Biological Physics
Computational Insights into Mechanostability and Dissociation Dynamics of the Dengue Virus Envelope Protein Ectodomain Dimer Across pH and Temperature Gradients
Georcki Ropón-Palacios, Luís G. F. Crespi, Jakub Rydzewski et al. (+2 more)
Dengue virus (DENV) is an enveloped flavivirus of major public health importance. Its envelope (E)
protein mediates viral entry through homodimer dissociation and subsequent membrane fusion, making it one of the principal targets for antiviral strategies. To investigate the molecular determinants of this process, we performed steered molecular dynamics (SMD) simulations of the E
protein ectodomain (ecE) dimer from DENV-2 and DENV-3 under variable pH and temperature conditions. Force-extension analyses revealed a highly stable interface for both serotypes, with rupture forces exceeding 1000 pN. pH and temperature had modest effects on overall mechanical resistance. However, DENV-3 displayed a distinct sensitivity to thermal stress compared to DENV-2. We identified a robust, asymmetric dissociation pathway across all conditions, characterized by a metastable intermediate state involving partial dimer opening and exposure of the fusion loop (FL). This intermediate exposes an immunodominant epitope and persists under physiological conditions, suggesting it as a viable target for therapeutic intervention. The primary contributions to the interfacial interaction network were found to arise from van der Waals interactions, followed by hydrogen bonds, salt bridges, and pi-cation interactions. DENV-3 exhibited a slightly greater contribution from polar interactions involving domains EDI, EDII, and EDIII. Furthermore, pairwise occupancy analysis identified pH-sensitive contacts that are disrupted under acidic conditions, particularly in DENV-3, providing mechanistic insight into the early stages of ecE dissociation. Together, these findings provide structural insights into the dissociation mechanism, identifying key metastable states and pH-sensitive interactions that could be exploited to develop antivirals that stabilize the dimer and prevent viral fusion.
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All authors Georcki Ropón-Palacios, Luís G. F. Crespi, Jakub Rydzewski, Walter Rocchia, Alexandre S. de Araujo
Chemical Physics · Cross-listed from cond-mat.soft
Fluctuation-induced ionic friction at solid-electrolyte interfaces
Damien Toquer, Baptiste Coquinot, Nikita Kavokine et al. (+1 more)
In this article, we explore how transport at a solid–electrolyte interface is affected by the internal fluctuations of the solid and quantify the role of solid excitations on ionic friction. Combining molecular dynamics simulations with theoretical modeling, we show that the presence of ions enhances the dynamical response of the electrolyte compared to pure water. This leads to an ionic contribution to the fluctuation-induced interfacial friction. We show that collective ionic modes dominate the dissipation, such that ionic friction arises from many-body effects rather than from individual drag forces. Furthermore, high-frequency molecular modes are found to be ion-specific, suggesting possible routes toward spectral separation of ions, with implications for desalination, filtration, and energy conversion.
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All authors Damien Toquer, Baptiste Coquinot, Nikita Kavokine, Lydéric Bocquet
Atmospheric and Oceanic Physics
Less is more: error-distance scaling relation for data-efficient kilometer-scale downscaling of extreme heat
Ahmed Marey, Henry Lu, Abhishek Gaur et al. (+6 more)
Extreme heat is where urban adaptation needs kilometer-scale data the most, but the simulations training a downscaler can cost more than they save, and how much is needed has not been identified. We measured it with CASPER, a U-Net with a structure-preserving loss downscaling 32 km reanalysis to 1 km temperature, humidity and wind, across 24 configurations of one to eight months. Held-out error grows linearly with climatological distance to the training data, RMSE = 0.83 + 2.95 d, explaining 90% of its variance against 7% for volume and predicting unseen months in advance. On held-out extreme summer weeks CASPER preserves the fine-scale structure and cross-variable physics that matched-budget baselines degrade, and matches station observations during documented heat waves to within 1.8 K. Transfer to a new region degrades geographically; 11 days of local simulation cuts Vancouver's held-out error from 3.8 to 1.3 K. Training periods should span the target
climate: the same accuracy for four times less simulation, putting kilometer-scale downscaling of extreme heat within reach of groups without large computing facilities.
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All authors Ahmed Marey, Henry Lu, Abhishek Gaur, Sherif Goubran, Malek Aloui, Theodore Potsis, David Rolnick, Alex Hernandez-Garcia, Liangzhu Leon Wang
Chemical Physics
Smite: A quasiclassical trajectory (QCT) program for bimolecular collisions and unimolecular dynamics on ab-initio, and machine-learned potential energy surfaces
Péter Szabó, Jenne van Veerdeghem, Jérôme Loreau et al. (+2 more)
We present Smite, a Python toolkit for quasiclassical trajectory (QCT) simulations of reactive and inelastic bimolecular collisions, unimolecular dynamics, and molecular collisions with finite surface models. A central feature is the explicit control of reactant preparation: harmonic normal modes admit fixed
quantum numbers, prescribed energies, thermal
quantum populations, or ground-state Wigner sampling; rotation is prepared at fixed angular-momentum magnitude or from thermal distributions appropriate to diatomic and polyatomic rotors. Rotating-Morse sampling provides a coupled anharmonic treatment of diatomic vibration and rotation, while saved molecular-dynamics phase points provide an alternative source of initial conditions. The same nuclear propagators operate with on-the-fly electronic-structure calculations or user-supplied analytical and machine-learned potential energy surfaces. Additional modules provide constrained rigid-fragment dynamics, thermostat-based preparation, photoionization initial conditions with energy and recoil constraints, and fewest-switches surface hopping (FSSH) on multiple PESs with approximate
curvature-derived couplings. Geometry optimization, transition-state searches, crossing-point optimization, intrinsic-reaction-coordinate following, and thermochemistry use the same energy and derivative interfaces. Analysis tools connect trajectories to product energy partitioning, stereodynamical correlations, time-resolved vibrational signatures, and independent-atom x-ray scattering.
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All authors Péter Szabó, Jenne van Veerdeghem, Jérôme Loreau, Jean-François Müller, Jeremy N. Harvey
Atmospheric and Oceanic Physics
reGRAF: a global MPAS reforecast data set with convection-allowing refinements over the US and Europe
Thomas M Hamill, Akshay Subramaniam, Montgomery Flora et al. (+8 more)
NVIDIA and The Weather Company (TWC) have generated a data set of reforecasts from TWC's GRAF (Global high-Resolution Atmospheric Forecasting) model, a version of the National Center for Atmospheric Research (NCAR) Model for Predictions Across Scales (\href{https://ncar.ucar.edu/what-we-offer/models/model-prediction-across-scales-mpas}{\underline{MPAS}}). GRAF is global, but the configuration for this reforecast had a mesh refinement to \textasciitilde4 km over the US, Caribbean Basin, and Europe, and 15 km elsewhere. This model was designed to run much of the computation on graphical processing units (GPUs), with this development assisted by NVIDIA. The 1836 reforecast cases (\textasciitilde5 years) were generated from ECMWF reanalyses (ERA5) for selected initial condition dates spanning more than 20 years, 2004–2024. These dates of the chosen initial conditions were mostly selected based on high-impact weather in the contiguous US (CONUS) and Caribbean. Sampling in this way, the reforecast spanned a wider range of interesting, high-impact weather scenarios than had we performed five contiguous years of once-daily reforecasts. The reforecast still provides many samples in non-precipitating regions with more ordinary weather. GRAF reforecasts were mostly run to $+$27 h lead time, assuming a 3-h
spin-up followed by a full diurnal cycle. Data were saved in zarr format on the native model vertical coordinate. Most fields were archived at 15-min intervals, though several precipitation variables were saved at 5-min cadence. Data are made publicly available to all through Amazon Web Services' Open-Data Initiative at https://registry.opendata.aws/graf-reforecast.
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All authors Thomas M Hamill, Akshay Subramaniam, Montgomery Flora, Raghu Raj Prasanna Kumar, Karthik Kashinath, Carl Ponder, Tao Ge, Sepideh Khajehie, John Wong, Brett Wilt, Peter Neilley
Plasma Physics
FIREWALL: A surrogate model for the rapid assessment of tokamak wall loading and melting by runaway electrons
Victor Johan Svensson, Tommaso Rizzi, Svetlana Ratynskaia et al. (+4 more)
Runaway electron (RE) beams generated during tokamak disruptions can deposit highly localized heat loads on
plasma-facing components, posing a serious risk of melting and damage. Monte Carlo particle transport simulations coupled with three-dimensional thermomechanical response modeling can quantify this damage but are too computationally demanding for device-scale assessments and extensive scenario scans. We present FIREWALL (Fast Integrated Runaway Electron WALL loads), a surrogate model that combines a database of Geant4 volumetric energy-deposition profiles with a one-dimensional heat-
diffusion solver for each wall element. FIREWALL retains the energy and incident angle distributions of impacting REs and predicts the spatiotemporal temperature
evolution of detailed three-dimensional wall geometries up to the melting threshold. FIREWALL thus provides a fast physics-based framework for translating global RE simulations into global wall melting predictions, enabling large-scale screening of disruption scenarios while directing high-fidelity costly workflows to the limited wall regions where they are actually required.
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All authors Victor Johan Svensson, Tommaso Rizzi, Svetlana Ratynskaia, Hannes Bergström, Luca Venerando Greco, Matthias Hoelzl, Panagiotis Tolias
Atomic Physics
Nuclear moments, charge radii, and magnetization distribution parameters of Ag isotopes from laser spectroscopy and ab initio electronic-structure calculations
Leonid V. Skripnikov, Bram van den Borne, Michail Athanasakis-Kaklamanakis et al. (+2 more)
The nuclear electromagnetic moments and mean-square charge radii of several silver (Ag) isotopes deduced from recent
laser spectroscopy studies in the mass region $A=$ 96-121 are determined using high-accuracy electronic structure calculations performed in this work. We report hyperfine structure and isotope-shift atomic factors calculated with the relativistic coupled cluster approach, including single, double, triple, and perturbative quadruple excitations, CCSDT(Q). Following a systematic theoretical uncertainty analysis, we show that at the precision now achieved (sub-percent uncertainties in some cases),
quantum electrodynamic effects become significant. We also show that the isotope-dependent effect in the hyperfine structure due to the non-point-like nuclear magnetization distribution can be extracted with negligible dependence on the assumed nuclear magnetization model at the present level of precision. This also yields a nuclear
magnetic dipole moment that is corrected for the hyperfine anomaly induced by the Bohr-Weisskopf effect. In terms of the nuclear electric quadrupole moments, the uncertainty in the electric-field gradient used to extract the quadrupole moments from
laser spectroscopy has also been reduced by one to two orders of magnitude relative to values used in previous studies. Finally, the nuclear charge radii of Ag isotopes are extracted using field- and mass-shift factors from our coupled cluster calculations, and the difference in mean-square charge radii between $^{107,109}$Ag agrees with the value deduced from muonic X-ray spectroscopy.
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All authors Leonid V. Skripnikov, Bram van den Borne, Michail Athanasakis-Kaklamanakis, Gleb Penyazkov, Ruben P. de Groote
Fluid Dynamics · Cross-listed from cond-mat.soft
Liquid crystalline order and its impact on shape evolution of fluid lipid membranes
Ingo Nitschke, Maik Porrmann and Axel Voigt
Dynamic approaches to minimize the classical
curvature-elasticity free energy for a fluid lipid membrane, are extended towards a Surface Beris–Edwards–Helfrich model. This extension explicitly treats the
liquid crystal structure of the membrane, which results from the lipid molecules, that are, on average, oriented normal to the surface. Locally varying
liquid crystal order leads to local variations in bending rigidities and surface viscosity and thus influences the shape
evolution. This provides a multiscale coupling between the local membrane mechanics on the level of the lipids and the mesoscopic length and time scales of biological functions. The model is derived using the Lagrange–d'Alembert principle. We provide a numerical
algorithm to solve the equations in the one-constant approximation and demonstrate the impact on the emerging
equilibrium shapes, which not only depend on the specified conserved surface area and enclosed volume, as for the classical
curvature-elasticity free energy, but also the elastic parameter. Exploring the dynamic
evolution shows a tight coupling of tangential flow, shape
evolution and
liquid crystalline order. We further point to extensions towards lipid phase separation and asymmetric lipid bilayers.
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Chemical Physics
Smart Machine Learning for Solving the Full Electron-Nuclear Schrödinger Equation with a Quantum-Chemically Inspired Wavefunction Ansatz
Yaolong Zhang, Bin Jiang and Hua Guo
Directly solving the full electron-nuclear Schrödinger equation remains one of the grand challenges in
quantum mechanics. Here, we propose a
quantum-chemically motivated orbital-based neural network wavefunction ansatz with explicit many-body electron-electron correlation terms, with parameters depending on the entire electron-nuclear configuration, enabling an accurate description of strongly correlated and/or multi-reference electronic structures by a single Slater-determinant across a broad nuclear configuration space. To train this wavefunction, we further develop an efficient hybrid optimization strategy that combines the variational Monte Carlo technique with local-energy constraints, mitigating the intrinsic sampling bias of the former and considerably reducing the statistical error. These advances are embedded in a unified neural network framework, Schrödinger, enabling the determination of globally accurate potential energy surfaces with a single training for systems ranging from strongly correlated diatomic molecules, triatomic reactions containing conical intersections, to polyatomic multi-reference molecules. This work offers a practical machine-learning tool for solving the electron-nuclear Schrödinger equation and capturing full
quantum effects beyond the Born-Oppenheimer approximation.
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Fluid Dynamics · Cross-listed from astro-ph.EP
Flow dynamics of cryolava or impact melt on Titan's surface
Daniel Cordier, Bastien Bodin, Stephane Le Mouelic et al. (+1 more)
Titan, a unique body in the solar system, resembles a life-size Miller-Urey experiment where pockets of
liquid water might interact with abundant organic matter. Its young surface (less than a billion years) shows signs of material exchange with the interior, and an isotopic signature is detected in the atmosphere. Cryovolcanism and meteor impacts represent potential high energy mechanism for these exchanges. Although cryolava or impact melt properties are largely unknown, Titan's internal structure makes a significant water content in these fluids highly probable. The temperature of these fluid mixtures at the onset of the flows is above 0~$^\circ$C. The primary objective of this work is to investigate the dynamical and thermal properties of potential Titanian flows, while ensuring their spatial extents remain broadly consistent with the few available observations. We also aim to assess whether their
evolution could enable the hydrolysis of encountered organic material. On Earth, in the context of lava flow risk assessment, numerical techniques based on cellular automata have been developed for many years. This approach allows simulating the flow of Bingham fluids over distance scales of several tens of kilometers. In the context of Titan's surface, and within the explored parameter space, flows with a spatial extent of several tens of kilometers can be produced with our model. The resulting flow thickness is about a meter. The flow extent is primarily controlled by the total erupted volume and the terrain
topology. As expected, the rheology and thermo-physical properties of the erupted fluid have significant influence on the flow's extent and the cooling rate of the cryolava. We predict hydrolysis reactions between an aqueous cryolava and the organic matter likely ubiquitous on Titan's surface. Our model code is publicly available.
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All authors Daniel Cordier, Bastien Bodin, Stephane Le Mouelic, Ashley G. Davies
Applied Physics
Bilayer Lithium Niobate Acoustic Resonators for Spurious-Free Wideband Operation at 6 GHz
Florian Hartmann, Silvan Stettler and Luis Guillermo Villanueva
The
evolution of wireless communication standards toward higher frequencies and wider bandwidths places increasing demands on acoustic filter technologies. Conventional resonators face scaling limitations above 5 GHz, where lithographic constraints, reduced electromechanical coupling coefficient (k2eff), and spurious mode excitation hinder practical filter implementation. Here, we introduce a bilayer X-cut lithium niobate (LiNbO3) thickness-shear bulk acoustic resonator architecture that leverages
symmetry engineering as a new design degree of freedom. By vertically stacking two piezoelectric thin films with a tailored bonding angle, the second-order thickness-shear mode (SH2, slow) is selectively excited. Furthermore, the fast thickness-shear modes inherent to X-cut LiNbO3 are suppressed, yielding a spurious-free in-band response. Devices operating around 6 GHz demonstrate a k2eff of approximately 35%, in close agreement with finite-element simulations and confirming the
symmetry-driven mode selection mechanism. Proof-of-concept ladder filters demonstrate a fractional bandwidth of 18.6%, highlighting the wideband capabilities of the proposed architecture. The proposed configuration enables thickness-defined frequency scaling while maintaining high coupling and spectral purity, offering a promising platform for wideband radiofrequency filters in next-generation wireless systems.
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Optics · Cross-listed from cond-mat.quant-gas
Room-temperature polariton supersolids
Yuanhao Gong, Jingwen Ma, Shuang Zhang et al. (+2 more)
Exploring exotic
quantum phases of matter at room temperature represents a frontier challenge in modern physics. The supersolid phase, uniquely merging crystalline order with frictionless superfluid flow, stands among the most intriguing macroscopic
quantum phenomena. However, all previous demonstrations of supersolidity, whether in ultracold atomic gases or III-V
semiconductor-based polariton systems, have been strictly confined to cryogenic temperatures. Here, we report the observation of room-temperature supersolids in photonic-
crystal polariton condensates. By integrating a room-temperature-stable perovskite
semiconductor with a dispersion-engineered photonic-
crystal waveguide, we create a polariton condensate with multi-mode dispersion landscapes and pronounced parametric nonlinearities. Above a critical condensation density, the interacting condensates spontaneously break continuous translational
symmetry, creating a non-rigid supersolid phase that simultaneously exhibits emergent crystalline order and global
quantum coherence. This work establishes a room-temperature platform for investigating
quantum hydrodynamics and developing coherent
quantum simulation devices.
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All authors Yuanhao Gong, Jingwen Ma, Shuang Zhang, Xiaobo Yin, Xiang Zhang
Accelerator Physics
Compact ultrafast intense LWFA-driven crystal-based source of $\gamma$-radiation, positrons and neutrons
Alexei Sytov, Hyeon Myung Jeong, Leejin Bae et al. (+5 more)
Compact sources of intense $\gamma$-rays, positrons and
neutrons can bring radiation and particle-beam capabilities to small university-scale laboratories that would otherwise rely on large accelerator facilities. Here we propose and simulate a compact,
laser-driven source that combines
laser plasma wakefield acceleration (LWFA) with oriented crystalline targets to enhance the conversion of relativistic electron beams into high-energy
photons and secondary particles. Electrons aligned with major crystallographic directions undergo coherent interactions, including channeling radiation and coherent bremsstrahlung, producing substantially enhanced
photon emission compared with amorphous targets. Moreover, the strong angular-spectral correlation of the emitted radiation enables the generation of collimated $\gamma$-ray beams with reduced spectral bandwidth. Consequently,
crystal-enhanced emission can increase particle-production efficiency, namely that of positrons through $\gamma$ conversion into electron-positron pairs and of
neutrons through photonuclear reactions. Using Geant4 simulations, we investigate electron energies of 300 MeV, 1 GeV and 3 GeV interacting with an oriented tungsten
crystal.
Crystal orientation increases the $\gamma$-ray, positron and
neutron yields by up to a factor of $\sim2$, reaching production rates of $\sim10^{24}\gamma/s$, $\sim10^{23}e^+/s$ and $\sim10^{21}neutrons/s$ for a 200 pC electron bunch with a duration of a few fs. The collimated $\gamma$-ray brightness reaches $\sim10^{24}\gamma/s/mm^2/mrad^2/0.1\%BW$, with an enhancement of 6-8 compared with random
crystal alignment. We further demonstrate tunable quasi-monochromatic radiation through coherent bremsstrahlung in a thin diamond
crystal, reaching a brilliance of $\sim3.5\cdot10^{20}\gamma/s/mm^2/mrad^2/0.1\%BW$. Furthermore, we discuss the potential applications of the technique proposed.
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All authors Alexei Sytov, Hyeon Myung Jeong, Leejin Bae, Iryna Chaikovska, Hyoeun Choi, Gianfranco Paternò, Laura Bandiera, Inhyuk Nam
Fluid Dynamics
A Reynolds-like Criterion for the Onset of Universal Active Turbulence
Kunal Kumar, Sandip Sahoo, Kirti Kashyap et al. (+4 more)
Beyond a critical Toner–Tu drive, bacterial
turbulence exhibits universal statistics, including a parameter-independent energy spectrum $E(k)\sim k^{-3/2}$. We show that the same universal state can be reached not only by increasing activity, but also by strengthening nonlinear advection, weakening nonlinear saturation, or tuning the Swift–Hohenberg instability. Motivated by the competition between these processes, we identify the independent dimensionless groups governing the dynamics and construct a Reynolds-like control parameter from them. A single critical value, calibrated from the known activity-controlled transition, predicts the onset of universality along the other parameter routes and collapses them onto a common threshold. These results identify a dynamical organizing parameter for the onset of universal active
turbulence and provide a Reynolds-like measure for the Toner–Tu–Swift–Hohenberg universality class.
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All authors Kunal Kumar, Sandip Sahoo, Kirti Kashyap, Amal Manoharan, Siddhartha Mukherjee, Anupam Gupta, Samriddhi Sankar Ray
Optics
Confocal imaging from biphoton correlations
Euan Millar, Emma Pearce, Daniele Faccio et al. (+1 more)
Confocal microscopy provides optical sectioning for three-dimensional imaging but conventionally relies on point-by-point scanning and physical pinholes, limiting imaging speed. Here, we demonstrate that confocal sectioning can instead arise directly from
quantum measurement, using spatial correlations in entangled biphoton states. Spatially resolved coincidence measurements in a widefield imaging system suppress contributions from out-of-focus planes, producing optical sectioning in parallel across the whole field of view without physical pinholes or mechanical scanning. In addition, this
quantum approach obtains an axial response that, as a result of position-momentum
entanglement, is $\sqrt{2}$-times narrower than that of classical confocal imaging. Our work establishes biphoton correlations as a mechanism for improved confocal imaging and enables parallel, pinhole-free optical sectioning without mechanical scanning.
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All authors Euan Millar, Emma Pearce, Daniele Faccio, Miles J. Padgett
Optics
Near-field Ultrafast Nondiffractive Laser Nanoscale Cutting of Glass with Quasi-null Interface Roughness
Rajeev Dwivedi, Anton Rudenko, Guodong Zhang et al. (+5 more)
Generally, ultrafast
laser glass dicing is governed by explosive material removal, which restricts the achievable surface roughness. Here we report single-step dicing of aluminosilicate glass with residual interface roughness below 5 nm, producing optical-quality surfaces without post-processing, using near-field-enhanced 0th-order Bessel-Gauss beams. This exceptional interface quality cannot be explained by a conventional
laser ablation mechanism, such as phase explosion, melt expulsion, or fracture-dominated material removal. Instead, quantitative analysis of local thermal dynamics indicates that material removal is consistent with a Hertz-Knudsen-type evaporation process, enabling layer-by-layer removal with precision approaching a few molecular layers. These results suggest that nanoscale optical confinement fundamentally alters the response of transparent materials to ultrafast
laser irradiation and establish a route toward deterministic
laser processing with near-atomic precision.
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All authors Rajeev Dwivedi, Anton Rudenko, Guodong Zhang, Xxx Sedao, Yaya Lefkir, Ciro D'Amico, Guanghua Cheng, Razvan Stoian
Optics
Non-additive surface and volume backscattering from a rough interface over a correlated random medium
Mariano Franco and Esteban Calzetta
We compute the first-order incoherent backscattering cross-section of a rough surface over a half-space with randomly fluctuating permittivity, when the two random fields are correlated, so that surface and volume scattering are not additive. A non-orthogonal coordinate transformation flattens the rough boundary and turns the
geometric roughness into volume sources of the same Helmholtz equation as the dielectric fluctuations, propagated by the same Green's function: both mechanisms and their interference follow from one calculation, with no equivalent surface currents and no prescription for the field discontinuity. The
geometric part of the amplitude reproduces the small-perturbation kernel exactly, for any incidence angle, permittivity and profile function. The interference term is obtained for both co-polarized channels, with an explicit surface-dielectric correlation coefficient. The departure from additivity reaches twenty percent at full correlation, changes sign with that coefficient, and is governed by a balance condition and a coherence condition on the depth of the correlated layer. It carries no angular signature and shifts the co-polarized ratio by less than a tenth of a decibel, so an additive inversion absorbs it, biasing the retrieved amplitude of the dielectric fluctuations by tens of percent.
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Applied Physics
Evaluating Advanced Impact Mitigation Technologies for Concussion Risk Reduction in Youth Cycling Helmets
Jessica A Towns, Fady F Abayazid, Gerald A Grant et al. (+2 more)
The efficacy of advanced cycling helmet technologies under youth-specific impact conditions remains unclear. We evaluated how helmet technologies affect head kinematics and concussion risk and whether helmet deformation and helmet-headform relative rotation contribute to protection. Six youth bicycle helmet technologies were tested, including two conventional EPS controls (FOAM-A, FOAM-B) and four advanced technologies (
CELL, SLIP, SLIDE, HYDRAULIC). Helmeted headforms were impacted at three locations using a 25 degree anvil at 2.9 m/s, and a 45 degree anvil at 5.2 m/s. Peak linear acceleration (PLA), peak rotational acceleration (PRA), and YGAMBIT-predicted concussion risk were quantified. Stereo high-speed videography measured anvil-normal headform displacement to approximate helmet deformation, and helmet-headform relative rotation. Helmet technology significantly affected predicted concussion risk under both conditions. At 2.9 m/s, all advanced technologies reduced risk relative to FOAM-A, while only SLIDE and HYDRAULIC reduced risk relative to FOAM-B. At 5.2 m/s, all advanced technologies reduced risk relative to both foam controls. HYDRAULIC produced the lowest risk in both conditions, reducing mean risk by 94-95% and 77-78% relative to the foam controls at 2.9 and 5.2 m/s, respectively.
CELL, SLIP, and SLIDE significantly reduced PRA across both conditions, whereas HYDRAULIC significantly reduced both PLA and PRA. Greater anvil-normal headform displacement was associated with lower PLA, and greater relative rotation with lower PRA; both independently contributed to lower predicted concussion risk. Advanced technologies in youth cycling helmets can reduce youth concussion risk, but effectiveness depends on impact condition and mitigation mechanism. Designs maximizing controlled helmet deformation and rotational decoupling may provide robust protection in youth-relevant impacts.
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All authors Jessica A Towns, Fady F Abayazid, Gerald A Grant, David B Camarillo, Nicholas J Cecchi
Applied Physics · Cross-listed from cond-mat.mes-hall
Multi-Branch Transport in a Back-gated WS$_2$ Transistor at Deep-Cryogenic Temperature
Megan Powell, Vilas Patil, Hazel Neill et al. (+5 more)
Two-dimensional materials are promising candidates for electronic applications beyond the operating limits of conventional
semiconductor technologies. Within this class, transition-metal dichalcogenides offer attractive properties for field-effect transistor operation, with tungsten disulphide (WS$_2$) emerging as a particularly promising material for operation at cryogenic temperatures. Here, we investigate the electrical performance of a back-gated multilayer WS$_2$ transistor at deep cryogenic temperature, down to 20 mK. The device remains strongly gate-tunable throughout the cryogenic regime, with an effective on/off current ratio exceeding $10^{5}$. Most notably, the low-temperature turn-on characteristics exhibit reproducible shoulder-like features, which we describe using a phenomenological model comprising multiple effective conduction branches operating in parallel.
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All authors Megan Powell, Vilas Patil, Hazel Neill, Stephen O'Sullivan, Paul K. Hurley, Lida Ansari, Farzan Gity, Alessandro Rossi
Atomic Physics · Cross-listed from quant-ph
Parallel algebraic surgery for qLDPC codes with constant shuttling depth
Tian-Gang Zhou, Boren Gu, Jens Eisert et al. (+1 more)
Reconfigurable atom arrays provide a promising platform for high-rate
quantum low-density parity-check codes, but their computational advantage depends on whether logical operations can be implemented without incurring prohibitive shuttling and space overheads. We introduce algebraic surgery for lifted product codes, co-designing the logical measurements, auxiliary codes, and atom shuttling to enable hardware-efficient Pauli-product measurements. These protocols provide flexible logical addressability subject to the cyclic-
symmetry constraint, enabling a broad class of parallel logical measurements, including canonical logical operators with heavily overlapping physical supports and joint measurements within or between code blocks even with different lift sizes, while achieving constant shuttling depth on neutral-atom processors under explicit layout assumptions. In a representative hardware-model
benchmark, a cycle supporting 33 parallel canonical logical measurements is about $2\times$ faster than the compared single-observable graph-based surgery schedules, with competitive
qubit overhead. These shuttling and
circuit-level simulations confirm that the algebraic structure of
quantum low-density parity-check codes can be used not only to reduce space overhead, but also to simplify physical implementation and expand the set of efficiently accessible logical operations on neutral-atom processors.
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All authors Tian-Gang Zhou, Boren Gu, Jens Eisert, Chen Zhao
Accelerator Physics
Beam Tracking I & II
Helga Timko
Longitudinal beam dynamics simulations are an essential tool for the design and operation of circular and linear accelerators alike, fundamentally supporting everything from RF system design to the interpretation of beam-based measurements. This paper gives a practical, self-contained introduction to longitudinal beam tracking, aimed at newcomers to the field who wish to build, or better understand, their simulation tools. Starting from the analogy between beam tracking and particle-in-
cell plasma simulations, the basic equations of motion, their discretisation, and the choice of phase-space coordinates are introduced, followed by the collective effects driven by the machine impedance. The modelling of the RF system and its associated control loops, and the generation and matching of realistic particle distributions are discussed thereafter. Selected topics that require a fully six-dimensional treatment are briefly touched upon, before closing with practical guidance on the design, optimisation, and benchmarking of longitudinal tracking codes.
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Physics and Society
Opinion dynamics under large-scale exogenous events
Gerard Argany Herrera, Lucila G. Alvarez-Zuzek and Oriol Artime
Large-scale events such as political scandals or misinformation campaigns can abruptly shift the collective opinion of a population and reshape the dynamics in ways that standard local-interaction models of sociophysics do not capture. Here, we investigate the dynamics of opinion formation when a group of interacting
agents is subjected to sudden, macroscopic exogenous shocks. Our framework is general and applies to arbitrary opinion dynamics models; to illustrate its scope, we consider the voter model and variations thereof. We verify that the mathematical description is excellent in describing the first-passage properties to consensus of the voter model on the complete graph and on complex networks. Remarkably, we identify the conditions under which shocks can be advantageous or detrimental to reach consensus. For the case of the all-to-all noisy voter model under exogenous events, we unveil a rich phase diagram characterized by novel trimodal and asymmetric bimodal states. Ultimately, this work provides a rigorous yet flexible
stochastic-process framework for understanding the out-of-
equilibrium behavior of opinion dynamics under recurrent exogenous stressors.
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Optics · Cross-listed from quant-ph
Optical measurement is almost quantum: Quantum inspired universal optical bounds
Daniel Ish and Chase T. Ellis
Inspired by results in
quantum information, we report the development of a formalism for optical sensing which abstracts the details of specific optical systems and allows us to form general bounds on measurement based only on the quantity to be measured. We find a universal bound that controls the performance of any passive optical system regardless of the technology used to construct it and that this bound is attained by a unique measurement scheme for each quantity of interest. Shockingly, our optical formalism is nearly identical to the
quantum formalism, with essentially the same notions of the state to be measured and the operation of the measurement, along with an accompanying uncertainty principle.
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Fluid Dynamics
Is Vorticity Amplification Essential for Anomalous Dissipation and Intermittency in Turbulence?
Alessandro Chiarini
The distinct dynamical roles of vorticity amplification (VA) and
vortex tilting (VT) in three-dimensional homogeneous isotropic
turbulence are investigated using direct numerical simulations of a modified Navier–Stokes system. By selectively suppressing VA while retaining VT, we demonstrate that gradient amplification by VA is strictly required to sustain the classical forward energy cascade. Progressively suppressing VA weakens small-scale velocity gradients, heavily depletes extreme fluctuations, and entirely eliminates the classical energy dissipative anomaly, causing the normalized energy dissipation to decay as $Re_\lambda^{-1}$. In the limit of complete VA suppression, enstrophy emerges as the relevant inviscid invariant. Scale-by-scale budget analyses confirm that the dynamics transition to a purely forward enstrophy cascade, characterized by an anomalous enstrophy dissipation and a robust $E(k) \sim k^{-3}$ intermediate energy spectrum. We verify that these asymptotic scaling limits—including a $Re_\lambda^{-1/2}$ finite-Reynolds-number correction for the enstrophy anomalous dissipation—are universal properties of the VA-suppressed dynamics, independent of whether the large-scale forcing is helical or non-helical. Remarkably, despite the smoothing of the velocity field and the elimination of the energy dissipative anomaly, anomalous structural scaling and a broad multifractal spectrum persist. These results reveal a fundamental mechanistic separation: while VA is responsible for amplifying intense localized fluctuations,
geometric reorganization by VT alone is mechanically sufficient to sustain multifractal intermittency.
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Optics · Cross-listed from cond-mat.mtrl-sci
Phonon-mediated closing of topological Floquet gaps in graphene: Non-phenomenological analysis
Royi Ledermann, Rave Hanoch Saadon, Adam Herling et al. (+1 more)
Floquet band engineering has been intensively studied for its potential to control material properties via
laser driving. In particular, Floquet topological states have been measured on the surface of Bi$_2$Se$_3$. Nonetheless, the original prediction of Floquet topological bands in
graphene remains unobserved, with works only measuring non-topological Floquet-Bloch states or indirect features. Here, we theoretically explore
graphene irradiated by circular
lasers with non-phenomenological electron-
phonon (e-ph) coupling. We show that e-ph interactions substantially broaden Floquet bands due to
graphene's large zero-point motion, as expected from phenomenological treatments. However, we further find that larger displacement $\Gamma$ optical
phonons reduce Floquet gaps by about half, even in absence of instrumentation broadening, and can also induce additional features like flat bands. These
phonons "enter the gap" and blur photoemission signatures. Including non-$\Gamma$
phonons closes the gap and greatly reduces visibility. When these modes couple to reasonably expected instrumentation broadening, the effect is significantly exacerbated. Our results shed light on the missing Floquet topological gaps and also lead to possible mitigation strategies: (i) Pre-pumping coherent
phonons to counteract blurring, or (ii), transition to a Dirac system with more favorable
phonon statistics. Moreover, our real-space analysis proposes that Floquet topological physics is alive in localized regions, such that properties of interest like transport should be accessible. We expect this work to impact experimental analysis and lead to set-ups where
graphene Floquet
topology might finally be directly observed.
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All authors Royi Ledermann, Rave Hanoch Saadon, Adam Herling, Ofer Neufeld
Applied Physics · Cross-listed from cond-mat.mtrl-sci
A transferable full-band Monte Carlo framework for complex alloy avalanche photodiodes
Shafat Shahnewaz, Hannaneh Karimi, Joe C. Campbell et al. (+1 more)
We present a physics-based multiscale full-band Monte Carlo framework for modeling avalanche multiplication and excess noise in complex
alloy avalanche photodiodes (APDs), demonstrated on Al$_{0.7}$InAsSb as a representative quaternary system. The framework links atomistic material structure to device-level avalanche statistics: an environment-dependent $sp^3d^5s^\ast$ tight-binding calculation resolves the full conduction- and valence-band structure of the random- or digital-
alloy configuration – including $\Gamma$, X, and L valley ordering, non-parabolicity, anisotropy, and
spin-orbit-induced valence-band splitting – and supplies the band-structure inputs for
stochastic high-field transport. A central element of the framework is a physics-derived treatment of
alloy-disorder scattering, in which the quaternary disorder potential is constructed from atomic valence differences, covalent radii, and Thomas–Fermi screening through a composition-weighted decomposition into binary contributions, complemented by composition-interpolated polar-optical, acoustic, intervalley-
phonon, impurity, and impact-ionization models. Because every material-dependent input is generated from the atomic composition and configuration by the same well-defined procedure, the framework transfers without structural modification to arbitrary zinc-blende ternary and quaternary
alloys. Applied to a \SI{1}{\micro\meter} Al$_{0.7}$InAsSb p-i-n APD, the framework reproduces the measured gain and excess-noise characteristics with only the impact-ionization softness parameters calibrated. The approach provides a documented, reproducible route for analyzing and designing complex
alloy APDs in which band structure, disorder, and scattering physics jointly determine gain and ionization statistics.
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All authors Shafat Shahnewaz, Hannaneh Karimi, Joe C. Campbell, Avik W. Ghosh
Applied Physics · Cross-listed from cs.LG
TopTimeNet: Topologically-assisted time-series classification model
Sharareh Sayyad and Sophia Bazzi
Distinguishing periodic from chaotic dynamics in a time series is a fundamental challenge in both physics and engineering. Yet, end-to-end learned architectures must discover both a representation and a decision boundary from data, at substantial cost. We introduce TopTimeNet, which decouples these tasks: a fixed, non-learned stage extracts a $42$-dimensional
geometric and topological descriptor from Takens delay
embeddings and persistent homology, and a lightweight learnable stage performs classification. On a
benchmark of $49$ nonlinear dynamical systems, a $1{,}638$-parameter configuration matches the mean accuracy of one with $33\times$ more trainable parameters. Additionally, this approach delivers mean accuracy comparable to convolutional neural networks and surpasses the average performance of converged
Transformer models, while requiring three to four orders of magnitude fewer trainable parameters. Robustness also depends sharply on where noise is introduced: TopTimeNet degrades gracefully under perturbations to its precomputed features, but degrades sharply when noise is introduced into the raw signal and the full feature-extraction pipeline is recomputed, showing that robustness to perturbations of the precomputed features does not imply robustness of the complete raw-signal-to-prediction pipeline. These results show that decoupling fixed
geometric and topological feature construction from a lightweight discriminative stage can achieve comparable classification accuracy with substantially fewer trainable parameters.
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Optics
Topological Fermi-polaron Polaritons with Electrically Invertible Topology
Xin Xie, Chenxi Liu, Yuze Liu et al. (+8 more)
Topological polaritons provide a route to engineer optical Chern bands, but realizing large gaps or efficient electrical tunability remains challenging because time-reversal-
symmetry breaking in
semiconductor polariton systems is typically limited by weak Zeeman splittings. Here, we demonstrate a topological Bose-Fermi mixture — Fermi-polaron polaritons —where large gaps and electrically invertible
topology emerge from the interplay of Fermi-polaron many-body interactions, photonic
symmetry, and strong light–matter coupling. Using a gate-controlled monolayer transition-metal dichalcogenide integrated with a
symmetry-engineered photonic
crystal, we create Fermi-polaron polaritons with topological band structures. The direct coupling between band
topology and gate-tunable many-body interactions provides a mechanism for amplified time-reversal-
symmetry breaking beyond bare Zeeman splitting and enables electrical inversion of topological gaps, Berry
curvature, and Chern numbers. These results establish an electrically reconfigurable platform for interaction-driven topological states and programmable topological photonics.
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All authors Xin Xie, Chenxi Liu, Yuze Liu, Lingxiao Zhou, Chulwon Lee, Yuhan Zhang, Nathanial Lydick, Kenji Watanabe, Takashi Taniguchi, Kai Sun, Hui Deng
Computational Physics · Cross-listed from cs.LG
Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction
Thomas Egg, Harry Winston Sullivan, Maya M. Martirossyan et al. (+8 more)
Crystal structure governs material properties, making
crystal structure prediction (CSP) a fundamental problem in materials science. Generative models are a promising approach for solving this problem, but the prevalence of polymorphism, coupled with large unit
cells and complex packing geometry, makes the molecular CSP task challenging for existing models. To address this, we introduce Coarse-Grained Open Materials Generation (CG-OMatG), an equivariant Riemannian flow-based generative model. CG-OMatG predicts molecular
crystal structures via a coarse-grained, hierarchical representation. CG-OMatG treats molecules as rigid bodies—performing both inter- and intra-molecular message passing to construct a
geometric representation for molecular packings—and learns to reconstruct molecule centroid positions, orientations, and
lattice parameters, conditioned on chemical species and conformer geometry. We train the model on subsets of the Open Molecular
Crystals (OMC25) and Cambridge Structural Database (CSD)
datasets. Further, we fine-tune the model via policy gradient reinforcement learning to steer the model towards generating low-energy candidate structures. We validate the generated structures on the CSP blind test
benchmark, assessing agreement with experimentally determined
crystals using COMPACK packing-similarity analysis. CG-OMatG exhibits strong performance for generative molecular
crystal structure prediction, paving the way for accelerated polymorph screening and organic solid-state materials discovery.
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All authors Thomas Egg, Harry Winston Sullivan, Maya M. Martirossyan, Philipp Höllmer, Cheng Zeng, Adrian Roitberg, Mingjie Liu, Richard Hennig, Sapna Sarupria, Ellad B. Tadmor, Stefano Martiniani
Biological Physics · Cross-listed from cond-mat.soft
Curvature-induced migration of small domains on lipid membranes
Jaime Agudo-Canalejo
Membrane
curvature has been shown to bias the location of lipid or
protein domains, but the roles of bending rigidity, spontaneous
curvature, Gaussian bending modulus, and line tension are difficult to separate in general. We develop a small-domain description for a membrane whose shape is held fixed, e.g. by strong adhesion to a curved substrate. Combining a local Helfrich energy with the small-area isoperimetric expansion gives a position-dependent energy determined by the local mean and Gaussian
curvatures. We identify four generic regimes of
curvature preference whose boundaries depend on only two dimensionless parameters. On specific membrane shapes with complex
curvature, we show that this
curvature preference determines the energy landscapes experienced by small domains, which are strongly dependent on the size of the domain through the line tension contribution. For example, on an oblate-shaped membrane, very small domains tend to localize at the poles, whereas larger domains prefer to localize at the equator. Whether this transition is continuous or discontinuous is found to strongly depend on the spontaneous
curvature of the domain. This ordering suggests a mechanism by which small domains can collect and coalesce at one location before relocating as they grow.
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