History and Philosophy of Physics
Schrodinger's Wave Mechanics: Remarkable Dates and Place One Hundred Years Ago
Sergei K. Suslov
We discuss, at a level accessible to a wide audience, including students and teachers of physics and mathematics, the fundamental transition from classical mechanics to wave equations made by Schroedinger a century ago. These historical events clarify the structure and significance of
quantum mechanics and are of interest to the global scientific community. Valuable sources for further studies are provided throughout the article.
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Plasma Physics
FUSENOW, NAPLIFE Collaborations: Zsuzsanna Márton, Imene Benabdelghani et al. (+23 more)
Why do we use nano-
antennas for fusion? In three sentences: The present
laser induced fusion plans use extreme mechanical shock compression to get one hotspot and then ignition. Still fusion burning spreads slower than expansion, and mechanical instabilities may also develop. With nano-
antennas in radiation dominated systems, simultaneous ignition can be achieved in the whole target volume and there is no time left for mechanical instabilities. Ignition is achieved with
protons accelerated in the direction of the nanoantennas that are orthogonal to the direction of
laser irradiation. Present
laser fusion methods are based on extreme and slow mechanical compression with an ablator surface on the fuel target pellet to increase compression and eliminate penetration of
laser electromagnetic energy into the target. This arises from a mistaken assumption, [1] that the detonation normal 4-vector should have vanishing time-like component, and this assumption eliminates the possibility to rapid or even simultaneous, radiation dominated detonations, (which are well known in the burning (or hadronization) of
Quark Gluon Plasma).
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All authors FUSENOW, NAPLIFE Collaborations: Zsuzsanna Márton, Imene Benabdelghani, Márk Aladi, Judit Budai, Aldo Bonasera, Attila Bonyár, Mária Csete, Tibor Gilinger, Martin Greve, Jan-Petter Hansen, Gergely Hegedűs, Ádám Inger, Miklos Kedves, Károly Osvay, István Papp, Péter Rácz, András Szenes, Ágnes Szokol, Dávid Vass, Parvin Varmazyar, Miklós Veres, Konstantin Zsukovszki, Tamás S. Bíró, Norbert Kroó, Laszlo P. Csernai
Plasma Physics · Cross-listed from astro-ph.SR
The gravitational stratification of multifluid and multispecies plasma
F. Zhang, J. Martínez-Sykora, Q. M. Wargnier et al. (+1 more)
Context. The
solar atmosphere is gravitationally stratified and consists of several layers at temperatures that vary by several orders of magnitude. Consequently, the
solar atmospheric
plasma changes from weakly ionized in the photosphere, partially ionized in the chromosphere, and to fully ionized in the corona. However, integrating ionization and recombination processes into multifluid
solar plasma models with gravitational stratification continues to be a nontrivial task. Aims. We intend to provide a method for constructing multifluid+multispecies (MFMS) gravitational stratification that satisfies the ionization
equilibrium and hydrostatic
equilibrium at the same time, avoiding causing nonphysical disturbances and numerical instability due to the initial imbalances. Methods. We assume that collisional interactions between fluids are sufficient for coupling all fluids when there is no high-frequency external driving force imposed. Ionization fractions can be (I) calculated assuming ionization in statistical
equilibrium at any given temperature or (II) extracted from other atmospheric models. A simple numerical integration routine would then be used to construct MFMS gravitational stratifications. Results. The gravitational stratification in hydrostatic
equilibrium can be constructed using the present numerical integration routine with any given ionization fractions of multispecies
plasmas. Meanwhile, without any dynamic driving force, fluid decoupling is initiated, particularly in the transition region of the constructed stratification, while the total velocity of all fluids remains at the level of zero. Conclusions. A gravitational stratification constructed using the present routine can be used in MFMS models to study specific dynamics without being affected by the initial imbalances.
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All authors F. Zhang, J. Martínez-Sykora, Q. M. Wargnier, V. H. Hansteen
Biological Physics · Cross-listed from cond-mat.soft
Mechanics of axis formation in $\textit{Hydra}$
Arthur Hernandez, Cuncheng Zhu and Luca Giomi
The emergence of a body axis is a fundamental step in the development of multicellular organisms. In simple systems such as $\textit{Hydra}$, growing evidence suggests that mechanical forces generated by collective cellular activity play a central role in this process. Here, we explore a physical mechanism for axis formation based on the coupling between active stresses and tissue elasticity. We analyse the elastic deformation induced by activity-generated stresses and show that, owing to the spherical
topology of the tissue, forces globally condense toward configurations in which both elastic strain and nematic defect localise at opposite poles. These mechanically selected states define either a polar or apolar head-food axis. To characterize the condensed regime, we introduce a compact parametrization of of the active force and flux distributions, enabling analytical predictions and direct comparison with experiments. Using this framework, we calculate experimentally relevant observables, including areal strain, lateral pressure, and normal displacements during muscular contraction, as well as the detailed structure of topological defect complexes in head and foot regions. Together, our results identify a mechanical route by which active tissues can spontaneously break
symmetry at the organismal scale, suggesting a general physical principle underlying body-axis specification during morphogenesis.
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Space Physics · Cross-listed from astro-ph.SR
Addressing Known Challenges in Solar Flare Forecasting I: Limb-Flare Prediction with a 4-pi Full-Heliosphere Framework
K.D. Leka, Eric L. Wagner, Lisa Upton et al. (+3 more)
A demonstrated failure mode for operational
solar flare forecasting is the inability to forecast
flares that occur near, or just beyond, the
solar limb. To address this shortcoming, we develop a "4pi" full-heliosphere event
forecasting framework and evaluate its statistical classification ability against this specific challenge. A
magnetic surface flux transport model is used to generate full-sun maps of the photospheric radial
magnetic field from which active regions (ARs) are identified and tracked using a new labeling scheme that is observer-location agnostic and allows for post-facto modifications.
Flare-relevant
magnetic parameters couple to a "visibility" index that specifies AR location relative to the visible
solar limb and expected
flare detection.
Flare labels are assigned according to peak Soft X-ray flux, and a statistical classification is performed using nonparametric discriminant analysis. A version where new or emerging ARs on the far ("invisible" side of the Sun are incorporated into the model by way of far-side helioseismology, is also tested. We evaluate the new framework by its performance specifically including the limb areas using Brier Skill Score and ROC Skill Score, finding improvement at the 2-sigma level or less. However, we do find that the number of False Negatives, or "missed" forecasts decreases, and find strong evidence that the additional information provided by the far-side helioseismology can help predict near- and just-beyond-limb
flares, particularly for East-limb events. While individual components of this framework could be improved, we demonstrate that a known failure mode for
solar flare forecasting can be mitigated with available resources.
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All authors K.D. Leka, Eric L. Wagner, Lisa Upton, Bibhuti Kumar Jha, Kiran Jain, Sara Petty
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Local Multimodal Dynamics in Mixed Ionic-Electronic Conductors and Their Fingerprints in Organic Electrochemical Transistor Operation
Shubham Tanwar, Han-Yan Wu, Chi-Yuan Yang et al. (+4 more)
Mixed ionic-electronic conductors host tightly coupled interactions among mobile ions, electronic charges, and the
polymer matrix, giving rise to complex
multimodal responses spanning electrical, mechanical, and morphological transformations. These materials underpin organic electrochemical transistors (OECTs), which translate such interactions into low-voltage signal amplification and sensing for applications in bioelectronics, neuromorphic computing, and
memory. Despite their central role, OECT current-voltage transfer characteristics are often treated phenomenologically, as both the local
multimodal dynamics and their connection to global device response remain unresolved. Here, we reveal that the transfer curve encodes a cascade of spatially localized electrochemical transitions, each associated with distinct changes in conductivity, stiffness, and morphology, fundamentally redefining it as a spatially resolved fingerprint of device's internal state. Using automated operando
multimodal in-
liquid scanning dielectric microscopy, we directly map these dynamics and identify region-specific electrochemical thresholds governing the interplay between source, channel, and drain. We found that the local tip-sample electrostatic force serves as a remarkable mechanistic observable of coupled
multimodal dynamics in mixed conductors. A physically grounded model links it to general material, interfacial, and
geometric parameters, enabling mechanistic interpretation and predictive insights. Our work provides a new framework for probing and understanding mixed conduction in ion-electron coupled systems.
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All authors Shubham Tanwar, Han-Yan Wu, Chi-Yuan Yang, Ruben Millan-Solsona, Simone Fabiano, Adrica Kyndiah, Gabriel Gomila
Physics and Society
Reducibility of higher-order to pairwise interactions: Social impact models on hypergraphs
Jaume Llabrés, Raúl Toral, Maxi San Miguel et al. (+1 more)
We show that a general class of social impact models with higher-order interactions on hypergraphs can be exactly reduced to an equivalent model with pairwise interactions on a weighted projected network. This reduction is made by a mapping that preserves the microscopic probabilities of changing the state of the nodes. As a particular case, we introduce hypergraph-voter models, for which we compute the weights of the projected network both analytically and numerically across several hypergraph ensembles, and we characterize their ordering dynamics through simulations of both higher-order and reduced dynamics. For a linear social impact function (hypergraph-linear voter model) the weights of the projected network are static, allowing us to develop a pair approximation that describes with accuracy the time
evolution of macroscopic observables, which turn out to be independent of those weights. The macroscopic dynamics is thus equivalent to that of the standard voter model on the unweighted projected network. For a power-law social impact function (hypergraph-nonlinear voter model) the weights of the projected network depend on the instantaneous system configuration. Nevertheless, the nonlinear voter model on the unweighted projected network still reproduces the main macroscopic trends for well connected hypergraphs.
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All authors Jaume Llabrés, Raúl Toral, Maxi San Miguel, Federico Vázquez
Computational Physics · Cross-listed from quant-ph
Quantum Elastic Network Models and their Application to Graphene
Ioannis Kolotouros, Adithya Sireesh, Stuart Ferguson et al. (+3 more)
Molecular dynamics simulations are a central computational methodology in materials design for relating atomic composition to mechanical properties. However, simulating materials with atomic-level resolution on a macroscopic scale is infeasible on current classical hardware, even when using the simplest elastic network models (ENMs) that represent molecular vibrations as a network of coupled oscillators. To address this issue, we introduce
Quantum Elastic Network Models (QENMs) and utilize the
quantum algorithm of Babbush et al. (PRX, 2023), which offers an exponential advantage when simulating systems of coupled oscillators. Here, we extend their
algorithm in 2D systems and demonstrate how our method enables the efficient simulation of planar materials. As an example, we apply our
algorithm to the task of simulating a 2D
graphene sheet. We analyze the complexity for initial-state preparation,
Hamiltonian simulation, and measurement of this material, and provide two real-world applications: heat transfer and the out-of-plane rippling effect. We estimate that an atomistic simulation of a
graphene sheet on the centimeter scale, classically requiring hundreds of petabytes of
memory and prohibitive runtimes, could be encoded and simulated with as few as $\sim 160$ logical
qubits.
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All authors Ioannis Kolotouros, Adithya Sireesh, Stuart Ferguson, Sean Thrasher, Petros Wallden, Julien Michel
Fluid Dynamics
Revisiting the scale dependence of the Reynolds number in correlated fluctuating fluids
Sijie Huang, Ayush Saurabh and Steve Pressé
For the incompressible Navier–Stokes equation, the Reynolds number ($\mathrm{Re}$) is a dimensionless parameter quantifying the relative importance of inertial over viscous forces. In the low-$\mathrm{Re}$ regime ($\mathrm{Re} \ll 1$), the flow dynamics are commonly approximated by the linear Stokes equation. Here we show that, within the framework of spatially fluctuating hydrodynamics, this linearization breaks down when the thermal noise is spatially correlated, even if $\mathrm{Re} \ll 1$. We perform direct numerical simulations of spatially correlated fluctuating hydrodynamics in both one and two dimensions. In one dimension, the linearized dynamics exhibit significantly slower relaxation of high-wavenumber
Fourier modes than the full nonlinear dynamics. In two dimensions, an analogous discrepancy arises in the particle velocity autocorrelation function, which decays more slowly in the correlated linear Stokes case than in the correlated nonlinear Navier–Stokes case. In both settings, spatial correlations inhibit viscous momentum
diffusion at small scales, leading to prolonged relaxation under the linear dynamics, whereas nonlinear mode coupling accelerates small-scale relaxation. Thus, the interplay between nonlinear coupling and viscous damping becomes scale dependent, invalidating the use of a single global Reynolds number. Taken together, these findings show that, for spatially correlated fluctuating fluids, the effective Reynolds number must be reinterpreted as a scale-dependent quantity.
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Optics
Generalized Thermodynamics of Solitonic Event Horizons in Dispersive Field Theories
Hasan Oguz
The realization of Hawking radiation in optical analogs has historically focused on kinematic observables, such as the effective temperature determined by the horizon's surface
gravity. A complete thermodynamic description, however, necessitates a rigorous definition of
entropy and irreversibility, which has remained elusive in
Hamiltonian optical systems. In this work, we bridge this gap by introducing an operational
entropy for solitonic event horizons, derived from the spectral partitioning of the optical field into coherent solitonic and incoherent radiative subsystems. The emission of resonant radiation, driven by the breaking of
soliton integrability under higher-order dispersion, is the fundamental mechanism for
entropy production. Numerical simulations of the generalized nonlinear Schrödinger equation (GNLSE) demonstrate that, in a coarse-grained sense, this process obeys a generalized second law (GSL), $\Delta S_{\mathrm{tot}} \ge 0$, robustly across a wide range of
soliton orders and dispersion strengths. These results show that event horizons in dispersive field theories behave as consistent nonequilibrium thermodynamic systems, and that the relevant
entropy is accessible from laboratory spectral measurements.
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Plasma Physics
Machine learning for radiative hydrodynamics in astrophysics
Gonzague Radureau
Radiation hydrodynamics describes the interaction between high-temperature hypersonic
plasmas and the radiation they emit or absorb, a coupling that plays a central role in many astrophysical phenomena related to
accretion and ejection processes. The HADES code was developed to model such systems by coupling hydrodynamics with M1-gray or M1-multigroup radiative transfer models, which are well suited to optically intermediate media. Despite its accuracy, radiation hydrodynamics simulations remain extremely demanding in terms of computational cost. Two main limitations are responsible for this. First, the M1-multigroup model relies on a closure relation with no analytic expression, requiring expensive numerical evaluations. Second, the Courant-Friedrichs-Lewy condition strongly restricts the time step of the explicit schemes used in HADES. To overcome these difficulties, two complementary Artificial Intelligence based strategies were developed in this thesis. The first approach consists in training a Multi-Layer Perceptron to approximate the M1-multigroup closure relation. This method achieves excellent accuracy while reducing the computational cost by a factor of 3000, making it the most efficient approach currently available for this task. This performance gain enables high-fidelity simulations of radiative shocks, in which radiation directly influences the shock structure. In particular, increasing spectral resolution slows down the shock and enlarges the radiative precursor. The second approach explores the use of Physics-Informed Neural Networks to directly solve the radiation hydrodynamics equations and extrapolate simulations beyond their initial time range. Tests on purely hydrodynamic shocks show accurate handling of discontinuities, but application to radiative shocks remains challenging and requires further investigation.
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Computational Physics · Cross-listed from astro-ph.HE
Multigroup Radiation Diffusion on a Moving Mesh: Implementation in RICH and Application to Tidal Disruption Events
Itamar Giron, Menahem Krief, Nicholas C. Stone et al. (+1 more)
Radiation-hydrodynamics (RHD) determines the bulk
evolution and observable emission in a wide variety of high-energy astrophysical phenomena. Due to their complexity, RHD problems must usually be studied through numerical simulation. We have extended the publicly available RICH code, which previously solved the equations of RHD in the limit of grey flux-limited
diffusion (FLD), to operate with a multigroup FLD solver. RICH is a semi-Lagrangian code that solves the equations of RHD on an unstructured moving mesh, and is the first multigroup RHD moving mesh code, making it uniquely applicable to problems with extreme dynamic range and dynamically important radiation forces. We validate our multigroup module against multiple analytic
benchmarks, including a novel test of the RHD Doppler term. The computational efficiency of the code is aided by a novel scheme to accelerate convergence in optically thick
cells by limiting the absorption coefficients. Finally, we apply multigroup rich in a pilot three dimensional study of a
stellar tidal disruption event (TDE), using a $10^4 M_\odot$ intermediate-mass black hole. Our simulations self-consistently produce a bright early-time X-ray flash prior to peak optical/UV light, in qualitative agreement with post-processing of (grey) RICH simulations of supermassive black hole TDEs, as well as X-ray observations of the TDE AT 2022dsb.
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All authors Itamar Giron, Menahem Krief, Nicholas C. Stone, Elad Steinberg
Optics · Cross-listed from quant-ph
Scalable Generation of Macroscopic Fock States Exceeding 10,000 Photons
Ming Li, Weizhou Cai, Ziyue Hua et al. (+7 more)
The scalable preparation of bosonic
quantum states with macroscopic excitations poses a fundamental challenge in
quantum technologies, limited by control complexity and
photon-loss rates that severely constrain prior theoretical and experimental efforts to merely dozens of excitations per mode. Here, based on the duality of the
quantum state
evolution in Fock state space and the optical wave-function propagation in a waveguide array, we introduce a Kerr-engineered multi-lens protocol in a single bosonic mode to deterministically generate Fock states exceeding $10,000$
photons. By optimizing phase and displacement operations across lens groups, our approach compensates for non-paraxial aberrations, achieving fidelities above $73\%$ in numerical simulations for
photon numbers up to $N=100,000$. Counterintuitively, the protocol's execution time scales as $N^{-1/2}$ with the target
photon number $N$, exhibiting robustness against the
photon loss. Our framework enables exploration of
quantum-to-classical transitions of
giant Fock states, paving the way for advanced
quantum metrology with significant
quantum gains, and error-corrected
quantum information processing in high-dimensional
Hilbert spaces.
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All authors Ming Li, Weizhou Cai, Ziyue Hua, Yifang Xu, Yilong Zhou, Zi-Jie Chen, Xu-Bo Zou, Guang-Can Guo, Luyan Sun, Chang-Ling Zou
Fluid Dynamics
Divide and conquer complex flows. Part I: cluster and manifold-based local analysis
Qihong L. Li-Hu, Guy Y. Cornejo Maceda, Andrea Ianiro et al. (+1 more)
This work is a two-part study on the description and prediction of complex fluid flows through the partitioning of the flow domain. In this first part, we propose a framework for a global description of the dynamics of complex flows via clustered spatial representations of the flow, isolating and identifying local dynamics, retrieving different \acp{ST-CNM}. The key enabler is the partitioning of the domain based on a nonlinear
manifold learning approach, in which spatial points are clustered based on the similarity of their dynamics, as observed in their compact
embedding in
manifold coordinates. The method receives as input time-resolved flow fields. The spatial
manifold is computed through isometric mapping applied to the vorticity time histories at each spatial location. An unsupervised clustering method, applied in the
manifold space, partitions the full flow domain into subdomains. The dynamics of each subdomain are then described with cluster-based modelling. The method is demonstrated on two flow-field
datasets obtained with a direct numerical simulation of a fluidic pinball under periodic forcing and with two-dimensional particle image velocimetry measurements of a transitional jet flow. The spatial
manifold-based flow partitioning identifies regions with similar dynamics in an automated way. For both cases, \ac{ST-CNM} identifies local dynamics that are not captured by a global approach. In particular,
vortex shedding and
vortex pairing dynamics are isolated in the jet flow experiment. The proposed fully automated domain partitioning method will benefit the structural description of controlled flows and unveil the actuation mechanisms at play.
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All authors Qihong L. Li-Hu, Guy Y. Cornejo Maceda, Andrea Ianiro, Stefano Discetti
Instrumentation and Detectors
A gaseous-helium cooling system for silicon detectors in the Nab experiment
Love Richburg, Noah Birge, Nadia Fomin et al. (+40 more)
The Nab experiment aims to extract the
neutron beta decay correlation coefficients 'a' and 'b'. This will be accomplished using a 7 m tall electromagnetic spectrometer which measures electron energies and
proton momenta. Detection of electrons and
protons resulting from
neutron beta decay will be carried out using large-area, thick, highly-segmented, single-
crystal silicon detectors. These detectors and accompanying electronics will be cooled by a recirculating, gaseous helium cooling system to below 150 K with +/- 0.5 K stability. We will motivate the need for detector cooling in the Nab experiment and discuss design and performance of this cooling system.
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All authors Love Richburg, Noah Birge, Nadia Fomin, Grant Riley, Josh Pierce, John Ramsey, Wolfgang Schreyer, Seppo Penttila, Isaiah Wallace, Di'Arra Mostella, Aaron Jezghani, Alexander Saunders, Americo Salas Bacci, Ariella Atencio, August Mendelsohn, Austin Nelsen, Bryan Zeck, Christopher Crawford, Corey Gilbert, David Mathews, Deion Fellers, Duncan Fuehne, Erick Smith, Francisco Gonzalez, Glenn Randall, Himal Acharya, Huangxing Li, Hunter Presley, Jackie Mirabal, Jason Fry, Jin Ha Choi, Jordan O'Kronley, Josh Hamblen, Leah Broussard, Mark Makela, Nick Macsai, Pat McGaughey, Rebecca Godri, Ricardo Alarcon, Russell Mammei, Sean Hollander, Skylar Clymer, Zachary Garman
Optics
How Dark is Dark? A Reflectance and Scattering Analysis of Black Materials
Jiri Filip and Radomir Vavra
Black materials play a critical role in applications such as image registration, camera calibration, stray light suppression, and visual design. Although many such materials appear similarly dark under diffuse illumination, their reflectance behavior can differ substantially as a function of viewing and lighting geometry. Ultra-black materials achieve exceptional light attenuation but are often constrained by cost and mechanical fragility, motivating the evaluation of more robust and accessible alternatives. In this study, we employ a gonimetric measurement system to capture the isotropic bidirectional reflectance distribution function of a range of black materials, including the ultra-black reference Vantablack, commercially available alternatives such as Musou Black and black velvet, and standard matte black coatings. We analyze their reflectance characteristics in terms of diffuse and specular scattering, as well as total integrated scatter, to quantify angular-dependent reflection. In addition, we compare their perceptual appearance using physically based rendering driven by the measured BRDFs and a psychophysical evaluation of perceived darkness. Together, these analyses provide a comprehensive assessment of black materials that links reflectance properties to visual appearance and perceptual performance, enabling informed material selection for optical applications.
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Atmospheric and Oceanic Physics · Cross-listed from astro-ph.EP
Surveying exogenous species in Saturn with ALMA I. Detecting and Mapping CO
Deborah Bardet, Thierry Fouchet, Thibault Cavalié et al. (+5 more)
The origin of carbon monoxide (CO) in Saturn's stratosphere remains uncertain, with proposed sources including internal thermochemical production, cometary impacts, and exogenic material from the rings and icy moons (i.e. Enceladus). We aim to constrain the vertical and meridional distribution of stratospheric CO and assess the relative contributions of these potential sources. Here, we analysed high-spectral-resolution ALMA observations of the CO (J=3-2) line obtained on 25 May 2018, sampling Saturn's limb from 20{\deg}S to 69{\deg}N. CO vertical profiles were retrieved using a line-by-line radiative transfer model combined with spectral inversion techniques, testing multiple prior scenarios representative of different source hypotheses. CO is confined to a narrow layer between 0.1 and 1 mbar, with a robust negative vertical gradient and mean abundances of (3.7+/- 0.8) x 10$^{-8}$ at 0.1 mbar and (7.2 +/- 0.9) x 10$^{-8}$ at 1 mbar. The meridional distribution is statistically homogeneous, with a marginal enhancement near 60{\deg} N plausibly related to Enceladus. No significant equatorial enhancement is detected. The absence of a strong equatorial enhancement rules out a long-lived steady source associated with ring infall. The observations are most consistent with a relatively recent ($\approx$200-year-old or younger) cometary impact whose material has since been horizontally mixed, while any Cassini Grand Finale ring influx was either too recent or inefficient to affect CO abundances at the probed pressure levels.
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All authors Deborah Bardet, Thierry Fouchet, Thibault Cavalié, Raphaël Moreno, Emmanuel Lellouch, Camille Lefour, Bilal Benmahi, Sandrine Guerlet
Chemical Physics
DMRG/FQ: a Polarizable Embedding Approach Combining Density Matrix Renormalization Group and Fluctuating Charges
Matteo Rinaldi, Chiara Sepali, Alicia Marie Kirk et al. (+2 more)
We present an integrated multiscale framework that combines the Density
Matrix Renormalization Group (DMRG) with a polarizable fluctuating-charge (FQ) force field for the simulation of electronic excited states in solution. The method exploits the capabilities of DMRG to accurately describe systems with strong static correlation, while the FQ model provides a self-consistent and physically grounded representation of solvent polarization within a QM/MM
embedding. The DMRG/FQ approach is applied to representative solvated systems, using extensive molecular dynamics sampling. The method yields reliable excitation energies, solvatochromic shifts, and a close agreement with available experimental data. The results highlight the importance of mutual polarization for capturing specific solute-solvent interactions, particularly in systems where hydrogen bonding or directional interactions play a dominant role.
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All authors Matteo Rinaldi, Chiara Sepali, Alicia Marie Kirk, Claudio Amovilli, Chiara Cappelli
Physics and Society · Cross-listed from cs.SI
Graph energy as a measure of community detectability in networks
Lucas Böttcher, Mason A. Porter and Santo Fortunato
A key challenge in network science is the detection of communities, which are sets of nodes in a network that are densely connected internally but sparsely connected to the rest of the network. A fundamental result in community detection is the existence of a nontrivial threshold for community detectability on sparse graphs that are generated by the planted partition model (PPM). Below this so-called “detectability limit”, no community-detection method can perform better than random chance. Spectral methods for community detection fail before this detectability limit because the
eigenvalues corresponding to the eigenvectors that are relevant for community detection can be absorbed by the bulk of the spectrum. One can bypass the detectability problem by using special
matrices, like the non-backtracking
matrix, but this requires one to consider higher-dimensional
matrices. In this paper, we show that the difference in graph energy between a PPM and an Erdős–Rényi (ER) network has a distinct transition at the detectability threshold even for the adjacency
matrices of the underlying networks. The graph energy is based on the full spectrum of an adjacency
matrix, so our result suggests that standard graph
matrices still allow one to separate the parameter regions with detectable and undetectable communities.
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Medical Physics
Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: applications to a large-scale, clinically heterogeneous dataset
Jelmer van Lune, Stefano Mandija, Oscar van der Heide et al. (+5 more)
Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily dependent on scanner hardware and acquisition settings. While quantitative MRI (qMRI) offers intrinsic tissue parameters, the requirement for specialized acquisition protocols and reconstruction
algorithms restricts its availability and impedes large-scale biomarker research. This study presents a self-supervised physics-guided deep learning framework to infer quantitative T1, T2, and
proton-density (PD) maps directly from widely available clinical conventional T1-weighted, T2-weighted, and FLAIR MRIs. The framework was trained and evaluated on a large-scale, clinically heterogeneous
dataset comprising 4,121 scan sessions acquired at our institution over six years on four different 3 T MRI scanner systems, capturing real-world clinical variability. The framework integrates Bloch-based signal models directly into the training objective. Across more than 600 test sessions, the generated maps exhibited white matter and gray matter values consistent with literature ranges. Additionally, the generated maps showed invariance to scanner hardware and acquisition protocol groups, with inter-group coefficients of variation $\leq$ 1.1%. Subject-specific analyses demonstrated excellent voxel-wise reproducibility across scanner systems and sequence parameters, with Pearson $r$ and concordance correlation coefficients exceeding 0.82 for T1 and T2. Mean relative voxel-wise differences were low across all quantitative parameters, especially for T2 ($<$ 6%). These results indicate that the proposed framework can robustly transform diverse clinical conventional MRI data into quantitative maps, potentially paving the way for large-scale quantitative biomarker research.
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All authors Jelmer van Lune, Stefano Mandija, Oscar van der Heide, Matteo Maspero, Martin B. Schilder, Jan Willem Dankbaar, Cornelis A.T. van den Berg, Alessandro Sbrizzi
Medical Physics
Dosimetric Impact of Hidden Input Parameters in Inverse Optimization Algorithms for GYN HDR Brachytherapy
YeongHyeon Park, Shiqin Su, Sarath Vijayan et al. (+3 more)
Inverse optimization (IO)
algorithms are used in GYN HDR brachytherapy planning, with user parameter settings embedded in commercial TPS. To examine the dosimetric influence of hidden input parameters in three IO
algorithms-IPSA, HIPO, and MCO-for GYN HDR brachytherapy across two applicator types. In-house implementations of IPSA, HIPO, and MCO were implemented and evaluated against retrospectively generated commercial TPS plans (Oncentra Brachy) using identical clinical input parameters across 24 cervical cancer cases (18 T&O; 6 T&O+Needles (T&O+N)). Each IO
algorithm was assessed using 1k combinations of hidden parameters (e.g., dwell-time modulation constraints, convergence thresholds). Cumulative DVH curves and dosimetric indices (HR-CTV D98/D90, OAR D2cc) were compared with commercial plans. Standard deviations (SD) of DVH differences were used to characterize sensitivity to hidden parameters. For HR-CTV, SD values in T&O+N cases reached 23.0 Gy and 7.1 Gy for MCO and HIPO, respectively, with corresponding average values of 55.8 Gy and 19.7 Gy. In T&O cases, HR-CTV SD values reached 4.9 Gy and 3.3 Gy for HIPO and IPSA, respectively, with average values of 20.1 Gy and 8.6 Gy. MCO exhibited the highest sensitivity, followed by HIPO and IPSA. T&O+N cases showed greater sensitivity than T&O cases. Absolute differences in HR-CTV D90 (D98) relative to commercial
algorithms reached up to 33.3 Gy (28.4) for T&O+N cases and 10.8 Gy (8.5) for T&O cases. For OARs, absolute D2cc differences in T&O+N (T&O) cases reached up to 8.6 Gy (2.3) for rectum, 17 Gy (10.2) for bladder, 14.8 Gy (3.9) for sigmoid, and 7.0 Gy (8.1) for bowel. Hidden input parameter settings significantly impact on GYN HDR plans, with target coverage up to 28.4 Gy across IO
algorithms for both T&O and T&O+N cases. The findings in this study shown the potential to improve plans through hidden input parameter optimization.
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All authors YeongHyeon Park, Shiqin Su, Sarath Vijayan, Zhiqian Henry Yu, Mandy Cunningham, Yusung Kim
Fluid Dynamics
PINN-Based Solution for a Diffusion Controlled Droplet Growth
Pavel Gol'din and Gennady Y. Gor
We study
diffusion-controlled growth of a spherical droplet with a moving boundary using a physics-informed neural network (PINN) formulation. The governing
diffusion equation is coupled to the interfacial mass balance, with the droplet radius treated as an additional trainable function of time. The PINN accurately reproduces the self-similar growth law and concentration profiles for a wide range of initial droplet radii, demonstrating convergence toward the asymptotic diffusive regime. The proposed approach provides a flexible and computationally efficient framework for solving moving-boundary
diffusion problems and can be readily extended to include additional physical effects.
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Fluid Dynamics
Deformable bodies in a 3-dimensional viscous flow: Vorticity-Stream vector formulation
Andreu F. Gallen, Joan Muñoz Biosca, Mario Castro et al. (+1 more)
When simulating three-dimensional flows interacting with deformable and elastic obstacles, current methods often encounter complexities in the governing equations and challenges in numerical implementation. In this work, we introduce a novel numerical formulation for simulating incompressible viscous flows at low Reynolds numbers in the presence of deformable interfaces. Our method employs a vorticity-stream vector formulation that significantly simplifies the fluid solver, transforming it into a set of coupled Poisson problems. The body-fluid interface is modeled using a phase field, allowing for the incorporation of various free-energy models to account for membrane bending and surface tension. In contrast to existing three-dimensional approaches, such as
Lattice Boltzmann Methods or boundary-integral techniques, our formulation is lightweight and grounded in classical fluid mechanics principles, making it implementable with standard finite-difference techniques. We demonstrate the capabilities of our method by simulating the
evolution of a single vesicle or droplet in Newtonian Poiseuille and Couette flows under different free-energy models, successfully recovering canonical axisymmetric shapes and stress profiles. Although this work primarily focuses on single-body dynamics in Newtonian suspending fluids, the framework can be extended to include body forces, inertial effects, and viscoelastic media.
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All authors Andreu F. Gallen, Joan Muñoz Biosca, Mario Castro, Aurora Hernández-Machado
Biological Physics
Geometric developmental principles for the emergence of brain-like weighted and directed neuronal networks
Aitor Morales-Gregorio, Anno C. Kurth and Karolína Korvasová
Brain networks exhibit remarkable structural properties, including high local clustering, short path lengths, and heavy-tailed weight and degree distributions. While these features are thought to enable efficient information processing with minimal wiring costs, the fundamental principles that generate such complex network architectures across species remain unclear. Here, we analyse single-
neuron resolution connectomes across five species (C. Elegans, Platynereis, Drosophila M., zebrafish and mouse) to investigate the fundamental wiring principles underlying
brain network formation. We show that distance-dependent connectivity alone produces small-world networks, but fails to generate heavy-tailed distributions. By incorporating weight-preferential attachment, which arises from spatial clustering of synapses along neurites, we reproduce heavy-tailed weight distributions while maintaining small-world
topology. Adding degree-preferential attachment, linked to the extent of dendritic and axonal arborization, enables the generation of heavy-tailed degree distributions. Through systematic parameter exploration, we demonstrate that the combination of distance dependence, weight-preferential attachment, and degree-preferential attachment is sufficient to reproduce all characteristic properties of empirical
brain networks. Our results reveal that activity-independent
geometric constraints during neural development can account for the conserved architectural principles observed across evolutionarily distant species, suggesting universal mechanisms governing neural
circuit assembly.
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Fluid Dynamics
Supersonic jet dynamics from two-cavitation-bubble interactions: acceleration, tip fragmentation and penetration
Shuai Yan, A-Man Zhang, Tianyuan Zhang et al. (+3 more)
This study experimentally and numerically investigates the dynamics of a high-speed
liquid jet generated from the interaction of two tandem cavitation bubbles, termed bubble 1 and bubble 2, depending on their generation sequence. In our experiments, two near-identical, highly-energized cavitation bubbles were generated using an
underwater electric discharge method, and their transient interactions were captured using a high-speed camera. We identify three distinct jet regimes that emerge from the tip of bubble 2: conical, umbrella-shaped, and spraying jets, characterized by variations in the initial bubble-bubble distance and the initiation time difference. Our numerical simulations using both Volume of Fluid and Boundary Integral methods reproduce the experimental observations quite well and explain the mechanism of jet acceleration. We show that the transition between the regimes is governed by the spatiotemporal characteristics of the pressure wave induced by the collapse of bubble 1, which impacts the high-
curvature tip of bubble 2. Specifically, a conical jet forms when the pressure wave impacts the bubble tip prior to its contraction, while an umbrella-shaped jet develops when this impact occurs after the contraction. The spraying jets result from the breakup of the bubble tip, exhibiting mist-like and needle-like morphologies with velocities ranging from 10 to over 1200 m/s. Remarkably, we observe that the penetration distance of spraying jets exceeds ten times the maximum bubble radius, making them ideal for long-range, controlled fluid delivery. Finally, phase diagrams for jet velocity and penetration distance in the $\gamma-\theta$ parameter space are established to provide a practical reference for biomedical applications, such as needle-free injection and micro-pumping.
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All authors Shuai Yan, A-Man Zhang, Tianyuan Zhang, Pu Cui, Rui Han, Shuai Li
Optics
Modulating near-field radiative energy and momentum transfer via rotating Weyl semimetals
Huimin Zhu, Gaomin Tang, Lei Zhang et al. (+1 more)
We study near-field radiative transfer of energy, angular momentum, and linear momentum between a nanoparticle and a plate consisting of
magnetic Weyl semimetals, and demonstrate that these can be efficiently tuned by a relative angle between the Weyl node separations. This tunability originates from the coupling between the particle-induced rotational Poynting vector and the nonreciprocal surface plasmon polaritons supported by the plate. Remarkably, we uncover a counterintuitive regime in which both energy and angular momentum transfer are maximized when the Weyl node separations are antiparallel rather than parallel. This arises from optimal mode matching between the rotation direction of the particle's circular heat flux and the propagation direction of the surface plasmon polaritons in the antiparallel configuration.
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All authors Huimin Zhu, Gaomin Tang, Lei Zhang, Jun Chen
Accelerator Physics
High Intensity for Accelerator Driven Systems (ADS)
Ulrich Dorda
Following the motivation for an Accelerator Driven System (ADS), the requirements on the accelerator are derived. Using the MYRRHA project as example, the beam optics/dynamics design and operational concept of such an accelerator are discussed and the main technology choices and challenges are presented.
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Classical Physics
Scale effects methodology applied to uprising jets in ASTRID
B Jourdy, D Guenadou, N Seiler et al. (+2 more)
CEA is involved in the development of the 4 th generation of
nuclear reactors, among which are the Sodium Cooled Fast Reactors (SFR). To support their design and safety, specific codes were developed and should be validated using experimental results from relevant mock-ups. Due to the complexity of building a fullsized prototype in the
nuclear field, most of the experiments are performed on reduced-sized models but it may lead to scale effects. Such scale effects are under study in this paper, focusing on a critical issue in SFR reactor, which is the rising of the jet outgoing the core at low power. For this purpose, a scale effects methodology is detailed, using the SFR's reduced scale mock-up MICAS as the reference scale. To achieve that, dimensionless Navier-Stokes equations under Boussinesq's approximation are considered and the Vaschy-Buckingham
theorem is applied to determine the most relevant dimensionless numbers, among them the densimetric Froude number. Experimental campaigns have been performed to measure velocity fields using the Particle Image Velocimetry (PIV). Their analysis clearly shown dependency of mean pathway of the jet on this dimensionless number. Particularly, plotting the jet angle as a function of the normalized densimetric Froude number, a change of behaviour for a threshold value of 0.45 has been observed. This result also shown negligible effects on the jet rise happening before jet impingement on the Upper Core Structure (UCS).
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All authors B Jourdy, D Guenadou, N Seiler, A Labergue, M Gradeck
Classical Physics
CFD modeling of hydrogen release and dispersion in a congested container
Hector Amino, Lynda Porcheron, Jérôme Daubech et al. (+4 more)
Hydrogen plays an important role in driving decarbonization within the current global energy landscape. As hydrogen infrastructures rapidly expand beyond their traditional applications, there is a need for comprehensive safety practices, solutions, and regulations. Within this framework, the dispersion of hydrogen in enclosed facilities presents a significant safety concern due to its potential for explosive accidents. In this study, hydrogen dispersion in a confined and congested environment (37 m${}^3$ container) is studied using computational fluid dynamics simulations. The experimental setup mirrors previous INERIS investigations, featuring a centrally located hydrogen injection point on the floor with a 20 mm diameter injector and a release rate of 35 g/s, resulting in a Froude number of 650. This yields an inertial jet and a challenging dispersion scenario for numerical prediction. Concentration mapping is carried out by 3 oxygen analyzers distributed throughout the 37 m3 chamber. Comparisons are made between the measured and numerical data to validate the solver used under such conditions. Best practice guidelines are followed, and sensitivity studies involving grid refinement and boundary conditions are conducted to ensure robust simulation results. The findings highlight the model's ability to reproduce the hydrogen concentration distribution for both empty and congested containers and underline the role of accounting for leakages in such scenarios.
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All authors Hector Amino, Lynda Porcheron, Jérôme Daubech, Emilie Ricrot, Annabelle Brisse, Emmanuel Leprette, Olivier Hurisse
Plasma Physics
A Comprehensive multi-species comparison of rotational temperature probes in a DC Ar/N$_2$ micro-hollow cathode discharge
Dimitrios Stefas, Belkacem Menacer, Alice Remigy et al. (+4 more)
Accurate gas temperature ($T_{\rm Gas}$) determination in microplasmas is critical for optimizing their applications, yet isolated diagnostic approaches may yield misleading results, especially under strong non-
equilibrium conditions. Here, high resolution rotational spectra of N$_2$(C), OH(A), NH(A) and NO(A), generated in the
plasma jet of a DC Ar/N$_2$ microhollow cathode discharge (MHCD), are recorded and their associated rotational temperatures ($T_{\rm rot}$) are cross compared. A detailed experimental analysis and robust fitting of the rotational spectra are performed, achieving a reliable estimation of $T_{\rm Gas}$. The dominant formation mechanisms of these species and their corresponding impact on rotational population distributions are also interrogated. Particularly, our findings indicate that the $T_{\rm rot}$of N$_2$(C) is significantly influenced by energy transfers from argon metastables (Ar$^m$) and spectral interference from NH(A). This makes it unreliable as a thermometric probe in Ar-rich MHCD, unless complex analyses are employed. In contrast, OH(A) rotational population distribution appears to be less sensitive to Ar-induced perturbations across various discharge currents and pressures, providing more straightforward results. For all molecules considered, this study reveals the conditions under which all the measured $T_{\rm rot}$ can be reliably considered to be in
equilibrium with $T_{\rm Gas}$. This highlights the importance of crossvalidating multiple thermometric probes and investigating relevant excitation kinetics when measuring $T_{\rm rot}$ in reactive microplasmas.
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All authors Dimitrios Stefas, Belkacem Menacer, Alice Remigy, Nikolaos Chazapis, Guillaume Lombardi, Claudia Lazzaroni, Kristaq Gazeli