Space Physics
Where Does Tracing of Cosmic Ray in Real Atmosphere Terminate?
Du-Xin Zheng, Long Chen and Ran Huo
In backtracing simulations, which are widely employed to determine
cosmic-ray particle trajectories in the geomagnetic field, the atmosphere is typically approximated as an artificial sharp boundary at some low altitude where the traced trajectory terminates. In this paper, we extend beyond this simplified assumption and investigate two realistic physical processes that terminate
cosmic-ray particle propagation in the atmosphere: Bethe-Bloch energy loss mechanisms and hard scattering interactions with atmospheric atoms using total cross sections based on the Glauber-Gribov formalism. The former mechanism dominates at low
rigidities (for
protons below $\sim0.57$~GV), while the latter becomes dominant at higher
rigidities. Consequently, we introduce two dimensionless variables up to detailed numerical criteria: the relative
rigidity shift due to Bethe-Bloch effects ($\Delta\mathfrak{R}/\mathfrak{R}$), and the expected number of hard scattering events ($\langle N\rangle$). Using the corrected US Standard Atmosphere 1976 model, we demonstrate that the altitude dependence can be factorized as approximately $\exp(-0.14h/\textrm{km})$. Additionally, the effect of the local
curvature radius of the trajectory near perigee can be similarly factorized. Our calculations indicate that the simplified sharp-boundary altitude should be at least $50$ km with $\Delta\mathfrak{R}/\mathfrak{R}+\langle N\rangle\lesssim1$ for
protons, increasing by more than $15$ km for heavy
nuclei such as iron.
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Fluid Dynamics
Tracking stall cell dynamics at high Reynolds numbers
Badoui Hanna, Bérengère Podvin and Caroline Braud
The spanwise organization of the flow over a thick airfoil is investigated using surface pressure measurements for a range of angles of attack around maximum lift and high Reynolds numbers (1 Million). Locally strong pressure fluctuations, which are not detected in the global lift coefficient, are shown to be associated with the presence of a stall
cell. The stall
cell width is of the order of the chord length and increases linearly with the angle of attack, with a weak dependence on the Reynolds number. Its dynamics at Reynolds numbers larger than 1 Million is dominated by a coherent motion in the spanwise direction with a characteristic velocity of order tenth of the freestream velocity. The motion can be decomposed into a large-scale, low-frequency sweep with a Strouhal number equal to 0.001 combined with faster, smaller-scale oscillations. The coherence of the stall
cell makes it possible to track global dynamics from local measurements.
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Space Physics · Cross-listed from astro-ph.EP
An Open Database of Lunar Regolith and Simulants Properties
Léonie Gasteiner, Naomi Murdoch and Olfa D'Angelo
Lunar regolith, the layer of unconsolidated material covering the Moon's surface, is central to the science and technology developed for the Moon, notably related to in-situ science investigations, resource utilization, surface infrastructure, and mobility systems. However, data on lunar soil properties remain fragmented across decades of mission reports, often in formats that are difficult to access or interpret. We present a newly compiled database of lunar regolith physical and geotechnical properties, including data collected by direct in-situ measurements from crewed missions, estimates inferred from surface interactions on the Moon and using remote sensing, as well as laboratory analyses of samples returned to Earth. The data collected include, among others, the angle of internal friction and cohesion (both Mohr-Coulomb model parameters), bulk density, and static bearing capacity, extracted from Luna and Apollo-era historical mission documentation all the way to contemporary Lunar programs. The
dataset specifies the type and location of the tests from which each value was obtained. Our database also includes parameters for lunar regolith simulants, providing a direct link between mission data and laboratory studies. In addition to centralizing this information, we developed a user interface that facilitates data
retrieval, filtering, and visualization. This interface enables users to generate customized plots for comparative analysis. Developed in an open-science perspective, it is designed to evolve in response to the community's needs. The database and its associated tools significantly enhance the accessibility and usability of lunar regolith and simulants data for scientific and engineering research.
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Atomic and Molecular Clusters
Features of clustering in a supersonic argon jet when using a conical nozzle
Yu. S. Doronin, A. A. Tkachenko, V. L. Vakula et al. (+1 more)
The article presents an original spectroscopic method for determining the initial stage of the clustering process in supersonic jets. The technique has been tested on a supersonic argon jet excited by electrons at a distance of 30 millimetres from the nozzle outlet, where the clustering process is practically complete, and the influence of secondary processes on the intensity of the observed emissions is significantly suppressed. It is proposed to use the continuum emitted by neutral excited clusters with a wavelength of 127 nm as an indicator of cluster formation in a supersonic argon jet under various flow conditions. Analysis of the temperature dependence of the intensity of this continuum recorded at multiple argon pressures at the nozzle inlet allowed us to establish that the parameters of supersonic jet flow corresponding to the onset of crystallisation are related by the empirical expression. The calculated value of the constant for argon in the studied range of pressures and temperatures was 0.011.
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All authors Yu. S. Doronin, A. A. Tkachenko, V. L. Vakula, G. V. Kamarchuk
Computational Physics · Cross-listed from cond-mat.soft
Vacancy defects in square-triangle tilings and their implications for quasicrystals formed by square-shoulder particles
Alptuğ Ulugöl, Giovanni Del Monte, Eline K. Kempkes et al. (+2 more)
Almost all observed square-triangle quasicrystals in soft-matter systems contain a large number of point-like defects, yet the role these defects play in stabilizing the quasicrystal phase remains poorly understood. In this work, we investigate the thermodynamic role of such defects in the widely observed 12-fold symmetric square-triangle quasicrystal. We develop a new Monte Carlo simulation to compute the configurational
entropy of square-triangle tilings augmented to contain two types of irregular hexagons as defect tiles. We find that the introduction of defects leads to a notable
entropy gain, with each defect contributing considerably more than a conventional vacancy in a periodic
crystal. Intriguingly, the
entropy gain is not simply due to individual defect types but isamplified by their combinatorial mixing. We then apply our findings to a microscopic model of core-corona particles interacting via a square-shoulder potential. By combining the configurational
entropy with vibrational free-energy calculations, we predict the
equilibrium defect concentration and confirm that the quasicrystalline phase contains a higher concentration of point-defects than a typical periodic
crystal. These results provide a new understanding of the prominence of observed defects in soft-matter quasicrystals.
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All authors Alptuğ Ulugöl, Giovanni Del Monte, Eline K. Kempkes, Frank Smallenburg, Laura Filion
Instrumentation and Detectors
ATLAS MDT TDC Simulations for LHC Run3 and HL-LHC
Jiajin Ge, Bing Li, Markus Fras et al. (+3 more)
The Large
Hadron Collider (LHC) started the Run 3 operation in 2022, and the peak instantaneous luminosity in Run 3 may reach 3 x 10^34 cm-2s-1. The ATLAS Monitored Drift Tube (MDT) chambers are the main component of the precision tracking system in the ATLAS
muon spectrometer. It is important to understand any potential issues with the MDT Front-End (FE) readout electronics for an expected level-1 (L1) trigger rate of 100 kHz and a complex deadtime of over 5% for Run 3 operations. We use raw data collected in 2022 to emulate the expected hit rates in MDT chambers and perform a realistic simulation on the ATLAS
Muon TDC (Time-to-Digital Converter) (AMT) chip with the current configuration. We study the AMT chip performances by analyzing the trigger/L1/readout buffer occupancies and hit loss fractions under different luminosities with L1 rate of 100 kHz by using the Modelsim software. The hit loss fraction of the hottest MDT chamber (BIL3C05) is lower than 5% due to FE readout, even at a luminosity of 5.01 x 10^34 cm-2s-1 with a deadtime of 5% and a L1 rate of 100 kHz, indicating that AMT can operate under Run 3 conditions without problems. The MDT trigger and readout electronics will be replaced for triggerless readout during High-Luminosity LHC (HL-LHC) runs. We also simulate the AMT behavior in the triggerless mode up to 7.44 x 10^34 cm-2s-1 and propose possible AMT configurations in case some FE electronics could not be replaced during the long shutdown 3 (LS3).
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All authors Jiajin Ge, Bing Li, Markus Fras, Junjie Zhu, Bing Zhou, Tiesheng Dai
Classical Physics · Cross-listed from cond-mat.stat-mech
The Mpemba effect in the Descartes protocol: A time-delayed Newton's law of cooling approach
Andrés Santos
We investigate the direct and inverse Mpemba effects within the framework of the time-delayed Newton's law of cooling by introducing and analyzing the Descartes protocol, a three-reservoir thermal scheme in which each sample undergoes a single-step quench at different times. This protocol enables a transparent separation of the roles of the delay time $\tau$, the waiting time $t_{\text{w}}$, and the normalized warm temperature $\omega$, thus providing a flexible setting to characterize anomalous thermal relaxation. For instantaneous quenches, exact conditions for the existence of the Mpemba effect are obtained as bounds on $\omega$ for given $\tau$ and $t_{\text{w}}$. Within those bounds, the effect becomes maximal at a specific value $\omega=\widetilde{\omega}(t_{\text{w}})$, and its magnitude is quantified by the extremal value of the temperature-difference function at this optimum. Accurate and compact approximations for both $\widetilde{\omega}(t_{\text{w}})$ and the maximal magnitude $\text{Mp}(t_{\text{w}})$ are derived, showing in particular that the absolute maximum at fixed $\tau$ is reached for $t_{\text{w}}=\tau$. A comparison with a previously studied two-reservoir protocol reveals that, despite its additional control parameter, the Descartes protocol yields a smaller maximal magnitude of the effect. The analysis is extended to finite-rate quenches, where strict equality of bath conditions prevents a genuine Mpemba effect, although an approximate one survives when the bath time scale is sufficiently short. The developed framework offers a unified and analytically tractable approach that can be readily applied to other multi-step thermal protocols.
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Computational Physics · Cross-listed from cond-mat.soft
Ultrastable 2D glasses and packings explained by local centrosymmetry
A. Zaccone
Using the most recent numerical data by Bolton-Lum et al. [Phys. Rev. Lett. 136, 058201 (2026)], we demonstrate that ideal ultrastable glasses in the athermal limit (or ultrastable ideal 2D disk packings) possess a remarkably high degree of local centrosymmetry. In particular, we find that the inversion-
symmetry order parameter for local force transmission introduced in Milkus and Zaccone, [Phys. Rev. 93, 094204 (2016)], is as high as $F_{IS}= 0.84522$, to be compared with $F_{IS}=1$ for perfect centrosymmetric
crystals free of defects, and with $F_{IS} \sim 0.3-0.5$ for standard random packings. This observation provides a clear, natural explanation for the ultra-high shear modulus of ideal packings and ideal glasses, because the high centrosymmetry prevents non-affine relaxations which decrease the shear modulus. The same mechanism explains the absence of
boson peak-like soft vibrational modes. These results also confirm what was found previous work, i.e. that the bond-orientational order parameter is a very poor correlator for the vibrational and mechanical
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Decision-oriented benchmarking to transform AI weather forecast access: Application to the Indian monsoon
Rajat Masiwal, Colin Aitken, Adam Marchakitus et al. (+9 more)
Artificial intelligence weather prediction (AIWP) models now often outperform traditional physics-based models on common metrics while requiring orders-of-magnitude less computing resources and time. Open-access AIWP models thus hold promise as transformational tools for helping low- and middle-income populations make decisions in the face of high-impact weather shocks. Yet, current approaches to evaluating AIWP models focus mainly on aggregated meteorological metrics without considering local stakeholders' needs in decision-oriented, operational frameworks. Here, we introduce such a framework that connects meteorology, AI, and social sciences. As an example, we apply it to the 150-year-old problem of Indian monsoon
forecasting, focusing on benefits to rain-fed agriculture, which is highly susceptible to
climate change. AIWP models skillfully predict an agriculturally relevant onset index at regional scales weeks in advance when evaluated out-of-sample using deterministic and probabilistic metrics. This framework informed a government-led effort in 2025 to send 38 million Indian farmers AI-based monsoon onset forecasts, which captured an unusual weeks-long pause in monsoon progression. This decision-oriented benchmarking framework provides a key component of a blueprint for harnessing the power of AIWP models to help large vulnerable populations adapt to weather shocks in the face of
climate variability and change.
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All authors Rajat Masiwal, Colin Aitken, Adam Marchakitus, Mayank Gupta, Katherine Kowal, Hamid A. Pahlavan, Tyler Yang, Y. Qiang Sun, Michael Kremer, Amir Jina, William R. Boos, Pedram Hassanzadeh
Plasma Physics
A High-order piecewise field-aligned triangular finite element method for electromagnetic gyrokinetic particle simulations of tokamak plasmas with open field lines
Zhixin Lu, Guo Meng, Eric Sonnendruecker et al. (+6 more)
A high-order piecewise field-aligned triangular finite element method is developed and implemented for global electromagnetic gyrokinetic particle-in-
cell simulations of tokamak
plasmas with open field lines. The approach combines locally field-aligned finite element basis functions with unstructured $C^{1}$ triangular meshes in cylindrical coordinates, enabling whole-volume simulations with substantially reduced computational effort, while avoiding the grid distortion associated with globally field-aligned coordinates and the associated singularity at the separatrix of diverted
plasmas. The formulation is compatible with both $\delta f$ and full-$f$ models and employs mixed-variable representations, along with a generalized pullback scheme, to control numerical cancellation in electromagnetic simulations. The method is implemented in the TRIMEG-C1 code and demonstrated using linear and nonlinear electromagnetic simulations of the TCV-X21 configuration. The results indicate that the approach accurately captures the key features of electromagnetic ion-temperature-gradient and kinetic ballooning mode physics, including the separatrix regions in the simulation, thereby providing a robust framework for whole-volume electromagnetic gyrokinetic simulations in realistic tokamak geometries.
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All authors Zhixin Lu, Guo Meng, Eric Sonnendruecker, Roman Hatzky, Giorgio Daneri, Gengxian Li, Peiyou Jiang, Klaus Reuter, Matthias Hoelzl
Plasma Physics
A numerical study on plasma acceleration processes with ion dynamics at the sub-nanosecond timescale
G. Parise, A. Cianchi, M. Galletti et al. (+5 more)
Plasma wakefield acceleration is a groundbreaking technique for accelerating particles, capable of sustaining gigavolt-per-meter accelerating fields. Understanding the physical mechanisms governing the recovery of
plasma accelerating properties over time is essential for successfully achieving high-repetition-rate
plasma acceleration, a key requirement for applicability in both research and commercial settings. In this paper, we present numerical simulations of the early-stage
plasma evolution based on the parameters of the SPARC_LAB hydrogen
plasma recovery time experiment (Pompili et al., Comm. Phys. 7, 241 (2024)), employing spatially resolved Particle-in-
Cell and fluid models. The experiment reports on a non-monotonic dependence of the
plasma recovery time on the initial
plasma density, an effect for which ion motion has been invoked as a contributing factor. The simulations presented here provide further insight into the role of ion dynamics in shaping this behavior. Furthermore, comparing Particle-in-
Cell and fluid approaches allows us to assess the quality of fluid models for describing this class of
plasma dynamics.
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All authors G. Parise, A. Cianchi, M. Galletti, F. Guglietta, R. Pompili, A. R. Rossi, M. Sbragaglia, D. Simeoni
Optics · Cross-listed from astro-ph.IM
Star Grazing with Alumina Grass: Antireflection coatings in the visible and near-infrared on IPX-Clear Microlenses assisted by Grass-like Alumina
Ishan Rana, Suvrath Mahadevan, Megan Delamer et al. (+1 more)
Two-
photon polymerization (2PP) enables fabrication of high-precision micro-optics with complex freeform geometries, opening a new parameter space for custom astronomical optics. Among available resins, the newly developed IPX Clear is particularly well suited for visible applications, offering high transmission across the visible-near-IR, low surface roughness, and excellent shape fidelity. However, Fresnel reflections at the air-
polymer interface introduce significant optical losses, which are detrimental in low-signal astronomy. Previous studies show grass-like alumina coatings on glass and fused silica can raise average transmission from 91.9% to approximately 99% over 400-900 nm. Here we explore the feasibility of Atomic Layer Deposition (ALD) to apply such coatings to IPX-Clear micro-optics over 400-1700 nm. Grass-like alumina anti-reflective (AR) coatings can approximate the ideal index condition by creating a gradual refractive-index transition from air to bulk IPX Clear, suppressing surface reflections. While grass-like coatings are established on bulk optics and conformal ALD films have been applied to 2PP micro-optics, we demonstrate - for the first time - alumina grass on 2PP microlenses made with the new IPX-Clear resin. We discuss key challenges and process steps, and observe that alumina-grass-coated microlenses lose only approximately 0.3% of
photons to reflection in the 400-850 nm range. Future work will test performance across the full 400-1700 nm band and explore improved environmental resilience, e.g., a SiO2 overcoat. Combined with the high optical transparency of IPX Clear, these coatings enable custom-designed, highly efficient microlenses for astronomical applications.
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All authors Ishan Rana, Suvrath Mahadevan, Megan Delamer, Ceiwynn Longworth
Computational Physics
Transformation front kinetics in deformable ferromagnets
Michael Poluektov
Materials such as
magnetic shape-
memory alloys possess an intrinsic coupling between material's magnetisation and mechanical deformation. These materials also undergo structural phase transitions, with phase boundaries separating different phases. The kinetics of the phase boundaries is governed by the
magnetic field and the mechanical stresses. There is a multiplicity of other materials revealing similar phenomena, e.g.\
magnetic perovskites. To model the propagation of the phase boundaries in deformable
magnetic materials at the continuum scale, three ingredients are required: a set of governing equations for the bulk behaviour with coupled
magnetic and mechanical degrees of freedom, a dependency of the phase boundary velocity on the governing factors, and a reliable computational method. The expression for the phase boundary velocity is usually obtained within the continuum thermodynamics setting, where the
entropy production due to phase boundary propagation is derived, which gives a thermodynamic driving force for the phase boundary kinetics. For deformable ferromagnets, all three elements (bulk behaviour, interface kinetics, and computational approaches) have been explored, but under a number of limitations. The present paper focuses on the derivation of the thermodynamic driving force for transformation fronts in a general magneto-mechanical setting, adapts the cut-finite-element method for transformation fronts in magneto-mechanics, which allows for an exceptionally efficient handling of the propagating interfaces, without modifying the finite-element mesh, and applies the developments to qualitative modelling of magneto-mechanics of
magnetic shape-
memory alloys.
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Medical Physics
Reducing acquisition time and radiation damage: data-driven subsampling for spectro-microscopy
Maike Meier, Lorenzo Lazzarino, Boris Shustin et al. (+2 more)
Spectro-microscopy is an experimental technique which can be used to observe spatial variations in chemical state and changes in chemical state over time or under experimental conditions. As a result it has broad applications across areas such as energy materials, catalysis, environmental science and biological samples. However, the technique is often limited by factors such as long acquisition times and radiation damage. We present two measurement strategies that allow for significantly shorter experiment times and total doses applied. The strategies are based on taking only a small subset of all the measurements (e.g. sparse acquisition or subsampling), and then computationally reconstructing all unobserved measurements using mathematical techniques. The methods are data-driven, using spectral and spatial importance subsampling distributions to identify important measurements. As a result, taking as little as 4-6% of the measurements is sufficient to capture the same information as in a conventional scan.
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All authors Maike Meier, Lorenzo Lazzarino, Boris Shustin, Hussam Al Daas, Paul Quinn
Physics and Society
Emergent structures in coupled opinion and network dynamics
Andrew Nugent, Carmen Calatayud Fernandez and Susana N. Gomes
This paper investigates a model of opinion formation on an adaptive social network, consisting of a system of coupled ordinary differential equations for individuals' opinions and corresponding network edge weights. A key driver of the system's behaviour is the form of the interaction function, which determines the strength of interactions based on the distance between individuals' opinions and appears in both opinion and network dynamics. Two cases are examined: in the first the interaction function is always positive and in the second case the interaction function is of bounded-confidence type. In both cases there is positive feedback between opinion clustering and the emergence of community structure in the social network. This is confirmed through analytical results on long-term behaviour, extending existing results for a fixed network, as well as through numerical simulations. Transient network dynamics are also examined through a short-time approximation that captures the `typical' early network dynamics. Each approach improves some aspect of our understanding of the interplay between opinion and network
evolution.
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Space Physics
Generation and Expansion-Driven Growth of Switchbacks in the Outer Solar Corona and Solar Wind
Nikos Sioulas, Marco Velli, Chen Shi et al. (+6 more)
We analyze Parker
Solar Probe and
Solar Orbiter measurements of
magnetic-field reversals (“switchbacks”) across the Alfvén surface ($M_a\simeq 1$), where $M_a$ is the Alfvén Mach number. The reported “sub-Alfvénic switchback dropout” follows from two diagnostic biases: conditioning on an instantaneous $M_a$, which is transiently elevated above unity by radial-velocity enhancements during large-amplitude Alfvénic rotations, and short-window local-mean backgrounds that partially track these rotations and suppress deflection angles. Treating $M_a$ as a bulk-stream property via rolling medians and referencing deflections to event-independent backgrounds – a Parker-spiral direction or a sufficiently long rolling median – recovers sub-Alfvénic switchbacks systematically. The mean deflection $\langle \theta \rangle$ separates into two regimes with $M_a$. For $M_a \lesssim 1$, $\langle \theta \rangle$ rises rapidly with weak dependence on the background window, consistent with expansion-driven amplification of Alfvénic fluctuations. For $M_a \gtrsim 1$, the
evolution becomes scale dependent: large-scale $\langle \theta \rangle$ continues to grow with $M_a$ at reduced rate, while small-scale growth saturates, consistent with turbulent decay and dissipation. Collectively, these results indicate that switchbacks need not originate only in the super-Alfvénic
solar wind. Instead, they are consistent with a formation pathway in which coronal fluctuations are amplified by large-scale expansion through the sub-Alfvénic regime, with subsequent propagation into the super-Alfvénic wind where turbulent decay modifies their scale-dependent properties.
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All authors Nikos Sioulas, Marco Velli, Chen Shi, Lorenzo Matteini, Trevor A. Bowen, Alfred Mallet, A. Larosa, Anna Tenerani, Timothy S. Horbury
Applied Physics
Machine-Learning Optimization of Detector-Grade Yield in High-Purity Germanium Crystal Growth
Athul Prem, Dongming Mei, Sanjay Bhattarai et al. (+2 more)
High-purity germanium (HPGe)
crystals underpin some of the most sensitive detectors used in fundamental physics and other high-resolution radiation-sensing applications. Despite their importance, the supply of detector-grade HPGe remains limited because achieving high yield in Czochralski growth (CZ) depends on tightly coupled, nonlinear processes,
impurity incorporation, thermal gradients, and dynamic control settings that are largely mastered by only a handful of companies with decades of experience. Here we present a data-driven prediction framework based on a Bidirectional Long Short-Term
Memory (BiLSTM) neural network with multi-head
attention, trained on time-resolved growth parameters (e.g., heater power, pull rate, and
impurity indicators) from 48 independent
crystal runs. The model predicts the final detector-grade fraction for each growth and, using SHAP feature-importance analysis, identifies
impurity concentration and growth rate as the dominant factors governing yield, consistent with empirical understanding. By providing a quantitative, interpretable link between in-process signals and post-growth detector quality, this framework offers a practical path toward improving yield, reducing dependence on trial-and-error tuning, and scaling HPGe production for next-generation rare-event detectors.
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All authors Athul Prem, Dongming Mei, Sanjay Bhattarai, Narayan Budhathoki, Sunil Chhetri
Applied Physics · Cross-listed from cond-mat.mes-hall
Stochastic Dynamics of Diffusive Memristor Blocks for Neuromorphic Computing
Wendy Otieno, Alex Gabbitas, Debi Pattnaik et al. (+3 more)
Biological systems use neural
circuits to integrate input information and produce outputs. Synaptic convergence, where multiple
neurons converge their inputs onto a single downstream
neuron, is common in natural neural
circuits. However, understanding specific computations performed by such neural blocks and implementating them in hardware requires further research. This work focuses on synaptic convergence in a simplified
circuit of three spiking artificial
neurons based on diffusive memristors. Numerical modelling and experiments reveal input voltage combinations that enable targeted activation of spiking for specific
neuron configurations. We analyse the statistical characteristics of spiking patterns and interpret them from a computational perspective. The numerical simulations match experimental measurements. Our findings contribute to development of universal functional blocks for neuromorphic systems.
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All authors Wendy Otieno, Alex Gabbitas, Debi Pattnaik, Pavel Borisov, Sergey Savel'ev, Alexander G. Balanov
Fluid Dynamics · Cross-listed from math.DG
Point Vortex Dynamics on Closed Surfaces
Marcel Padilla
The theory of point
vortex dynamics has existed since Kirchhoff's proposal in 1891 and is still under development with connections to many fields in mathematics. As a strong simplification of the concept of vorticity it excels in computational speed for vorticity based fluid simulations at the cost of accuracy. Recent finding by Stefanella Boatto and Jair Koiller allowed the extension of this theory on to closed surfaces. A comprehensive guide to point
vortex dynamics on closed surfaces with genus zero and vanishing total vorticity is presented here. Additionally fundamental knowledge of fluid dynamics and surfaces are explained in a way to unify the theory of point
vortex dynamics of the plane, the sphere and closed surfaces together with implementation details and supplement material.
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Physics and Society
Instantaneous Spectra Analysis of Pulse Series – Application to Lung Sounds with Abnormalities
Fumihiko Ishiyama
The origin of the "theoretical limit of time-frequency resolution of
Fourier analysis" is from its numerical implementation, especially from an assumption of "Periodic Boundary Condition (PBC)," which was introduced a century ago. We previously proposed to replace this condition with "Linear eXtrapolation Condition (LXC)," which does not require periodicity. This feature makes instantaneous spectra analysis of pulse series available, which replaces the short time
Fourier transform (STFT). We applied the instantaneous spectra analysis to two lung sounds with abnormalities (crackles and wheezing) and to a normal lung sound, as a demonstration. Among them, crackles contains a random pulse series. The spectrum of each pulse is available, and the spectrogram of pulse series is available with assembling each spectrum. As a result, the time-frequency structure of given pulse series is visualized.
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Classical Physics · Cross-listed from cs.LG
Equilibrium Propagation for Non-Conservative Systems
Antonino Emanuele Scurria, Dimitri Vanden Abeele, Bortolo Matteo Mognetti et al. (+1 more)
Equilibrium Propagation (EP) is a physics-inspired learning
algorithm that uses stationary states of a dynamical system both for inference and learning. In its original formulation it is limited to conservative systems, $\textit{i.e.}$ to dynamics which derive from an energy function. Given their applications, it is important to extend EP to non-conservative systems, $\textit{i.e.}$ systems with non-reciprocal interactions. Previous attempts to generalize EP to such systems failed to compute the exact gradient of the cost function. Here we propose a framework that extends EP to arbitrary non-conservative systems, including feedforward networks. We keep the key property of
equilibrium propagation, namely the use of stationary states both for inference and learning. However, we modify the dynamics in the learning phase by a term proportional to the non-reciprocal part of the interaction so as to obtain the exact gradient of the cost function. This
algorithm can also be derived using a variational formulation that generates the learning dynamics through an energy function defined over an augmented state space. Numerical experiments show that this
algorithm achieves better performance and learns faster than previous proposals.
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All authors Antonino Emanuele Scurria, Dimitri Vanden Abeele, Bortolo Matteo Mognetti, Serge Massar
Physics and Society · Cross-listed from nlin.AO
Noisy nonlocal aggregation model with gradient flow structures
Su Yang, Weiqi Chu and Panayotis G. Kevrekidis
Interacting particle systems provide a fundamental framework for modeling collective behavior in biological, social, and physical systems. In many applications,
stochastic perturbations are essential for capturing environmental variability and individual uncertainty, yet their impact on long-term dynamics and
equilibrium structure remains incompletely understood, particularly in the presence of nonlocal interactions. We investigate a
stochastic interacting particle system governed by potential-driven interactions and its continuum density formulation in the large-population limit. We introduce an energy functional and show that the macroscopic density
evolution has a gradient-flow structure in the Wasserstein-2 space. The associated variational framework yields
equilibrium states through constrained energy minimization and illustrates how noise regulates the density and mitigates singular concentration. We demonstrate the connection between microscopic and macroscopic descriptions through numerical examples in one and two dimensions. Within the variational framework, we compute energy minimizers and perform a linear stability analysis. The numerical results show that the stable minimizers agree with the long-time dynamics of the macroscopic density model.
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Instrumentation and Detectors
Fabrication and Characterization of p-type Inverted Coaxial Point Contact (ICPC) Detectors with a-Ge Dual-Blocking Contacts
S.A. Panamaldeniya, K.M. Dong and D.M. Mei
We report the fabrication and characterization of two p-type inverted coaxial point contact (ICPC) high-purity germanium (HPGe) detectors, SAP16 and SAP17, produced from USD-grown
crystals with net
impurity concentrations of $\sim 3\times10^{10}\,\mathrm{cm^{-3}}$. Both devices employ thin amorphous-germanium (a-Ge) dual-blocking contacts, implemented here for the first time on ICPC detectors, to provide bipolar charge blocking while limiting dead-layer thickness. Electrical tests at 76~K demonstrate stable operation with picoampere-level leakage currents and sub-pF capacitance: SAP17 reached $\sim 4.62$~pA at the maximum tested bias (500~V) and operated stably at 400~V with $C\simeq 0.503$~pF. Meanwhile, SAP16 achieved superior spectroscopic performance, with energy resolutions of 2.42% at 59.5~keV and 0.36% at 662~keV. Gamma-ray spectroscopy with $^{241}$Am and $^{137}$Cs shows that modest
geometric differences lead to measurable changes in depletion behavior and charge-collection uniformity, consistent with electrostatic modeling. Angular-response measurements further reveal pronounced directional sensitivity at 59.5~keV, whereas the 662~keV response is essentially isotropic over the measured range. These results validate thin a-Ge dual-blocking contacts for ICPC HPGe detectors and highlight geometry-driven trade-offs among leakage current, depletion, and energy resolution relevant to low-background and low-threshold applications.
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Medical Physics · Cross-listed from cs.CV
Quasi-multimodal-based pathophysiological feature learning for retinal disease diagnosis
Lu Zhang, Huizhen Yu, Zuowei Wang et al. (+4 more)
Retinal diseases spanning a broad spectrum can be effectively identified and diagnosed using complementary signals from
multimodal data. However,
multimodal diagnosis in ophthalmic practice is typically challenged in terms of data heterogeneity, potential invasiveness, registration complexity, and so on. As such, a unified framework that integrates
multimodal data synthesis and fusion is proposed for retinal disease classification and grading. Specifically, the synthesized
multimodal data incorporates fundus fluorescein angiography (FFA), multispectral imaging (MSI), and saliency maps that emphasize latent lesions as well as optic disc/cup regions. Parallel models are independently trained to learn modality-specific representations that capture cross-pathophysiological signatures. These features are then adaptively calibrated within and across modalities to perform information
pruning and flexible integration according to downstream tasks. The proposed learning system is thoroughly interpreted through visualizations in both image and feature spaces. Extensive experiments on two public
datasets demonstrated the superiority of our approach over state-of-the-art ones in the tasks of multi-label classification (F1-score: 0.683, AUC: 0.953) and diabetic retinopathy grading (Accuracy:0.842, Kappa: 0.861). This work not only enhances the accuracy and efficiency of retinal disease screening but also offers a scalable framework for data augmentation across various medical imaging modalities.
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All authors Lu Zhang, Huizhen Yu, Zuowei Wang, Fu Gui, Yatu Guo, Wei Zhang, Mengyu Jia
Computational Physics · Cross-listed from astro-ph.IM
A Method for Thermal Radiation Transport Using Backward Characteristic Tracing
J. C. Dolence, H. R. Hammer, H. Park et al. (+3 more)
Thermal radiation transport is a challenging problem in computational physics that has long been approached primarily in one of a few standard ways: approximate moment methods (for instance P$_1$ or M$_1$), implicit Monte Carlo, discrete ordinates, and long characteristics. In this work we consider the efficacy of the Method of (Long) Characteristics (MOC) applied to thermal radiation transport. Along the way we develop three major ideas: transporting MOC particles backwards in time from quadrature grids at the end of the timestep, limiting the computational cost of these backward characteristics by terminating transport once optical depths along rays become sufficiently large, and timestep-dependent closures with multigroup MOC solutions for a gray low-order system. We apply this method to a suite of standard radiation transport and radiation hydrodynamics test problems. We compare the method to several standard analytic and semi-analytic solutions, as well as implicit Monte Carlo, P$_1$, and discrete ordinates (S$_n$). We see that the method: gives excellent agreement with known results, has stability for large time steps, has the
diffusion limit for large spatial
cells, and achieves $\sim$20-70% performance improvement when terminating optical depths at O(10-100) in the grey Marshak and crooked pipe problems. However, for the Coax radiation-hydrodynamics problem, we see that MOC is approximately two to three times slower than IMC-DDMC and S$_n$ in its current implementation.
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All authors J. C. Dolence, H. R. Hammer, H. Park, B. Prather, B. R. Ryan, R. T. Wollaeger
Physics and Society
Toward a new AI winter? How diffusion of technological innovation on networks leads to chaotic boom-bust cycles
Sabin Roman and Francesco Bertolotti
Technological developments and the impact of artificial intelligence (AI) are omnipresent themes and concerns of the present day. Much has been written on these topics but applications of quantitative models to understand the techno-social landscape have been much more limited. We propose a mathematical model that can help understand in a unified manner the patterns underlying technological development and also identify the different regimes in which the technological landscape evolves. First, we develop a model of innovation
diffusion between different technologies, the growth of each reinforcing the development of the others. The model has a variable that quantifies the level of development (or innovation, discovery) potential for a given technology. The potential, or
market capacity, increases via
diffusion from related technologies, reflecting the fact that a technology does not develop in isolation. Hence, the growth of each technology is influenced by how developed its neighboring (related) technologies are. This allows us to reproduce long-term trends seen in computing technology and large
language models (LLMs). We then present a three-dimensional system of supply, demand, and investment which shows oscillations (business cycles) emerging if investment is too high into a given technology, product, or
market. We finally combine the two models through a common variable and show that if investment or
diffusion is too high in the network context, chaotic boom-bust cycles can emerge. These quantitative considerations allow us to reproduce the boom-bust patterns seen in non-fungible
token (NFT) transaction data and also have deep implications for the development of AI which we highlight, such as the arrival of a new AI winter.
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Fluid Dynamics
Distributed Roughness-Induced Transition on a Blunt Body at Mach 6: a Numerical Investigation
Sean Dungan, Mateus Braga, Robyn Macdonald et al. (+1 more)
Surface roughness significantly impacts transition to
turbulence, especially over high-speed, blunt geometries where surface ablation is necessary to mitigate heat loads during atmospheric entry. Inspired by sand-grain roughness experiments performed by Hollis (2017), we perform the first direct numerical simulation (DNS) of a blunt cylinder in Mach 6 cross-flow with roughness elements distributed along the entire surface. Such simulations aimed to uncover the precise means by which laminar-turbulent transition occurs given the limited measurements attainable from experiments and non-existent high-fidelity simulations. Element heights were held fixed at approximately 35% boundary layer thickness, while the relative phasing between streamwise rows was varied. All configurations exhibited convective instabilities driving the transition process, with the mode type being set by the roughness configuration. A fundamental sinuous streak mode dominated the aligned roughness element case, whereas both the staggered and randomly phased cases saw 2D T-S waves dominating. These instability waves, when grown to sufficient amplitude, triggered the steady streaks seeded by the underlying roughness pattern to begin forming hairpin
vortices and breakdown occurred soon thereafter. The roughness arrangement was found to dramatically influence the degree to which the waves were destabilised, as well as the strength of the underlying steady streaks, thereby combining to dictate the position along the surface where LTT occurred. Finally, exogeneous forcing was not required for the T-S dominated cases as the acoustics generated by the
turbulence in the subsonic flow excited T-S waves on the other side - a feedback mechanism hitherto unknown.
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All authors Sean Dungan, Mateus Braga, Robyn Macdonald, Christoph Brehm
Plasma Physics
Multi-Diagnostic Characterization of Laser-Produced Tin Plasmas for EUV Lithography
Stanislav Musikhin, Anatoli Morozov, Alec Griffith et al. (+2 more)
We present a comprehensive characterization of
laser-produced tin (Sn)
plasmas relevant to extreme ultraviolet (EUV) lithography using a multi-diagnostic suite integrated into the new experimental platform, "SparkLight". Tin
plasmas are generated by irradiating a continuously moving tin-coated wire with
laser pulses (1064 nm, 10 ns, up to $5.7\times10^{10}$ W/cm$^2$) and probed via coherent Thomson scattering,
laser interferometry, and EUV emission spectroscopy. Thomson scattering measurements reveal electron temperatures and densities that decay with distance from the target. Densities derived from Thomson scattering are cross-validated against
laser interferometry, showing excellent agreement. Correlating the results of these
laser diagnostics with spatially resolved EUV spectroscopy suggests that the bulk of useful EUV emission originates within 150 $\mu$m of the target and is generated under suboptimal
plasma conditions. This work demonstrates a practical integrated approach for
plasma characterization in EUV source development.
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All authors Stanislav Musikhin, Anatoli Morozov, Alec Griffith, Shurik Yatom, Ahmed Diallo
Fluid Dynamics · Cross-listed from cond-mat.quant-gas
Dynamic similarity of vortex shedding in a superfluid flowing past a penetrable obstacle
Junhwan Kwon and Y. Shin
We numerically investigate wake dynamics in a superfluid flowing past a penetrable obstacle. Unlike an impenetrable object, a penetrable obstacle does not fully deplete the density. We define an effective diameter $D_{\rm eff}$ from the Mach-1 contour of the time-averaged irrotational flow around the obstacle, which delineates the local supersonic region where quantized
vortices nucleate. Using this flow-defined length scale, we construct a superfluid Reynolds number $Re_{\rm s} = (v_0 - v_c) D_{\rm eff}/ (\hbar/ m)$, where $v_0$ is the flow speed, $v_c$ is the critical velocity, and m is the particle mass. We show that $Re_{\rm s}$ organizes the wake dynamics across obstacle sizes and strengths: the transition from dipole-row emission to alternating
vortex cluster shedding occurs at $Re_{\rm s}$ around 2, and both the Strouhal number and the drag coefficient collapse onto universal curves when plotted as functions of $Re_{\rm s}$. These results extend the concept of dynamic similarity in superfluid flows to penetrable obstacles and demonstrate that the dynamically relevant length scale is determined by the supersonic region rather than by the
geometric obstacle size.
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Geophysics
Radial gradient of superionic hydrogen in Earth's inner core
Zepeng Wu, Liangrui Wei, Chen Gao et al. (+3 more)
Hydrogen is considered a key light element in Earth's core, yet the thermodynamics of its superionic phase and its distribution in the inner core remain unclear. Here, we compute ab initio Gibbs free energies for
liquid and superionic hcp and bcc Fe-H phases and construct the superionic-
liquid phase diagram over pressure-temperature conditions relevant to the Earth's inner core. We find that phase diagrams at different inner-core pressures collapse when temperatures are scaled by the melting temperature of pure iron, indicating that solid-
liquid partitioning is controlled primarily by a reduced temperature relative to iron melting and is weakly sensitive to pressure. This scaling relation further reconciles previously reported discrepancies in partition coefficients among theoretical studies and yields good agreement with available experimental data at low pressures. By applying thermochemical constraints, our free-energy results reveal a radial hydrogen gradient within the inner core. These results demonstrate that compositional gradients of superionic hydrogen in the inner core emerge naturally from
equilibrium thermodynamics and suggest a general mechanism governing the depth-dependent distribution of light elements within Earth's inner core.
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All authors Zepeng Wu, Liangrui Wei, Chen Gao, Shunqing Wu, Renata M. Wentzcovitch, Yang Sun