle 0.5 mJ, 0.2 THz pulse, paving the way for the realisation of THz-based injectors. The exit beam shows excellent beam quality with 50 fs bunch lengths, sub 0.5% energy spread and emittances of under 0.15 {\mu}rad. We also present an analysis of the robustness of the designs to errors in machining and operational parameters demonstrating the feasibility of the concept. We show that using multi-objective genetic
algorithm optimization and robust design process, we can achieve high-quality 1 MeV beams.
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All authors Filip J. Peczek, Laurence J. R. Nix, Graeme Burt, Rosa Letizia, Joseph T. Bradbury, Darren M. Graham, Morgan T. Hibberd, Steven P. Jamison, Robert B. Appleby
Fluid Dynamics
Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics
Pradyumn Singh Sikarwar, Vishal Sharma and Gaurav Bhutani
Accurate prediction of avalanche motion is essential for hazard assessment in mountainous terrain. This study develops and evaluates a physics-informed neural network (PINN) framework for the Savage-Hutter model of depth-averaged granular flow, progressing from 1D analytical verification to 2D experimental validation. First, three 1D problems of increasing complexity were verified against the analytical solution: height prediction with prescribed velocity, velocity prediction with prescribed height, and coupled prediction of both fields using the conservative formulation. The decoupled tests accurately reconstructed the spatio-temporal
evolution of each field when the other was prescribed. The coupled formulation learned both fields without prescribed data, achieving mean height and velocity RMSEs of 0.043 and 0.079 in non-dimensional units. A hyperparameter sensitivity study evaluated the effects of network depth, width, collocation density, learning rate, and epochs. The framework was then extended to 2D and validated against laboratory experiments of a cylindrical granular pile collapsing on an inclined plane, with TITAN2D providing numerical comparisons. Purely physics-based training converged to the trivial zero solution; augmenting the loss with 10 sparse training points from final deposit profiles produced a physics-informed, data-assisted hybrid framework. Peak flow depth, depth-averaged velocity, RMSE, and wetted-area IoU evaluated global and local agreement. Global height RMSE ranged from 2.7 to 6.7 mm across four experimental cases, while mean wetted-area IoU ranged from 69 to 81 %, demonstrating consistent performance across variations in pile mass and slope angle.
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Chemical Physics · Cross-listed from cond-mat.soft
A Unified Rational-Function Approximation for Square-Well, Square-Shoulder, and Nonadditive Hard-Sphere Mixtures
Andrés Santos, Santos B. Yuste, Ana M. Montero et al. (+1 more)
We develop a rational-function approximation for the structural properties of multicomponent fluids with narrow square-well and square-shoulder interactions, together with weakly nonadditive hard-sphere mixtures. The theory is obtained by reformulating the analytical Percus–Yevick solution for additive sticky hard-sphere mixtures so as to account for finite interaction widths, leading to a unified semianalytical framework for these classes of fluids. The approximation satisfies the exact low-density limit and preserves the continuity of the cavity functions; a simple local correction restores the continuity of their first derivatives. Comparison with Monte Carlo simulations for binary mixtures shows that the theory accurately describes both the radial distribution functions and their
Fourier transforms for narrow wells and shoulders and for weak nonadditivity. The proposed formulation extends previous sticky-hard-sphere-based approaches while retaining their analytical simplicity.
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All authors Andrés Santos, Santos B. Yuste, Ana M. Montero, Mariano López de Haro
Physics Education
Community agreements pedagogy in physics
Rachel E. Scherr, Jer Steeger and Paige Sechrest
The idea of engaging critically and creatively with physics theories is a stretch for many physicists and physics educators. Most physicists become enculturated into the belief that physics definitions, laws, and equations are read from the book of nature. However, this belief obscures how theories are collectively negotiated by people in specific socio-political and personal conditions, and how students' particular ideas and intuitions will inevitably shape their own practice of science. To help students build their skills for collective theory-building, we suggest a pedagogy for physics in which students actively negotiate the laws and definitions of theories.
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Optics
A three-phase framework for photon scattering in porous nanocomposites
Khalid Alhammadi, Daniel Carne and Xiulin Ruan
Light scattering in heterogeneous media underpins a broad range of natural phenomena and optical technologies, yet remains difficult to understand in porous nanocomposites. State-of-the-art theories generally treat these materials as two-phase systems consisting of particles and a
matrix, overlooking the air pores that are intrinsically present in porous composites. Here we experimentally determine the scattering coefficients of six BaSO4-acrylic and TiO2-acrylic coatings spanning a range of particle volume fractions and develop a three-phase scattering framework that explicitly accounts for pore-induced scattering. By representing the composite as two coupled scattering subsystems, particle-
matrix and particle-air, the framework resolves discrepancies between theory and experiment: conventional two phase models substantially underpredict scattering in BaSO4 coatings while overpredicting scattering in TiO2 coatings, whereas the three-phase model accurately captures the observed trends and reduces the mean absolute logarithmic error from 0.667 to 0.379. This framework identifies air pores as a fundamental and independently controllable contributor to optical scattering, providing new physical insights and design principles for engineering highly scattering porous nanocomposites.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Chemical site bases and average-atom potentials for the atomic cluster expansion
Lorenzo Piersante and Anirudh Raju Natarajan
Interatomic potentials are central tools in the atomistic modeling of materials. The atomic cluster expansion (ACE) parameterizes such potentials from ab initio data, conventionally encoding the chemical degrees of freedom with a one-hot representation that yields chemically stratified models. The alternative chemical representations used in on-
lattice configurational cluster expansions have not been assessed for interatomic potentials. Here we revisit the multicomponent ACE for an arbitrary chemical site basis. We then establish an exact analytical mapping between a fitted linear ACE and the average-atom potential that describes a perfectly random
alloy. We
benchmark potentials built on the occupational, Chebyshev, and conventional ACE bases against solute binding and vacancy formation energies in Mg-Nd, and against the mixing enthalpies of the Mo-Nb and Cr-W solid solutions. When training data are scarce, the occupational basis converges fastest and offers the best control over targeted material properties, while the conventional and Chebyshev bases face challenges in reproducing these properties. The occupational basis likewise yields the most reliable average-atom description of disordered
alloy thermodynamics. In the large-data limit the three bases perform identically. The chemical basis is therefore a design choice that governs data efficiency. Its explicit treatment opens a route to average-atom potentials for the thermodynamic, mechanical, and kinetic properties of concentrated
alloys.
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Atmospheric and Oceanic Physics
MW-Nowcast: Six-hour ensemble nowcasting of extreme precipitation
Ning Wang, Zuliang Fang, Weixin Jin et al. (+19 more)
Extending reliable nowcasting of extreme precipitation could provide critical additional time for warnings and emergency response during high-impact events such as flash floods. Radar-based generative machine-learning models have enabled skilful hyperlocal precipitation nowcasting, but accurate prediction of intense precipitation remains confined to the first few hours. Because storm-scale structure is predictable for longer than individual
cells, a natural strategy is to predict that structure while generatively modelling only the uncertain local growth, decay, reorganisation and initiation of storms. Here we present Microsoft Weather Nowcast (MW-Nowcast), a six-hour ensemble radar nowcasting model that jointly learns a deterministic predictor to capture organised precipitation structure shared across ensemble members, and a generator to produce diverse local residuals around this shared prediction. Across independent test data from the United States, Europe and China, MW-Nowcast achieves higher detection skill than leading methods for heavy and extreme precipitation throughout the 6 h horizon. For the most intense rainfall, MW-Nowcast doubles the available warning time across all three regions, delivering 6 h forecasts with skill previously limited to 3 h for the leading generative baseline. A cost-loss decision analysis shows that MW-Nowcast retains substantial value for a broad range of applications even at 4-6 h, where alternative methods offer little benefit. These additional hours can give forecasters and emergency managers the time to warn and act before extreme rainfall strikes, helping to protect lives and property.
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All authors Ning Wang, Zuliang Fang, Weixin Jin, Zhongjian Lv, Shuang Qin, Pengcheng Zhao, Siqi Xiang, Jiang Bian, Haoyi Xiong, Nan Guan, Bin Zhang, Liangjie Zhang, Denvy Deng, Qi Zhang, Matt Corey, Jitu Keshri, Sridhar Iyer, Hongyu Sun, Kit Thambiratnam, Jonathan Weyn, Richard E. Turner, Haiyu Dong
Atomic Physics · Cross-listed from quant-ph
Cubic Phase Gate with a Trapped Ion Oscillator
Nigel Benjamin Lee Junsheng, Eugene Koh Jun Wei, Mu Young Kim et al. (+1 more)
The motional modes of trapped ions are promising candidates for continuous-variable (CV)
quantum computation and simulation. However, to achieve a universal gate set for CV
quantum computation, anharmonic nonlinear
unitaries are required. Here, we experimentally demonstrate a protocol that allows us to approximate the cubic phase gate. By numerically optimizing the phase angles and amplitudes of a set of state-dependent force pulses, we demonstrate the cubic phase gate for both
vacuum and low-$\alpha$ coherent state inputs and verify its performance. Our protocol can also be extended to approximate other nonlinear
unitaries.
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All authors Nigel Benjamin Lee Junsheng, Eugene Koh Jun Wei, Mu Young Kim, Dzmitry Matsukevich
Atomic and Molecular Clusters
Model potential based estimation of positron bound states with polar molecules
Snigdha Sharma and Dhanoj Gupta
Positron forming a bound state with molecules is an area of meticulous research and remains open to simpler techniques for estimating the binding energy. Correlation between the incoming positron and the molecular electrons plays a crucial role even for polar molecules, where binding is also possible at the static-potential level. In this work, we have used a model correlation potential, which accounts for the virtual positronium formation, in the single-center expansion scattering calculations for polar oxygen-containing molecules. The thus determined S-
matrix is continued into the complex momentum plane by fitting it to the Pade approximant. The positron bound state is estimated using the calculated pole position of the S-
matrix. The results, compared with the latest experimental and ab initio findings, look quite promising.
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Space Physics · Cross-listed from astro-ph.EP
The precipitation of protons and electrons in Jupiter's auroral regions: a statistical comparison based on Juno/JEDI data
B. Benmahi, N. André, V. Hue et al. (+8 more)
Energetic electrons dominate the energy precipitated into Jupiter's auroral regions, but
protons precipitate along the same field lines, with a contribution that remains poorly constrained. We statistically compare the precipitating energy flux of
protons and electrons in two of Jupiter's auroral sub-regions, the polar (PE) and main (ME) emission regions. We use Juno/JEDI data from PJ3 to PJ66. The
magnetic footprint of the spacecraft, computed with the JRM33 and CON2020 field models, is assigned to one of the two sub-regions, and the precipitating energy flux of each species is obtained by integrating over the loss cone the mean differential intensity measured within it. In both sub-regions, the median
proton energy flux is 52 to 223 times lower than that of the electrons, and the total precipitated
proton power is less than 2% of the electron power.
Proton fluxes are broadly distributed across the sub-regions, with higher values in the ME than in the PE.
Protons play a secondary role in Jupiter's auroral energy budget, radiating an estimated 5 to 9 GW in the UV per sub-region, pending a dedicated
proton transport modelling. Their Doppler signature in the red wing of the Lyman-$\alpha$ line, undetected by HST and difficult to access with Juno/UVS, is a key observable for the upcoming Juice and Europa Clipper missions.
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All authors B. Benmahi, N. André, V. Hue, Z.-Y. Liu, G. Gronoff, B. Mauk, B. Bonfond, T. Stallard, M. Blanc, M. Devinat, M. Barthélémy
Fluid Dynamics
Phase-field simulation of interfacial stability in structured gas-liquid contactors: design rules for gas diffusion electrodes
Alexander J. Wagner, Hari Murali Krishna Varma Gottumukkala and Henning Bonart
Many process engineering applications hold a gas-
liquid interface stationary inside a structured solid by a controlled pressure difference. Gas
diffusion electrodes (GDEs) are one such case, where the interface separates the
liquid electrolyte from the gaseous reactant. Maintaining it is particularly challenging in organic electrosynthesis, where low surface tensions lower the admissible pressures throughout and small contact angles leave the electrode with little margin against flooding. Here, we quantify how the shape, wettability, and three-dimensional
topology of a structured medium set this window, using phase-field simulations of the Cahn-Hilliard-Navier-Stokes equations. Each geometry is characterised by its Laplace pressure curve, which yields both the maximum admissible pressure difference and the stiffness of the interface against pressure fluctuations. For single flat orifices at constant open area, elongating the opening from an aspect ratio of one to six raises the admissible pressure difference by 40 % and the stiffness by a factor of 3.3. Comparison with slits of equal width shows that this gain originates entirely from the reduced opening width. Sheared, diamond shaped openings are markedly less effective. In woven meshes, the wettability displaces the operating window several times as far as it stretches it. A less wetting surface therefore buys flooding margin largely at the expense of breakthrough margin, whereas the
geometric route, established here for flat openings, widens the window itself. From these results we derive design rules for structured gas-
liquid contactors and improved GDE architectures for organic electrosynthesis.
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Optics
Surface Acoustic Wave-Mediated Brillouin Temperature Sensor on Thin-Film Lithium Niobate
Varun Marathan Kovil, Justus Nölkensmeier, Gladys Jara-Schulz et al. (+8 more)
The emergence of thin-film lithium niobate (TFLN) has paved the way for realizing strong Brillouin interactions in lithium niobate platforms, enabling new opportunities in integrated photonics. However, fully harnessing stimulated Brillouin scattering (SBS) in TFLN for the plethora of Brillouin applications remains an exciting area of research, with significant opportunities for further exploration and technological advancement. Here, we present the first comprehensive experimental and numerical study of the surface acoustic wave (SAW)-mediated Brillouin temperature sensor on a TFLN-on-
insulator chip. The proposed technique directly senses the surrounding environment via SAWs, providing an optical-power-efficient platform compatible with existing integrated photonic architectures. Exploiting the strong intermodal Brillouin interactions in x-cut TFLN waveguides, we report a high Brillouin gain of 24.8$ \pm $1.3\, m$^{-1}$W$^{-1}$ and a temperature coefficient of $-0.73$ $\pm$ 0.02\,MHz/$^\circ$C. Considering the anisotropic nature of lithium niobate, we investigate the temperature dependence of the Brillouin frequency for the propagation directions 0$^\circ$, 10$^\circ$, 20$^\circ$, 30$^\circ$ relative to the crystallographic y-axis.
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All authors Varun Marathan Kovil, Justus Nölkensmeier, Gladys Jara-Schulz, Pratham Kulkarni, Silia Babel, Christian Golla, Rajkumar Jadhav, Christof Eigner, Laura Padberg, Christine Silberhorn, Birgit Stiller
Data Analysis and Statistics · Cross-listed from math-ph
Scattering Measures and Information Geometry
Tatsuro Oda
We formulate scattering experiments in terms of parameterized finite measures on outcome spaces and develop the associated information geometry defined by the Fisher metric. The decomposition of a scattering measure into total mass and normalized shape separates Fisher information into contributions from changes in overall scattering strength and redistribution among outcomes. Measurement processes are represented by probability or sub-probability kernels acting on the scattering measure. Such kernels contract Fisher information, placing a broad class of experimental operations within a common information-theoretic framework. This formulation connects scattering experiments to the theory of optimal experimental design through the Fisher geometry of scattering measures. The same finite-measure structure arises naturally in
quantum measurements with incomplete detection, clarifying its place in the hierarchy from
quantum measurement to classical outcome statistics.
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Atomic Physics
Interactions and dynamics of metastable triplet-state helium dimer with Ne and Ar
Dibyendu Sardar and François Lique
Helium dimer in its metastable triplet electronic state, He$_2(a~^3\Sigma_u^+)$, is a promising candidate for direct
laser cooling and precision measurements. Interactions and collisions involving He$_2(a~^3\Sigma_u^+)$ remain unexplored in ultracold and cold energy domains. Here, we present the first theoretical investigation of intermolecular interactions and collision dynamics of He$_2(a~^3\Sigma_u^+)$+Ne van der Waals complex. For the ground electronic state, $X~^3\mathrm{A}'$, we employ a
spin-restricted coupled cluster method with single, double, and noniterative triple excitations. The resulting interaction potential exhibits an extremely shallow well with a depth of 4.612 cm$^{-1}$. We construct a three-dimensional vibrationally averaged potential energy surface. Using this surface, we perform full close-coupling calculations including fine-structure levels of He$_2(a~^3\Sigma_u^+)$ to investigate collisional excitation and quenching induced by Ne. We analyze the low-energy scattering dynamics and model resonant features associated with quasi-bound states supported by interaction potential. Propensity rule for fine-structure conserving transitions is established. We additionally consider He$_2$+Ar collisions and compare their energy dependence and resonance structure with those of He$_2$+Ne. The He$_2$+Ar system exhibits a richer resonance structure, highlighting the sensitivity of low-energy scattering to interaction potential and reduced mass. Calculated PES and scattering properties provide a reliable
benchmark for description of He$_2$+Ne van der Waals complex and may be useful for interpretation of future experimental spectra and collision measurements.
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Space Physics · Cross-listed from astro-ph.EP
Energy distributions of precipitating electrons in Jupiter's auroral regions from combined Juno/JADE and Juno/JEDI measurements
B. Benmahi, V. Hue, N. André et al. (+17 more)
Jupiter's auroras are produced by magnetospheric electrons precipitating into its atmosphere. Juno/JADE and Juno/JEDI together measure these electrons from 100 eV to 1 MeV. However, their auroral spectra are poorly reproduced by the widely used kappa distribution, hereafter the classical single-kappa distribution. We aim to statistically characterize the energy flux distributions of precipitating auroral electrons and to derive a new phenomenological 4-kappa distribution better suited to JADE+JEDI data. We build mean energy flux distributions in six auroral sub-regions (polar, main, and outer emissions in both hemispheres), combining JADE and JEDI data from PJ3 to PJ35, mapped to the SIII frame with the JRM33 model including the current sheet. We fit them using MCMC with the classical single-kappa and 4-kappa distributions. The mean distributions show a monotonic power-law decay with an energy cutoff beyond ~500 keV in most sub-regions, although some individual spectra depart from it at intermediate energies. Mean energies range from ~21 to ~119 keV, and energy fluxes from ~9.5 to ~28.7 mW/m$^2$. The classical single-kappa fit fails in all sub-regions, with $\kappa$ converging to the lower bound of its prior range. We therefore introduce the 4-kappa distribution, a linear combination of four classical single-kappa distributions modulated by an exponential high-energy cutoff, which accurately fits all six sub-regions. At equal energy flux and mean energy, transport simulations show that the 4-kappa distribution deposits energy at lower altitude than the classical one and distributes it differently along the vertical, with implications for the UV color ratio, atmospheric chemistry and thermal structure, and ionospheric conductances. This distribution provides an analytical framework for realistic modeling of electron precipitation and UV auroral emissions at Jupiter.
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All authors B. Benmahi, V. Hue, N. André, B. Bonfond, M. Blanc, Z.-Y. Liu, B. H. Mauk, F. Allegrini, G. Clark, M. Devinat, G. Gronoff, T. Le Liboux, M. Barthélémy, C. Lefour, T. Cavalié, B. Benne, T. Gautier, T. Briand, J. A. Noble, J. A. Sinclair
Chemical Physics
Symmetry-Aware Flow Matching for End-to-end Molecular Crystal Generation
Wendi Cai and Fanyang Mo
Molecular
crystal packing shapes properties from drug bioavailability to charge transport, yet generating realistic structures requires coordinating molecular flexibility, intermolecular interactions and
symmetry. Here we introduce SALA, a flow-matching model built on state–context separation: it evolves only asymmetric-unit (ASU) atomic coordinates and
symmetry-compatible
lattice parameters while predicting their updates from the full periodic environment. Conditioned on molecular graphs and a space group, SALA generates molecular conformation,
lattice geometry and packing end to end while preserving the specified
symmetry. Across 799 held-out
crystals spanning four chemical classes and all seven
crystal systems, SALA achieves a 72.0% hit rate from 50 candidates per target, compared with 8.1% for an atomistic full-
cell generative baseline. Mean best-candidate packing root-mean-square deviation decreases from 4.48 to 1.70~Å, with the advantage widening as system size and
symmetry multiplicity increase. SALA thus enables end-to-end generation of complex,
symmetry-constrained molecular
crystals, with potential applications in CSP, structure-based pharmaceutical polymorph design and organic molecular materials discovery.
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Space Physics
P2D - A Two-Dimensional Multi-Spacecraft Solar Wind Persistence Model
Daniel Milošić, Manuela Temmer, Stephan G. Heinemann et al. (+2 more)
The background solar wind is a key component in space weather forecasting, as it contains geoeffective high-speed streams and provides the medium through which coronal mass ejections propagate and evolve in interplanetary space. Due to the solar rotation and the slow
evolution of large-scale solar wind structures, solar wind properties exhibit an autocorrelation with a period of roughly 27 days, particularly at solar minimum. We made use of this property to develop a solar wind persistence model with input from multiple spacecraft (Solar Orbiter, Parker Solar Probe, STEREO-A, STEREO-B and the OMNI database). The model ballistically propagates in-situ data from the position of their measurement radially away from the Sun, as well as longitudinally with the solar rotation rate, producing 2D maps of solar wind parameters. These can be extracted at any point in the heliosphere for a solar wind reconstruction. From Earth's perspective, the reconstruction performs with an MAE of 65.41 km/s and 3.51/cm^3 for speed and density, respectively. During high-speed streams, the peak hit rate is 50% and 48% for speed and density. It performs best during times when there are spacecraft located between Earth and Lagrange point L5. During these times, the mean absolute error of the predicted solar wind speed decreases by roughly 35% in comparison to the
benchmark 27-day persistence model. Therefore, future L5 missions like Vigil are expected to provide a robust basis for reliable persistence forecasts.
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All authors Daniel Milošić, Manuela Temmer, Stephan G. Heinemann, Mathew Owens, Stefan J. Hofmeister
Biological Physics
DNA geometry around highly transcribed bacterial genes
Marc Joyeux
Recent high-resolution (500 bp) Hi-C experiments reported contact maps with unusual patterns around highly expressed bacterial DNA loci. These patterns, described as arched stripes and bundled domains, extend over nearly 100 kbp. We performed Brownian Dynamics simulations with a specially designed coarse-grained model to rationalize these findings. The main feature of the model is that it takes explicitly into account the waves of positive (respectively, negative) supercoiling generated by the translocating polymerase downstream (respectively, upstream) of its position. Contact maps computed from the simulations also display the arched stripe and bundled domain patterns for above-threshold values of the rate of twist injection. Computed DNA conformations indicate that these patterns reflect an extraordinarily entangled DNA geometry, which involves both plectonemic and toroidal supercoiling, with some DNA segments experiencing both of them simultaneously. Moreover, DNA segments located on each side of the polymerase systematically wind around tracts located on the other side, which is a purely out-of-
equilibrium effect driven by the continuous injection of twist. The present work therefore reveals that repeated transcription of a DNA locus systematically brings into contact DNA segments separated by several tens of kbp, which may eventually contribute to allosteric modulation and long-range communication.
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Applied Physics
Adaptive metamaterial resonators: a discrete and continuous mechanism
Vanessa Cool, Elke Deckers and Frank Naets
Locally resonant metamaterials are an established route to lightweight attenuation of vibration and noise, but their performance is tied to a bandgap fixed at the design stage. In practice, excitation frequencies are rarely constant, as they can vary with operating conditions and loading, causing fixed-frequency resonators to lose effectiveness as conditions drift from their design point. Existing strategies to address this rely on active control, introducing sensors, actuators, and a continuous power supply, or on broadband and multi-resonator designs that trade attenuation depth for bandwidth. A passive alternative, capable of adapting its resonance characteristics directly within the operating environment, would remove this trade-off and open locally resonant metamaterials to a much wider range of real-world, time-varying applications. In this work, we present two adaptive resonator concepts that enable in-situ modification of local resonance characteristics through discrete and continuous adaptation mechanisms.
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Biological Physics · Cross-listed from cond-mat.soft
Cell division sets a universal flow geometry in cell layers
Tianxiang Ma, Lasse Bonn, Valeriia Grudtsyna et al. (+4 more)
Collective flows in epithelial tissues contain a
geometric backbone of vortical interfaces whose statistics exhibit hallmarks of critical percolation and conformal invariance. Yet how fundamental cellular processes govern the breakdown of such
symmetry-rich flow geometry remains unclear. Here we show that
cell division plays a central physical role in regulating this universal flow organization by controlling both the
geometric and mechanical flexibility of the
cell-
cell network. Using pharmacological perturbations, we find that when proliferation is suppressed through two independent interventions, coherent flows persist but neighbor exchanges decline and conformally invariant geometry is lost. Blocking apoptosis does not affect universality, isolating division as the key control. A vertex model with tunable division quantitatively reproduces these effects and restores conformal invariance when division is allowed. We further trace this effect to changes in both the
geometric and mechanical organization of the
cell layer: Divisions act as intermittent topological renewals that loosen constraints, preserving the network's flexibility and capacity to rearrange across scales. Thus, beyond its canonical role in growth,
cell division acts as a structural and mechanical regulator of collective self-organization. These findings establish a direct connection between fundamental biological processes and emergent physical
symmetries.
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All authors Tianxiang Ma, Lasse Bonn, Valeriia Grudtsyna, Nigar Abbasova, Martin Cramer Pedersen, Nuno A. M. Araujo, Amin Doostmohammadi
Chemical Physics
Curvature-Aware Flow Matching for Molecular Structure Generation
Samir Darouich, Juliane Geisler, Jacob W. Toney et al. (+4 more)
Generative models produce three-dimensional molecular structures with high
geometric accuracy, yet they are trained on distributions of atomic coordinates without explicit access to the underlying physics. The potential energy surface (PES) describes how the energy changes around a molecular geometry, and the RMSD between a generated structure and its reference captures this local landscape only indirectly. Supervising the PES during training could close this gap, but conformers and transition states (TSs) are stationary points at which the forces vanish, so first-order quantities carry little information about them. What remains is the local
curvature, encoded in the Hessian of the PES.
Quantum-chemical Hessians are too expensive to be available at the scale required for training, but recently proposed machine-learned predictors make
curvature inexpensive enough to supervise directly. We introduce CurvFM, a flow matching (FM) formulation whose training objective constrains the
curvature at the generated structure. A frozen Hessian prediction model is evaluated at the generated endpoint and at the reference structure, which removes the need for
quantum-chemical Hessians and keeps the residual cheap enough to impose at every training step. Across TS and conformer generation, CurvFM substantially improves physical fidelity at unchanged global structural accuracy, reducing the median deviation in maximum force by 63% on GEOM-QM9 and raising the fraction of valid TSs by up to 10% across three reaction
datasets.
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All authors Samir Darouich, Juliane Geisler, Jacob W. Toney, Tanja Bien, Johannes Kästner, Heather J. Kulik, Mathias Niepert
Atomic Physics
Breit interaction in elastic scattering of vortex electron on Hydrogen atomic target
Pengcheng Zhao
The interaction of electron
vortex beams with atoms is fundamental to their applications, yet existing studies on elastic scattering have considered only the Coulomb interaction. The role of the Breit interaction, which represents the leading relativistic correction to the Coulomb potential between two electrons, has not been systematically examined. We study the elastic scattering of a \(300\) keV
vortex electron by a hydrogen atomic target, with emphasis on the role of the Breit interaction. Comparisons are made between the pure Coulomb contribution and the sum of the Coulomb and Breit contributions. Our results show that the Breit interaction dominates the scattering process in certain kinematic regions when the total angular momentum (TAM) of the
vortex electron is sufficiently large, which breaks with the conventional notion that the Breit interaction has little contribution to electron scattering for low-\(Z\) atoms. This phenomenon arises primarily because a
vortex electron with large angular momentum possesses a substantial
magnetic moment, and the Breit interaction precisely describes the interaction between
magnetic moments. We further compare single-atom, mesoscopic, and macroscopic target cases, and show that the target size significantly influences the observability of the Breit-induced effects, with a smaller target size being favorable for observing this phenomenon.
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Geophysics
A Review of Deep-learning-based Seismic Data Denoising and Its Promising Paradigm Shift to Foundation Models
Xintong Dong, Zhengyi Yuan, Changxin Wei et al. (+3 more)
Denoising is a long-standing and widely-concerned topic in seismic data processing, for it can significantly increase the signal-to-noise ratio of seismic data. Numerous deep learning (DL) methods have shown promising denoising performance, but most of them are task-specific and focus on a certain type of seismic background noise. The real condition that seismic
datasets are often contaminated by various types of noises motivates us to explore a well-generalized and versatile DL model for seismic data denoising. Recently, in the fields of computer
vision and natural
language processing, foundation models (FMs) pre-trained on vast
datasets demonstrate outstanding adaptability and generality across diverse downstream tasks. This paradigm offers a promising path to address the challenges faced by task-specific DL denoising models, such as poor generalization, retraining from scratch for different noise, and the lack of labeled data. We first provide a brief review of traditional seismic denoising methods, followed by a comprehensive review of existing DL-based denoising methods categorized by noise type. Furthermore, we conduct a case study on a dedicated seismic denoising foundation model termed SeisDeFM. This is the first study in geophysical research to develop and validate a seismic denoising foundation model on pre-stack gathers with diverse noise conditions. Experimental results demonstrate that, compared with task-specific DL baselines, SeisDeFM achieves superior denoising performance and cross-noise generalization by the advantages of sufficient pre-training and appropriate downstream adaptation, and it effectively preserves weak reflection events while suppressing complex noise in pre-stack seismic data.
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All authors Xintong Dong, Zhengyi Yuan, Changxin Wei, Wenshuo Yu, Shiqi Dong, Jun Lin
Optics
Contact lens with stretchable distributed-feedback laser for intraocular pressure monitoring
S.A. Ivanov, I.M. Fradkin, E.S. Musikhina et al. (+8 more)
Continuous monitoring of intraocular pressure (IOP) is essential for the diagnosis and management of glaucoma, yet existing clinical methods rely on intermittent in-clinic measurements that miss critical diurnal fluctuations. Smart contact lenses are an attractive platform for continuous IOP tracking, and optical strain sensors are particularly promising thanks to their high sensitivity and natural readout. Most such optical sensors infer strain from the period of a regular structure - a grating or photonic
crystal - whose deformation is read out optically. However, the precision of all sensors based on the period of regular structures is fundamentally bounded by the uncertainty principle, which severely limits performance at the millimeter length scales available inside a contact lens. Here, we address this limitation by integrating a distributed-feedback (DFB)
laser, based on a surface-modulated ultrathin F8BT dye layer, into a soft polydimethylsiloxane (PDMS) contact lens. Operating at a
symmetry-protected bound state in the continuum at the {\Gamma} point, the device produces a narrow lasing line whose wavelength shifts directly with grating strain - a quantity not constrained by the spatial uncertainty principle. The DFB structure is fabricated by UV holographic lithography and transferred onto the lens by a simple float-off process, yielding a stretchable, transparent,
polymer-compatible sensor that is intrinsically scalable. Tested on a custom artificial eye model whose pressure-induced deformation is comparable in scale to that reported for the human eye, the sensor achieves a sensitivity of 0.027 nm/mmHg and a calibration residual of 1.2 mmHg under phantom conditions, a level relevant to tonometric monitoring, with substantial headroom currently limited mainly by auxiliary readout equipment.
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All authors S.A. Ivanov, I.M. Fradkin, E.S. Musikhina, R.V. Kirtaev, A.A. Khrebtov, A.A. Vyshnevyy, A.A. Marchenko, V.R. Solovei, I.P. Radko, A.V. Arsenin, V.S. Volkov
Fluid Dynamics · Cross-listed from math.AP
A Critical Value for the Viscosity Coefficient: Triggering Oscillatory Traveling Waves in the Pseudo-parabolic Fisher-KPP Equation
Yang Cao, Haomeng Chen, Chunhua Jin et al. (+1 more)
The pseudo-parabolic term $u_{xxt}$ serves as a canonical example of higher-order viscosity that provides effective regularization while capturing the refined physical mechanism. How it alters the dynamics of prototype equations remains a fundamental issue, which is not yet fully understood. The goal of this paper is to show that this term induces a sharp transition in traveling wave structure, via studying the pseudo-parabolic Fisher-KPP equation $$ u_t - \tau u_{xxt} = D u_{xx} + u(1-u). $$ We completely characterize how the parameter ratio $\tau/D$ acts as a critical switch: it preserves the monotonic structure of classical traveling waves when $\tau/D \leq 1$, yet it triggers a qualitative shift to oscillatory traveling waves when $\tau/D > 1$. Numerical simulations support these findings. The threshold $\tau/D=1$ thus captures the dual role of the pseudo-parabolic term: it acts as a structure-preserving viscosity when small, but when large it reflects dominant capillary hysteresis, generating the oscillations that explain the saturation overshoot, a phenomenon that contradicts classical
diffusion models yet is widely observed in two-phase flow.
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All authors Yang Cao, Haomeng Chen, Chunhua Jin, Jingxue Yin
Applied Physics · Cross-listed from quant-ph
Cavity magnonics and bound states in the continuum with Bragg and anti-Bragg mirrors
B.-Y. Wu, K.-P. Li, G. Chen et al. (+7 more)
A periodic resonant emitter array coupled to a one-dimensional waveguide can act as a mirror. A typical example is a Bragg mirror, where emitters are spaced by multiples of half wavelengths and collectively enhance light reflection. Two such mirrors form an effective cavity that hosts bound states in the continuum (BICs). However, generating and detecting the spatial profiles of such BICs has proven challenging. Here, we experimentally demonstrate BICs in cavity magnonics using two periodic ferrimagnetic-sphere arrays and a probe sphere in a dual-open-waveguide architecture. We realize both Bragg and anti-Bragg cavities, whose mirrors have different
lattice constants. In the Bragg cavity, there are degenerate supermodes formed by mirror spheres. We show that a single dark supermode coherently couples to the probe
magnon in the cavity region, forming two polaritons whose splitting scales with both the probe-sphere size and the number of mirror spheres. By contrast, the anti-Bragg cavity has bright and dark supermodes in a bandgap, substantially changing the
magnon-cavity interaction. Moreover, by moving the probe sphere, we perform position-dependent detection of the cavity field, highlighting the role of BICs in these cavities. Our flexible experimental setup with a scanning probe opens possibilities to detect other exotic states created by light-matter interaction, to interface with superconducting
circuits in hybrid
quantum networks, and to study non-Hermitian physics with Bragg and anti-Bragg cavities.
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All authors B.-Y. Wu, K.-P. Li, G. Chen, W.-M. Zhou, C.-X. Run, K.-M. Hsieh, A. F. Kockum, Z.-R. Lin, W. Nie, I.-C. Hoi