Computational Physics · Cross-listed from hep-ph
Transient PULSE: Code for the Transient Propagation of UltraLight (pseudo)Scalars to Earth
Jason Arakawa, Charles Cheung, Muhammad Hani Zaheer et al. (+2 more)
We present Transient PULSE, a software package that numerically implements a previously developed source-to-detector framework for transient ultralight bosonic signals from astrophysical bursts. Predicting these signals relies on connecting the source emission spectrum to its
evolution during propagation and the resulting observables at a terrestrial detector. The package discretizes a user supplied energy spectrum into momentum modes, propagates them through a specified matter density profile and constructs the time-frequency energy density distribution at Earth, accounting for dispersion and in-medium screening effects. This treatment accommodates non-Gaussian source spectra and provides inputs for detector specific analyses. A complementary analytical module estimates coupling sensitivities, arrival time delays and screening thresholds from parameterized source and detector properties.
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All authors Jason Arakawa, Charles Cheung, Muhammad Hani Zaheer, Volodymyr Takhistov, Marianna Safronova
Space Physics · Cross-listed from astro-ph.EP
Revealing the Spatial Distribution of Dust and Plasma Solitary Waves in Jupiter's Innermost Magnetosphere Using Juno Waves Observations
Wenyu Zhang, Hao Cao, William S. Kurth et al. (+6 more)
Jupiter's faint ring system contains micron- and submicron-sized dust whose dynamics are influenced by the
planet's rapidly rotating
magnetic field. Optical observations have established the morphology of the main ring and
halo, but tenuous dust close to Jupiter remains difficult to characterize. We analyze nearly a decade of in-situ Juno Waves electric-field measurements using a two-stage convolutional neural network to identify and classify dust impacts, solitary waves, and other
plasma waves. These in-situ dust-impact detections reveal a radially evolving structure extending well inside the traditionally observed
halo. In the innermost region, dust is concentrated in a compact, equatorially symmetric layer, indicating that the optical inner boundary does not mark the end of the dust population. Farther outward, the layer expands vertically into a broad
halo before contracting toward the main ring, directly revealing the toroidal morphology of the Jovian
halo. Dust number density is enhanced within the
halo and near the main-ring–
halo transition. The vertical distribution also develops hemispheric asymmetries that vary with radial distance, consistent with an influence of Jupiter's
magnetic geometry on charged-dust dynamics. In contrast, solitary waves occur predominantly at high latitudes, and their mapped
magnetic footprints show a strong spatial correspondence with Jovian auroral structures, particularly the main auroral oval. Together, these in-situ measurements extend the remote-sensing picture of Jupiter's rings and reveal previously unresolved dust and
plasma structures in its innermost magnetosphere.
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All authors Wenyu Zhang, Hao Cao, William S. Kurth, Mitchell M. Shen, Darrelle Wilkinson, Donglai Ma, Martin Brennan, George Hospodarsky, Scott J. Bolton
Geophysics · Cross-listed from stat.AP
Probabilistic AI models outperform numerical weather prediction models on record breaking heat extremes
Jakob Benjamin Wessel, Fiona Spuler, Christopher A. T. Ferro et al. (+2 more)
AI weather prediction (AIWP) models have emerged as a key complement to physics-based numerical weather prediction (NWP) models, and now often outperform them on aggregate skill. Yet, several studies report that physics-based models still forecast extreme events better, in particular record-breaking extremes, based on the evaluation of deterministic forecasts. Here we evaluate heat extreme forecasts from probabilistic AIWP models over global land and show that they clearly outperform the ECMWF IFS ensemble, both raw and post-processed, including for record-breaking events, in all regions and at all lead times considered. AIWP models better forecast the occurrence and intensity of extremes, are better calibrated in the tail and miss fewer records. Station observations confirm these results. We argue that many reported AIWP limitations stem from unsuitable verification choices, specifically comparing deterministic forecasts that target different quantities. Instead, a fair evaluation of extremes necessitates probabilistic verification.
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All authors Jakob Benjamin Wessel, Fiona Spuler, Christopher A. T. Ferro, Marlene Kretschmer, Sebastian Sippel
Applied Physics
Effect of deep-trap density of states for a-Si:H layers on HIT cell performances: Modeling Framework
Tewfik Souier and Adel Gougam
In this work, an aSi and cSi heterojunction solar
cell with an intrinsic layer is simulated using AFORS-HET software. The study focuses on the role of the electronic density of states DOS of the amorphous emitter, p type aSiH, in governing the performance of the HIT
cell and the electronic transfer across the heterointerface. It is found that the DOS of the p type aSiH emitter can cause an unfavorable recombination and trapping effect, which becomes more severe and difficult to avoid when the bulk dangling-bond density in the a-Si emitter approaches or exceeds the doping concentration. An increase in deep trap density beyond a critical value causes a drop in the built in voltage and shifts the depletion layer into p type aSi. This situation leads to a sharp decline in HIT
cell performance, namely the open
circuit voltage and the fill factor, and to the appearance of an S shaped IV characteristic. The simulation results suggest that the emitter activation energy needs to be optimized to achieve high efficiency. Under optimal conditions, holes accumulate near the heterojunction interface, leading to the formation of an inversion layer. This paper presents a physical mechanism for recombination processes within the emitter and concludes with the optimized parameters required to achieve a HIT
cell efficiency comparable to Sanyo record of 23 percent on a thin silicon wafer.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Structural identification in general crystalline systems via Voronoi cell topology
Emanuel A. Lazar and Chris H. Rycroft
Widely used methods for identifying
crystal structure in atomistic simulations are limited in practice to a handful of simple structures, leaving many important crystalline systems without automated classification techniques. Voronoi
topology analysis offers a route to classifying arbitrary crystalline and defect environments, but realizing this potential first requires enumerating the Voronoi
cell topologies that can arise under thermal perturbation of a structure of interest. We present an
algorithm that deterministically enumerates all Voronoi
cell topologies arising from generic infinitesimal perturbations of an arbitrary
crystal structure, producing structural classifiers that extend automated identification to general crystalline systems. We demonstrate the approach on several structures of general interest.
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Chemical Physics
Cartesian and Curvilinear Anharmonic Frequencies and Intensities: Perturb-then-Diagonalize Polyad Transport and Adiabatic Discrete-Variable Representation
Vincenzo Barone
Anharmonic intensities reveal vibrational coupling that band positions alone cannot determine. We derive explicit second-order infrared transition moments in curvilinear normal coordinates, including kinetic metric derivatives and transport through variational resonance polyads. The vibrational perturbation-to-second-order-then-diagonalization (VP2TD) treatment covers fundamentals, overtones, three-
quantum transitions, and hot bands. A general computational platform combines Extended
Symmetry-Adapted Local Coordinates (ESALCs), using Cartesian (ESALC-C) or internal (ESALC-I) primitives, with interchangeable
quantum-chemical programs and parallel finite differences. Independent oscillator
matrices verify the intensity equations; a molecular water check reproduces second-order amplitudes within $8.4\times10^{-8}$ atomic units. Comparisons with established tools reproduce a formaldehyde Fermi polyad within 0.163 cm$^{-1}$ and 0.061 km mol$^{-1}$ and water Raman activities within $10^{-7}$ Angstrom$^6$. For 29 matched formaldehyde rotational line pairs, the predicted hot-to-fundamental intensity ratio, using the measured lower-state energy, is consistent with the nuclear-
spin-corrected median: the differences are 3.9% (ESALC-I) and 3.8% (ESALC-C), compared with a 15% uncertainty estimate for individual measured line intensities. Common analytic reference derivatives ensure identical harmonic observables, while internal coordinates reduce and localize intermode anharmonic couplings. Rotation-vibration constants extend the same tensor treatment. An integrated adiabatic discrete-variable representation treats large-amplitude motions, and finite-level partition functions provide anharmonic thermochemistry.
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Atomic Physics · Cross-listed from quant-ph
Demonstration of a mobile ion-trap quantum device
Sara Alfaro, Dipesh Bhanushali, Sankarshan Choudapurkar et al. (+8 more)
Trapped-ion devices are being investigated for transportable applications, including the transfer of exotic charged particles between laboratories and the development of portable
quantum technologies. To date, ion transport has been demonstrated only in
magnetic (Penning) traps, whereas radiofrequency (Paul) traps are the predominant platform in
quantum science. Here, we report the first transport of a few thousand ions confined in a linear Paul trap over distances of several kilometers, with transport durations of 15 and 45 min. These results establish a foundation for mobile trapped-ion
quantum devices capable of operating while in motion and may enable the transport of exotic ions in Paul traps between experimental facilities.
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All authors Sara Alfaro, Dipesh Bhanushali, Sankarshan Choudapurkar, Ashwin Bhartia, Thomas Lafenthaler, Tommaso Faorlin, Yannick Weiser, Lorenz Panzl, Thomas Monz, Rainer Blatt, Giovanni Cerchiari
Fluid Dynamics
Reynolds-number-dependent entrance bias in temperature polarization of lab-scale membrane distillation
Soyoung Kim, Tiezheng Tong and Yinuo Noah Yao
Lab-scale membrane
distillation (MD) modules are commonly used for membrane characterization and developing empirical heat-transfer correlations. Entrance-induced flow structures can introduce geometry-specific effects into measured temperature polarization (TP) and heat transfer. However, the dependence of these effects on module geometry and flow condition remains unclear. We performed three-dimensional computational fluid dynamics (CFD) simulations of direct contact membrane
distillation (DCMD) over inlet Reynolds numbers of $\Re_{\mathrm{in}}=10$-$1000$, focusing on side-chamber length and main-channel height. We discovered that counter-rotating streamwise
vortices formed near the main-channel entrance across all geometries, but their downstream persistence increased with $\Re_{\mathrm{in}}$. At lower $\Re_{\mathrm{in}}$, the
vortices mostly decayed before mid-channel, while at higher $\Re_{\mathrm{in}}$ they persisted farther downstream and produced pronounced spatial variations in TP. Increasing side-chamber length reduced the secondary-flow kinetic energy entering the main channel, and generally strengthened TP, whereas increasing main-channel height reduced the bulk velocity and streamwise kinetic energy, resulting in a thicker thermal boundary layer and stronger TP. For most geometries, the deviation from the straight-channel baseline changed from stronger TP at lower $\Re_{\mathrm{in}}$ to weaker TP at higher $\Re_{\mathrm{in}}$. Entrance effects therefore vary in both magnitude and direction with operating condition and cannot be represented by a constant correction across the Reynolds-number range.
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Computational Physics
LAO+: Focused, Multi-Replica Accelerated Orthogonal Sampling for Robust Binding Free Energy Predictions
Narjes Ansari, Florent Hédin, Jérôme Hénin et al. (+2 more)
We introduce Lambda-ABF-OPES+ ($\text{LAO+}$), a multi-replica framework for absolute binding free energy (ABFE) calculations that accelerates both the alchemical transformation and the slow “orthogonal” motions coupled to it. At the core of $\text{LAO+}$ is a partitioned $\lambda$-dynamics scheme that concentrates sampling on the abrupt rehydration of the binding pocket, the main bottleneck of ligand decoupling, while
Hamiltonian replica exchange relays configurations along the entire alchemical path. This drives a fourfold gain in convergence speed for the rate-limiting leg over our previous $\text{LAO}$ method, which was itself up to ninefold faster than Lambda-ABF, an overall gain of up to $\sim$36-fold. Applied to 28
protein–ligand complexes across five targets, $\text{LAO+}$ achieves a root-mean-square error of 0.83~kcal~mol$^{-1}$ and a correlation of 0.87 with experiment from only 63~ns of sampling per ligand. Moreover, dedicated reservoir replicas accelerate any slow degree of freedom that can be described by a collective variable. We demonstrate this by recovering hidden
protein and ligand conformational states, for example in T4 lysozyme, BRD4 and JNK1. Together, these advances make accurate ABFE calculations practical for drug discovery.
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All authors Narjes Ansari, Florent Hédin, Jérôme Hénin, Jean-Philip Piquemal, Louis Lagardère
Instrumentation and Detectors · Cross-listed from nucl-th
Fast Monte Carlo calculation of multiple scattering in resonant neutron capture
R. M. Djilkibaev
A fast Monte Carlo code has been developed to calculate multiple
neutron scattering in a sample. Good agreement with an independent Monte Carlo calculation using SAMMY is obtained for
neutron capture in $^{197}$Au over the energy range 50–300 eV. For capture following two or more scattering events, a difference is found between the direct Monte Carlo calculation and the analytical approximation in SAMMY. The computational speed allows the scattering correction to be recalculated whenever trial resonance parameters are changed during parameter estimation. The computational core is implemented in C++, while data preparation, calculation control and analysis are performed in Python. Model studies examine how Monte Carlo statistics affect the accuracy with which
neutron and radiative resonance widths are recovered.
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Atmospheric and Oceanic Physics
Improved Precipitation Variability in the Community Atmosphere Model through Implementation of a Neural-Network Deep Convection Scheme
Xavier J. Levine, Griffin Mooers, Jack W. Atkinson et al. (+4 more)
Conventional deep convection schemes remain a primary source of uncertainty in global
climate models, yet replacing them with data-driven alternatives while maintaining physical consistency and numerical stability is an open challenge. We present a hybrid configuration of the Community Atmosphere Model version 6 (CAM6), in which a fully connected deep neural network replaces the Zhang-McFarlane deep convection scheme (ZM), while radiation,
turbulence, and other cloud processes are left unchanged. The network is trained on output from a storm-resolving global model - the global System for Atmospheric Modeling (gSAM) - using a coarse-graining approach to derive subgrid-scale convective fluxes and tendencies. This data-driven parameterization is ported to CAM6 and found to run stably for more than a decade while conserving energy and moisture. It produces a broadly realistic climatology without retuning the remaining parameterizations. Relative to the default Zhang-McFarlane scheme, the neural network parameterization substantially improves some long-standing model deficiencies. In particular, the biases in light precipitation and extreme precipitation are markedly reduced, and the diurnal cycle of tropical land precipitation shifts from a spurious midday peak over many regions to the observed late-afternoon peak. These results support targeted ML-based convection schemes as a viable path toward reducing systematic model errors in next-generation
climate models.
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All authors Xavier J. Levine, Griffin Mooers, Jack W. Atkinson, Marat F. Khairoutdinov, Janni Yuval, Dominic Orchard, Paul A. O'Gorman
Computational Physics · Cross-listed from cond-mat.soft
Effective Graph Neural Representation of Chain Architectures of Block Copolymers Tested by Predicting RPA Instability Limits
Xiyue Zhang, Yutong Wu and Yi-Xin Liu
Advances in
polymer synthesis and computational modeling are expanding the block-copolymer architecture space accessible for phase-behavior design. Machine learning can accelerate this exploration, yet a common representation capable of learning across diverse chain
topologies remains lacking. Here, we present a graph neural network (GNN) representation of acyclic AB multiblock architectures, tested by random-phase approximation (RPA) instability prediction. Each chain is represented as a graph, enabling a common model to learn across diverse
topologies. This representation, which organizes RPA-related information, retains predictive capability when extrapolated to architectures with more blocks and demonstrates its potential for reuse across tasks through transfer to instability-wavenumber prediction. By effectively linking block-copolymer chain architecture to field-theoretic response, this graph representation not only reconstructs stability-limit curves but also provides a practical route for future self-consistent field theory exploration of ordered phase space across complex
topologies.
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Fluid Dynamics
Component-wise outer similarity of turbulent boundary layers with strong adverse-pressure gradient
Yu-Xuan Shi, Mingze Ma and Xi Chen
The adverse-pressure-gradient (APG) effect challenges the classical scaling of turbulent boundary layers (TBLs) over a flat plate, and it remains unclear whether outer-layer similarity holds across a wide range of APG strengths.We assemble a
benchmark comprising the present direct numerical simulation of a suction–blowing-induced separation bubble and published profiles, spanning Clauser parameters $\beta_e=0.04$–$180$ and Reynolds numbers $Re_\theta=530$–$19000$. Across this broad $(\beta_e,Re_\theta)$ parameter range, existing APG normalizations do not simultaneously collapse the two mean-velocity defects and four Reynolds-stress components, leaving open whether outer similarity persists. Instead of defining new scalings, we normalize each quantity by its value at a common location $y_s$. Results are shown using $y_s=0.5\delta$, beyond the outer stress peaks. For each of the six quantities, the normalized profiles exhibit a common outer shape across the conditions, with collapse emerging for $y/\delta\gtrsim0.2$ for the velocity defects and $y/\delta\gtrsim0.4$ for the Reynolds stresses. The collapse-error analysis shows that outer self-similarity is retained over a broad range of $y_s$ within the outer region and is not restricted to $y_s=0.5\delta$. Furthermore, explicit expressions are provided for the normalized outer profiles. These results support component-wise outer similarity under strong APGs and provide compact references for APG
turbulence-model assessment and conditional profile reconstruction.
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Classical Physics · Cross-listed from eess.AS
Continued fractions and passive ladder networks for acoustic impedances: the baffled piston and the horn
Ronald M. Aarts
Lumped-element networks give transparent, passive models of acoustic impedances whose low- and high-frequency limits can be read from the
circuit, but a systematic, arbitrarily accurate construction for non-rational impedances is lacking. Continued fractions, one- and two-point Padé approximants and their identity with ladder networks and Cauer synthesis are introduced in tutorial form and applied to two examples: the radiation impedance of a baffled circular piston and the throat impedance of a horn with a piston mouth. The even contraction of the piston's continued fraction has positive coefficients, certified by interval arithmetic for the first 100 pairs, and yields a ladder of positive resistances, masses and compliances; with 14 elements the error is 4e-4 up to ka = 5. Beranek's four-element network is, to about 2%, the order-two two-point Padé approximant. A horn modelled as a cascade of waveguide sections is a continued fraction whose tail is the mouth impedance; the infinite exponential horn is a periodic continued fraction, an exact high-pass ladder. The piston networks are passive at every certified order (up to 202 elements) and are extended without changing existing elements; for a finite horn the error of the mouth network passes one to one to the throat impedance.
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Optics
Cavity-tunable Pseudospin-Hall Topology and Edge Transport
Minghui Niu, Yan Meng, Chengle Fan et al. (+5 more)
Topological edge states are a hallmark of topological phases, with their existence tied to bulk band
topology through bulk-edge correspondence. In photonic pseudospin-Hall systems, these states exhibit pseudospin-momentum locking, with
lattice interactions and interface geometry determining each pseudospin's propagation direction. Reversing the pseudospin-dependent propagation direction without altering the
lattice configuration or excitation handedness remains a fundamental challenge in controlling topological edge transport. Here, we theoretically and experimentally demonstrate cavity-tunable topological edge transport in a microwave metasurface embedded within a metallic cavity. Varying the cavity height reshapes resonator interactions, driving band inversion and topological phase transition while preserving the
lattice geometry. For a fixed domain-wall configuration, this transition reverses the propagation direction associated with each pseudospin while preserving pseudospin-momentum locking. Excitations with the same handedness are observed to launch edge waves propagating in opposite directions at their respective edge-band frequencies determined by the cavity height. These results establish cavity electrodynamics as an external means of controlling the bulk
topology and reconfiguring the directional response of topological interfaces, creating new opportunities for topological wave routing in fixed photonic
lattice structures.
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All authors Minghui Niu, Yan Meng, Chengle Fan, Xiaoyuan Jiao, Jidong Song, Perry Ping Shum, Zhen Gao, Mengyao Li
Optics · Cross-listed from cond-mat.mes-hall
Making Weak Interlayer Excitons Absorb: Manipulating the Effective Oscillator Strength via Purcell Engineering of Critical Coupling
Saroj Poudyal, Anabel Atash Kahlon, Michael Klein et al. (+7 more)
Interlayer
excitons (IXs) in transition metal dichalcogenide bilayers possess unique dipolar properties, providing a path for exploring correlated many-body phases, electrically tunable dipole-dipole interactions, and long-range
exciton transport. However, the large electron-hole separation underlying their dipolar character also results in a significantly reduced oscillator strength, limiting their direct optical interaction with light, and thus the direct probing of their dynamics and many-body interactions. Here, we show that by using Purcell engineering of critical coupling, a weak interlayer transition can absorb as strongly as the dominant intralayer transition, despite its much smaller intrinsic oscillator strength. Using this approach, in an open cavity architecture we demonstrate an order of magnitude IX absorption modulation in bilayer and trilayer MoS2, with doubling of the IX to A-
exciton interaction strength weight from ~23% to ~53%. Furthermore, we demonstrate that in a tailored closed cavity architecture, the IX enhancement can reach beyond an order of magnitude, from ~5% to ~83% excitonic absorption, enabling IX absorption similar to intralayer
excitons. An analytical description of the interaction is obtained via a closed-form transmission-line model which separates the excitonic and photonic contributions to the optical response, revealing how cavity architecture can be designed towards critical coupling. Our findings establish Purcell engineering of critical coupling as a general route to controlling and enhancing weak excitonic transitions.
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All authors Saroj Poudyal, Anabel Atash Kahlon, Michael Klein, Matan Meshulam, Yonatan Gershuni, Thomas Poirier, James H. Edgar, Mukesh Kumar, Seth Ariel Tongay, Itai Epstein
Fluid Dynamics
Extreme-Scale Super-Resolution of Homogeneous Turbulence from a Single Realization
Arth Sojitra, Muhammad Abid and Omer San
Homogeneous turbulent flows exhibit recurring multiscale structures across spatially separated regions, suggesting that a single flow realization may contain sufficient information to learn representations of unresolved scales. We investigate this hypothesis through an extreme super-resolution framework in which a wide-activation deep super-resolution (WDSR) network is trained exclusively on overlapping patches extracted from a single high-resolution turbulent realization. Previously unseen flow fields are reconstructed through patchwise prediction followed by Hann-window-weighted overlap-add assembly. The framework is evaluated for two-dimensional homogeneous isotropic
turbulence at super-resolution factors of x32 and x64, representing severe spatial under-resolution. Despite the limited training data, the proposed approach reconstructs coherent vortical structures and recovers fine-scale features more accurately than conventional interpolation. Spectral and statistical analyses further demonstrate improved recovery of high-wavenumber energy content and multiscale flow characteristics. To assess the effectiveness of exploiting internal spatial information, we compare the proposed framework against WDSR models trained on 1, 25, 50, and 100 complete high-resolution snapshots without patch extraction. This comparison distinguishes the benefits of localized learning from those associated with increasing the number of training realizations. The results demonstrate that exploiting spatial redundancy within a single turbulent realization enables accurate reconstruction of previously unseen flow fields, even under extreme spatial under-resolution. These findings establish single-realization patch-based learning as a promising data-efficient approach for turbulent super-resolution when high-resolution training data are scarce.
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Medical Physics
A single radiation hard pixel detector for proton dosimetry, imaging, energy resolution and beam monitoring
Nico Frederic Brosda, Stephane Higueret, Nicolas Arbor et al. (+7 more)
Proton therapy enables highly conformal tumour irradiation by exploiting the Bragg peak. Clinical precision relies on detector systems that provide linearity, spatial resolution, radiation hardness, and, for ultra-high-dose-rate (FLASH) therapy, high dynamic range with sufficient temporal response. No compact all-in-one solution currently fulfils all these requirements. Here, we present pixelated gallium nitride (GaN) arrays as a multifunctional platform. These detectors exhibit high linearity (
proton currents from 70 to 1700 pA cm-2) and signal uniformity below 2% across 128 pixels. To probe GaN radiation hardness, we applied cumulative doses up to 6.7 MGy at energies from 25 MeV down to the Bragg-peak regime. Locally deposited dose dictates long-term signal loss, yet devices preserve linearity and spatial response. We demonstrate 0.25 mm effective spatial resolution, validated against radiochromic film.
Proton radiography resolves fine tissue structures, with the dose extrapolated to 7 mGy per 1 ms frame in a prospective single-shot configuration. Energy-dependent responses match GATE/Geant4 simulations, and wedge measurements enable Bragg-peak tracking with an energy resolution below 10 keV in an optimised geometry. Real-time ms-scale beam monitoring enables live dose verification.These results establish GaN pixel detectors as a scalable and radiation-hard platform, enabling dosimetry, beam monitoring and energy verification in one device.
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All authors Nico Frederic Brosda, Stephane Higueret, Nicolas Arbor, Matilde Siviero, Maxime Hugues, Eric Frayssinet, Luisa Parschat, Christian Baumer, Andreas Dirk Wieck, Jean Yves Duboz
Biological Physics
Memory-resolved prediction of ligand residence times on the minutes timescale
Hossein Batebi, Lucas Tepper and Roland R. Netz
AI-enabled computational drug discovery is advancing rapidly in predicting molecular structures, binding poses and affinities, but ligand dissociation kinetics remain harder to access. Bound-state residence time, important for biological response and kinetic selectivity, is not fixed by
equilibrium affinity but depends on the dissociation free-energy landscape and dissipative friction effects. Here, we show that restrained umbrella-sampling trajectories can be used to calculate residence times on the minutes timescale. Time-resolved coordinate fluctuations yield friction profiles that incorporate non-Markovian effects on dissociation kinetics. Combining them with the free-energy profile, we predict a residence time of $\tau_{\rm res}$ = 275 s for the adenosine A$_{2A}$ receptor with ZM241385 (comparable to the experimental value of 125 s) and reproduce the experimental ranking of wild type and two receptor mutants. For HSP90 with compound 18 and RNase S with the S15 peptide, we predict $\tau_{\rm res}$ = 2,169 s and 2,259 s (experimental values are 833 s and 2,439 s). Neglecting
memory effects on residence kinetics overestimates $\tau_{\rm res}$ by factors of 2.6 to 29.
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Optics
Photoacoustic-guided reflection-mode wavefront shaping through dynamic biological tissue
Xuan Liu, Sacha Noimark, Wenfeng Xia et al. (+2 more)
Strong optical scattering limits the depth at which light can be focused and used for imaging in biological tissue. Photoacoustic (PA)-guided wavefront shaping enables non-invasive light focusing in scattering media, but most existing implementations require optical and acoustic access from opposite sides of the sample and a rigidly aligned free-space optical path, which have confined these demonstrations to thin or static samples. Here, we combine a real-valued intensity transmission
matrix (RVITM)
algorithm with a photoacoustic guidestar (PA-RVITM) in a reflection-mode configuration. Modulated light is delivered through a flexible multimode fiber passing through the central aperture of a focused ultrasound transducer, enabling optical illumination and acoustic detection from the same side of the sample without a free-space combiner. Fiber integration preserved the wavefront shaping performance, and the reflection-mode PA-RVITM system achieved sub-second wavefront optimization with a ~14-fold PA signal enhancement through a diffuser. In ex vivo chicken breast tissue, the enhancement decreased with tissue thickness, reaching ~3.5 through a 2-mm chicken breast layer, with a speckle decorrelation time of ~450 ms. By performing an independent RVITM optimization at each scan position, our system enabled photoacoustic microscopy of a black nylon wire through the same layer, reducing the imaged line width from ~141 {\mu}m to ~102 {\mu}m, close to the nominal diameter of ~100 {\mu}m. This work advances PA-guided wavefront shaping toward a compact, same-side implementation for future biomedical therapeutic and imaging applications.
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All authors Xuan Liu, Sacha Noimark, Wenfeng Xia, Sebastien Ourselin, Tianrui Zhao
Accelerator Physics · Cross-listed from nucl-ex
Physics with Radioactive Ion Beams at the Nuclear Science Laboratory
W.S. Porter, D.W. Bardayan, M. Brodeur et al. (+13 more)
The University of Notre Dame is home to a rich history of nuclear science efforts, including some of the earliest developments in the production and creation of radioactive ion beams (RIBs). The resulting TwinSol facility stands as the longest continuously-operating RIB facility in the United States, and has enabled a wide range of experimental efforts in nuclear structure, astrophysics and fundamental
symmetries through in-flight RIBs one to two nucleons from stability. A recent upgrade to TwinSol via a third solenoid constituted the founding of the TriSol facility, which provides cleaner, better-focused RIBs to downstream experiments. In this paper, we present a summary of RIB science at the Nuclear Science Laboratory (NSL) with both TwinSol and TriSol and discuss recent upgrades and future experimental plans at the facilities.
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All authors W.S. Porter, D.W. Bardayan, M. Brodeur, C. Dembski, P.D. O'Malley, F. Rivero, W.W. von Seeger, C. Boomershine, O. Bruce, S.R. Carmichael, S. Coil, A.M. Houff, J.J. Kolata, D. Schroeder, A.A. Valverde, R. Zite
Fluid Dynamics · Cross-listed from cond-mat.mtrl-sci
High-Frequency Mass Transfer Enabling Over-Limiting Currents in Porous Electrodes
Md Abdul Hamid and Kyle C. Smith
Classical film theory predicts a finite
diffusion-limited current at porous electrodes. However, over-limiting currents (OLCs), which exceed this limit, are often observed and have been attributed to surface charge, confinement, or electrokinetic effects. Here, we use a frequency-domain framework to identify a different mechanism governed by the time scale of concentration variation. For perfectly reactive interfaces, the spectral Sherwood number, a frequency-dependent dimensionless measure of interfacial mass transfer relative to molecular
diffusion, grows as $\Shnd\sim\omega^{1/2}$ at high frequency, while its phase approaches $\pi/4$. This response corresponds to the semi-infinite Warburg limit of the electrochemical impedance. A scaling analysis shows that the exponent and prefactor are determined by
diffusion within a thin layer adjacent to the interface and are therefore independent of the global pore geometry. Numerical results for parallel plates, circular tubes, and twelve porous microstructures confirm this scaling. Geometry, flow strength, and flow direction affect the low-frequency response and crossover frequency, but not the asymptotic scaling in the high-frequency limit. This temporal route to OLCs requires neither surface charge nor confinement and could inform the design of systems for pulsed electrodeposition, mineral recovery and renewable-energy storage.
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Computational Physics
Learning to reconstruct Germano Differential Filtered Fields with Convolutional Neural Networks for Large Eddy Simulation of Plasma Turbulence
Jony Castagna and Josh Williams
We present a novel method which combines the invertibility of the differential filter of Germano, with convolutional networks to accelerate
plasma turbulence simulations. Rather than learning the mapping from coarse-grid LES fields to fine-grid DNS, the proposed method learns the mapping from coarse LES fields to the differential-filtered DNS fields. We then use the inverse of Germano's filter to reconstruct the fine-scale details and hence calculate exactly the nonlinear terms in the governing equations and subgrid-scale terms in the LES equations. The method is tested on the 2D Hasegawa-Wakatani (HW) and modified Hasegawa-Wakatani (mHW)
plasma turbulence models at $256^2$ and $512^2$ DNS resolutions using 2, 4 and 8 times smaller LES grids in each direction. We compare the model with DNS results on energy, enstrophy, spectra, probability distributions, poloidal and radial fluxes and computational cost. Validation extends to 1000 simulation time units for HW and 100 for mHW, whose faster dynamics lead toward laminarization. For the $256^2$ cases, the finer LES meshes preserve several integral and spectral features, whereas the coarsest mesh yields unphysical behavior. In contrast, for the $512^2$ cases, even the coarsest LES mesh preserves the turbulent character of the flow and maintains acceptable statistics for both the HW and mHW models. Moreover, we show how our methodology is superior to traditional algebraic numerical LES models, which traditionally fail to capture important design features. Finally,
benchmarks show an MPI task-time reductions of 4.82–49.45, with a maximum wall-clock speedup of $1.55\times$ when compared to full CPU socket.
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Optics
From Single-Particle Thermal Asymmetry to Collective Control: Janus Plasmonic Colloids for Photothermal Applications
Cédric Rousseau, Javier González-Colsa, Victor Joris et al. (+3 more)
Janus nanoheaters provide a route to break the spatial
symmetry of thermoplasmonic heating and generate directionally biased thermal gradients at the nanoscale. However, in realistic photothermal scenarios, nanoheaters rarely act as isolated objects, but rather operate within colloidal assemblies where collective thermal and electromagnetic effects reshape the local temperature landscape. Here, we investigate how the intrinsic thermal asymmetry of a single Janus plasmonic nanoheater is transformed when moving from isolated particles to planar random arrays under continuous-wave illumination. Using coupled electromagnetic and steady-state heat-transfer simulations, we first quantify the finite spatial range over which the single-particle Janus signature remains detectable. We show that neighboring nanoheaters introduce two competing effects: a nearly symmetric collective thermal background that screens and homogenizes the Janus factor, and short-range neighbor-induced asymmetries that partially compensate this screening when interparticle distances become comparable to the spatial extent of the single-particle thermal anisotropy. We derive a closed-form analytical model for the array-averaged Janus factor as a function of nanoparticle number and surface density. The model predicts the screening-dominated regime from single-particle quantities and identifies deviations associated with near-field neighbor-induced contributions at higher densities. These results demonstrate a central trade-off for biomedical photothermal applications in continuous-wave operation: collective heating is required to reach relevant temperature increments, but it progressively erases the directional Janus character by thermal homogenization. Our framework provides a practical route to predict and rationally design the spatial temperature distribution in plasmonic assemblies of Janus particles.
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All authors Cédric Rousseau, Javier González-Colsa, Victor Joris, Pablo Albella, Bjorn Maes, Gilles Rosolen
Atomic Physics
Fine-structure Raman interferometry with metastable barium for magnetically resilient inertial sensing
Masaki Nagamori, Hiromi Hatano, Toshiyuki Hosoya et al. (+3 more)
Atom-interferometric
quantum inertial sensors are promising candidates for inertial navigation systems owing to their high sensitivity and intrinsically low drift. However, their application to next-generation inertial navigation, targeting a drift below 100 m/month, requires exceptionally stringent inertial-sensor bias stability. In conventional Raman atom interferometers based on ground-state hyperfine transitions, suppressing inertial-sensor biases arising from quadratic Zeeman shifts requires highly optimized
magnetic shielding. In this work, we propose a Raman atom interferometer based on fine-structure transitions between metastable states of barium, which exhibit a quadratic Zeeman sensitivity approximately three orders of magnitude lower than that of conventional alkali-atom Raman transitions. We show that the proposed scheme increases the allowable spatial gradient of the
magnetic-field magnitude by a factor of several tens, thereby relaxing the
magnetic-field-control requirements from highly optimized shielding and compensation systems to standard
magnetic-field-control techniques. Furthermore, we experimentally demonstrate Mach–Zehnder interference between metastable fine-structure states of barium, validating a key building block of the proposed inertial-sensing scheme.
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All authors Masaki Nagamori, Hiromi Hatano, Toshiyuki Hosoya, Yuki Miyazawa, Tomoya Sato, Mikio Kozuma
Atmospheric and Oceanic Physics · Cross-listed from astro-ph.IM
R&D activity in INAF on light instrumentation for continuous optical turbulence monitoring
Camilo Weinberger Elena Masciadri, Luca Carbonaro, Marlene de Sepibus et al. (+4 more)
Measurements of optical
turbulence are essential in both ground-based astronomy and free-space optical communication systems contexts for multiple reasons including supporting and optimizing Adaptive Optics. Similarly, forecasting these parameters is highly valuable for planning observational campaigns; however, it requires at least two years of continuous data to generate a reliable training
dataset. The most commonly used instruments to monitor continuously the optical
turbulence include DIMM, MASS, SLODAR, RINGSS sensors. The Arcetri team is leading two operational forecast systems for two different Observatories: ALTA above LBT, and FATE above VLT. Both systems are in continuous
evolution and obviously forecast performances depend also on available measurements. Our long-term goal is to develop our own instruments to obtain continuous measurements directly from local observations. In this work, we present an automated system designed for continuous seeing measurements using multiple sensors. This portable station integrates a Cyclope, a RINGSS unit, a scintillometer which operate together to provide comprehensive night-time atmospheric information. We will compare the performance of low-cost sensors, such as the Cyclope and the scintillometer, with that of the RINGSS
turbulence profiler, which has been fully installed and programmed by our team in collaboration of LBT team. A dedicated insturment for night and day-time measurements is planned for near future. This system incorporates a fully automatic on-site system that monitors operational status, delivers real-time information on sensor conditions and measurements, and manages synchronization with the data storage unit. The system's real-time acquisition capability enables continuous
turbulence analysis, supports R&D activities, facilitates local data generation, and allows on-site testing of forecasting methodologies.
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All authors Camilo Weinberger Elena Masciadri, Luca Carbonaro, Marlene de Sepibus, Fernando Pedichini, Ciro Del Vecchio, Christian Veillet, Sam Ragland
Fluid Dynamics · Cross-listed from math.NA
eMOOD: Entropy-Based Multidimensional Optimal Order Detection for High-Order Shock-Capturing Finite-Volume Schemes
Michał Umiński, Panagiotis Tsoutsanis, Ahmed A Sheikh Al-Shabab et al. (+1 more)
We present eMOOD, an
entropy-guided
evolution of the Multidimensional Optimal Order Detection (MOOD) framework for high-order finite-volume methods on unstructured meshes. A novel troubled-
cell indicator based on numerical
entropy production replaces the classical relaxed discrete maximum principle. Using
entropy generation as a physically motivated measure of non-smoothness, the detector targets shocks, contact discontinuities and under-resolved flow features with a compact stencil. Compared with conventional MOOD detection, eMOOD reduces flagged
cells by up to 75%, improving efficiency and reducing
memory-access overhead. The detector is used within both the classical MOOD cascade of progressively reduced-order schemes and a novel MOOD-CWENO hybrid, which retains inexpensive linear reconstruction in smooth regions and activates nonlinear high-order reconstruction only where needed. Implemented in the open-source parallel solver UCNS3D, the methodology is assessed on the Shu-Osher shock-
entropy-wave interaction, double Mach reflection, supersonic forward-facing step, shock-helium-bubble interaction and triple material point problems. These
benchmarks encompass strong shock interactions, shock-induced instabilities, multi-material interfaces and
vortex-dominated flows, testing robustness, shock capturing and accuracy on unstructured meshes. Results show that eMOOD preserves the accuracy and robustness of reference CWENO and MOOD formulations while achieving speed-ups of up to 20% without loss of solution quality. Its compact detection stencil, reduced
memory footprint and improved localisation offer a more scalable and efficient framework for massively parallel high-order compressible-flow simulations. UK Ministry of Defence (copyright) Crown owned copyright 2026 AWE.
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All authors Michał Umiński, Panagiotis Tsoutsanis, Ahmed A Sheikh Al-Shabab, Alan S. Dawes
Instrumentation and Detectors
A low-cost compact muon detector for millikelvin operation
Tengiz Ibrayev, Danish Khan, Alex Herscovics et al. (+5 more)
Ionizing radiation produces correlated errors in superconducting
qubits, posing some challenges to
quantum error correction. In addition, it causes background events in other superconducting cryogenic devices, such as kinetic inductance detectors and superconducting nanowire single-
photon detectors.
Cosmic muons are a component of this background that can only be partly shielded against at ground level, but can be tagged by an independent detector inside the cryostat, so that the affected data can be vetoed, or the
muon tags incorporated into error correction. We present a low-cost, compact
muon detector consisting of two plastic scintillator modules, each read out by a silicon photomultiplier (SiPM), operated in coincidence. We characterize the SiPMs from room temperature down to 10 mK, including the breakdown and upper-limit voltages that define the operating bias range. Operated as a
muon counter, the detector measures a coincidence rate that, as expected, is independent of temperature within uncertainties and agrees with analytical and Monte Carlo predictions. Below approximately 8 K, each
muon event produces two pulses, one narrow and one broad, an effect that, to our knowledge, has not been reported before. Coincidences with an independent
muon detector outside the cryostat confirm that
muons are still counted reliably in this regime. By studying the appearance of double pulses as a function of temperature and
magnetic field up to 4.5 T, we find a behavior consistent with the phase diagram of a type-II
superconductor. This links the double pulses to a superconducting material in the SiPM, likely an adhesion layer or
diffusion barrier introduced during manufacturing. The mechanism by which the superconducting state produces the second pulse is not yet understood.
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All authors Tengiz Ibrayev, Danish Khan, Alex Herscovics, Komal Kataruka, Matilda Lawton, Sandhya Sharma, Steven Waddy, Laura Manenti
Optics
Near-field contributions to cavity-mediated radiative heat transfer
Antonio Mastropasqua, Martin Eckstein, Daniele Fausti et al. (+1 more)
Embedding materials in optical cavities has emerged as a powerful strategy for controlling their physical properties. In this context, increasing
attention has been devoted to the thermal Purcell effect, which describes how the radiative heat transfer between a material and its photonic environ- ment can be modified by the electromagnetic boundary conditions imposed by the cavity. Here, we investigate near-field effects in cavity-mediated radiative heat transfer in planar cavities composed of realistic, dissipative gold mirrors, extending previous work that considered ideal mirrors. We iden- tify the conditions under which near-field effects lead to a substantial enhancement of heat transfer between the material and a photonic thermal bath relative to free space, owing to the strong modi- fication of the photonic local density of states by evanescent modes within the cavity. In particular, we find that radiative heat flow can be enhanced by several orders of magnitude in cavities ranging from nanometer to micrometer scales, depending on the absorber frequency and dipole orientation. These findings suggest that near-field effects may be relevant to polariton chemistry experiments and other systems operating within this cavity length-scale regime. Our results add to the idea that cavities can modify material properties not only by engineering
vacuum fluctuations in the strong light-matter coupling regime, but also by controlling radiative dissipation and heat transfer.
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All authors Antonio Mastropasqua, Martin Eckstein, Daniele Fausti, Francesca Fassioli
Optics
Polaritonic self-hybridized critical coupling by Brillouin zone folding induced quasi-bound states in the continuum in bulk WS2 metasurfaces
Kuidong Wang, Xiongwei Guo, Fu Liu et al. (+2 more)
Maximizing the absorption of
exciton-polaritons in transition-metal dichalcogenides (TMDCs) under critical coupling conditions is crucial for developing high-efficiency polariton-based photodetectors, solar
cells, and perfect absorbers. Here, we propose a polaritonic critical self-hybridized coupling between Brillouin zone folding driven quasi-bound states in the continuum (BZF-QBIC) mode and A
excitons in a bulk WS2 metasurface. This polaritonic critical coupling shows robust behavior with respect to the asymmetric parameters of the involved BZF-QBIC mode, in contrast to the asymmetry-sensitive conventional QBIC-based critical coupling. By changing the height of WS2 metasurfaces, we observe a typical anti-crossing behavior with a Rabi splitting of 246.5 meV. Moreover, the maximum absorption value of 0.5 for
exciton-polaritons is achieved at the polaritonic critical coupling condition. The large population of
excitons provided by bulk WS2 is essential for achieving polaritonic critical coupling and can further enhance polaritonic absorption. This work enables the realization of robust, high-absorption self-hybridized polaritonic critical coupling in TMDCs, and further expedite their applications in high-absorption low-dimensional polaritonic devices.
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All authors Kuidong Wang, Xiongwei Guo, Fu Liu, Jinhai Si, Xun Hou