Plasma Physics
Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
Siqi Ding, Zitong Zhang, Guoyang Shi et al. (+7 more)
As artificial intelligence emerges as a transformative enabler for fusion energy commercialization, fast and accurate solvers become increasingly critical. In
magnetic confinement
nuclear fusion, rapid and accurate solution of the Grad-Shafranov equation (GSE) is essential for real-time
plasma control and analysis. Traditional numerical solvers achieve high precision but are computationally prohibitive, while data-driven surrogates infer quickly but fail to enforce physical laws and generalize poorly beyond training distributions. To address this challenge, we present a Physics-Informed Neural Operator (PINO) that directly learns the GSE solution operator, mapping shape parameters of last closed flux surface to
equilibrium solutions for realistic nonlinear current profiles. Comprehensive benchmarking of five neural architectures identifies the novel
Transformer-KAN (Kolmogorov-Arnold Network) Neural Operator (TKNO) as achieving highest accuracy (0.25% mean L2 relative error) under supervised training (only data-driven). However, all data-driven models exhibit large physics residuals, indicating poor physical consistency. Our unsupervised training can reduce the residuals by nearly four orders of magnitude through
embedding physics-based loss terms without labeled data. Critically, semi-supervised learning–integrating sparse labeled data (100 interior points) with physics constraints–achieves optimal balance: 0.48% interpolation error and the most robust extrapolation performance (4.76% error, 8.9x degradation factor vs 39.8x for supervised models). Accelerated by TensorRT optimization, our models enable millisecond-level inference, establishing PINO as a promising pathway for next-generation fusion control systems.
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All authors Siqi Ding, Zitong Zhang, Guoyang Shi, Xingyu Li, Xiang Gu, Yanan Xu, Huasheng Xie, Hanyue Zhao, Yuejiang Shi, Tianyuan Liu
Accelerator Physics
Fast Adaptive Neural Control of Resonant Extraction at Fermilab
A. Whitbeck, J. Berlioz, K. Danison-Fieldhouse et al. (+8 more)
We present progress on the development of a machine learning (ML) regulation system for third-order resonant extraction of the beam delivered to the Mu2e experiment at Fermilab. We consider classical and ML-based controllers optimized on semi-analytic simulations and provide performance comparisons for several models. Additionally, we discuss the efficiency of each model in training, which has implications for future work on adaptive control. We also discuss progress on developing optimized implementations of ML models for edge-based inference.
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All authors A. Whitbeck, J. Berlioz, K. Danison-Fieldhouse, K. Hazelwood, M. Khan, J. Mitrevski, A. Narayanan, J. St. John, N. Tran, J. Ji, M. Walter
Instrumentation and Detectors
Cryogenic characterization of FBK NUV-HD-Cryo 3T SiPM sensors for the DUNE photon detection system
F. Acerbi, M. Andreotti, A. Balboni et al. (+93 more)
The Deep Underground
Neutrino Experiment (DUNE) is a long-baseline
neutrino experiment based in the USA and composed of a Near Detector (ND) complex at
Fermi National Laboratory (FNAL), and a Far Detector (FD) complex located at the Sanford Underground Research Facility (SURF) $\sim$1300\,km distant. DUNE will study
neutrino oscillations looking for unresolved issues of the Standard Model of particle physics (SM) such as CP violation in the leptonic sector,
neutrino mass ordering and others, starting from the early 2030s. The FD, with a mass of $\sim$17\,kt, that will exploit both ionization and scintillation signals to detect
neutrino interactions with Argon. Scintillating
photons in LAr will be detected by the
photon detection system (PDS) based on light collectors coupled to Silicon Photomultipliers (SiPMs). During a test campaign, different laboratories of the collaboration performed an investigation of the best SiPM candidates that fulfill the DUNE FD requirements. We identified two models of SiPM, produced by Hamamatsu Photonics K.K. (HPK) and Fondazione Bruno Kessler (FBK), respectively. In this paper, we focus on the FBK selected model showing its main features. We will describe the characterization protocol, the results at both room and cryogenic temperatures and the
photon detection efficiency measurements.
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All authors F. Acerbi, M. Andreotti, A. Balboni, E. Bertolini, S. Bertolucci, G. Botogoske, F. Bramati, A. Branca, C. Brizzolari, G. Brunetti, R. Calabrese, E. Calvo, N. Canci, P. Carniti, D. Casazza, C. Cattadori, A. Cervera, F. Chiapponi, S. Chiozzi, V. Cicero, A. Cotta Ramusino, E. Cristaldo Morales, C. Cuesta, R. D Amico, L. Degli Esposti, M. Delgado Gonzalez, F. Di Capua, D. Di Ferdinando, A. Dyshkant, M. Eads, A. Falcone, E. Fialova, A. Ficorella, P. Filip, G. Fiorillo, M. Fiorini, K. Francis, A. Gabrielli, F. Galizzi, G. Gallina, D. Garcia-Gamez, M. A. Garcia-Peris, T. Giammaria, I. Gil-Botella, A. Gola, C. Gotti, M. Guarise, D. Guffanti, G. Ingratta, I. Lax, I. Lopez de Rego, E. Luppi, S. Manthey, J. Martin-Albo, N. Mauri, L. Meazza, A. Mengarelli, A. Minotti, E.Montagna, A. Montanari, I. Neri, F. J. Nicolas-Arnaldos, C. Palomares, L. Parellada-Monreal, L. Pasqualini, G. Paternoster, L. Perez-Molina, G. Pessina, V. Pia, L. Pierini, F. Poppi, M. Pozzato, M. Querol, F. Retiere, J. Rocabado, A. Ruggeri, A. Saadana, A. Sanchez-Castillo, P. Sanchez-Lucas, A. Scanu, F. S. Schifano, G. Sirri, J. Smolik, M. Tenti, F. Terranova, V. Togo, L. Tomassetti, M. Torti, N. Tosi, C. Valieri, A. Verdugo de Osa, H. Vieira de Souza, J. Zalesak, B. Zamorano, S. Zucchelli, V. Zutshi
Biological Physics · Cross-listed from q-bio.PE
Many-Eyes and Sentinels in Selfish and Cooperative Groups
Charlie Pilgrim, Andrew M Bate, Anna Sigalou et al. (+6 more)
Collective vigilance describes how animals in groups benefit from the predator detection efforts of others. Empirical observations typically find either a many-eyes strategy with all (or many) group members maintaining a low level of individual vigilance, or a sentinel strategy with one (or a few) individuals maintaining a high level of individual vigilance while others do not. With a general analytical treatment that makes minimal assumptions, we show that these two strategies are alternate solutions to the same adaptive problem of balancing the costs of predation and vigilance. Which strategy is preferred depends on how costs scale with the level of individual vigilance: many-eyes strategies are preferred where costs of vigilance rise gently at low levels but become steeper at higher levels (convex; e.g. an open field); sentinel strategies are preferred where costs of vigilance rise steeply at low levels and then flatten out (concave; e.g. environments with vantage points). This same dichotomy emerges whether individuals act selfishly to optimise their own fitness or cooperatively to optimise group fitness. The model is extended to explain discrete behavioural switching between strategies and differential levels of vigilance such as edge effects.
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All authors Charlie Pilgrim, Andrew M Bate, Anna Sigalou, Mélisande Aellen, Joe Morford, Elizabeth Warren, Christopher Krupenye, Dora Biro, Richard P Mann
Optics
High-precision luminescence cryothermometry strategy by using hyperfine structure
Marina N. Popova, Mosab Diab and Boris Z. Malkin
A novel, to the best of our knowledge, ultralow-temperature luminescence thermometry strategy is proposed, based on a measurement of relative intensities of hyperfine components in the spectra of Ho$^{3+}$ ions doped into a
crystal. A $^{7}$LiYF$_4$:Ho$^{3+}$
crystal is chosen as an example. First, we show that temperatures in the range 10-35 K can be measured using the Boltzmann behavior of the populations of
crystal-field levels separated by an energy interval of 23 cm$^{-1}$. Then we select the 6089 cm$^{-1}$ line of the holmium $^5I_5 \rightarrow ^5I_7$ transition, which has a well-resolved hyperfine structure and falls within the transparency window of optical fibers (telecommunication S band), to demonstrate the possibility of measuring temperatures below 3 K. The temperature $T$ is determined by a least-squares fit to the measured intensities of all eight hyperfine components using the dependence $I(\nu) = I_1 \exp(-b\nu)$, where $I_1$ and $b = a\nu + \frac{\nu}{kT}$ are fitting parameters and a accounts for intensity variations due to mixing of wave functions of different
crystal-field levels by the hyperfine interaction. In this method, the absolute and relative thermal sensitivities grow at $T$ approaching zero as $\frac{1}{T^2}$.and $\frac{1}{T}$, respectively. We theoretically considered the intensity distributions within hyperfine
manifolds and compared the results with experimental data. Application of the method to experimentally measured relative intensities of hyperfine components of the 6089 cm$^{-1}$ PL line yielded $T = 3.7 \pm 0.2$ K. For a temperature of 1 K, an order of magnitude better accuracy is expected.
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Instrumentation and Detectors
Simulating neutron diffraction from deformed mosaic crystals in McStas
Daniel Lomholt Christensen, Sandra Cabeza, Thilo Pirling et al. (+2 more)
Monochromator and analyzer systems that rely on bent single
crystals are in use throughout the
neutron scattering community. We here introduce a new component to the
neutron simulation software package McStas, that simulates these bent single
crystals. We then compare the performance of this component to like software in SIMRES, and Ncrystal. These simulations show excellent agreement across the different software programs. Finally we compare simulations of the new McStas component with analytical calculations of secondary extinction, based on the Darwin transfer equations. Here we also find excellent agreement, further validating this new component.
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All authors Daniel Lomholt Christensen, Sandra Cabeza, Thilo Pirling, Kim Lefmann, Jan Saroun
Optics
Experimental insights into data augmentation techniques for deep learning-based multimode fiber imaging: limitations and success
Jawaria Maqbool and M. Imran Cheema
Multimode fiber~(MMF) imaging using deep learning has high potential to produce compact, minimally invasive endoscopic systems. Nevertheless, it relies on large, diverse real-world medical data, whose availability is limited by
privacy concerns and practical challenges. Although data augmentation has been extensively studied in various other deep learning tasks, it has not been systematically explored for MMF imaging. This work provides the first in-depth experimental and computational study on the efficacy and limitations of augmentation techniques in this field. We demonstrate that standard image transformations and conditional generative
adversarial-based synthetic speckle generation fail to improve, or even deteriorate, reconstruction quality, as they neglect the complex modal interference and dispersion that results in speckle formation. To address this, we introduce a physical data augmentation method in which only organ images are digitally transformed, while their corresponding speckles are experimentally acquired via fiber. This approach preserves the physics of light-fiber interaction and enhances the reconstruction structural similarity index measure~(SSIM) by up to 17%, forming a viable system for reliable MMF imaging under limited data conditions.
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Computational Physics
Fast-Converging and Asymptotic-Preserving DSMC
Bin Hu, Liyan Luo, Kaiyuan Wang et al. (+1 more)
Improving the efficiency of the direct simulation Monte Carlo (DSMC) method has become increasingly urgent with the rapid development of space exploration. To address this issue, the direct intermittent general synthetic iteration (DIG) scheme has recently been proposed to enable DSMC's rapid and accurate convergence to steady-state solutions, even when the
cell size is much larger than the mean free path in near-continuum flow regimes. The first part of the paper is devoted to the mathematical analysis of DIG's fast-converging and asymptotic-preserving properties. Because the Boltzmann equation is analytically intractable, the analysis is conducted using the linearized BGK model. It is found that, in the near continuum flow regime, the DIG method asymptotically recovers the Navier Stokes equations when the
cell size is O(1), rather than being constrained by the mean free path. Moreover, after a single cycle of DIG
evolution, the deviation from the final steady state solution is reduced by more than a factor of five. In the second part of the paper, the Poiseuille flow and hypersonic flow passing over cylinder are investigated using the DIG scheme, with different time step and
cell sizes, thereby demonstrating its efficiency and accuracy in multiscale flow simulation. Specifically, when the Knudsen number is 0.01, the DIG method is found to be faster than the traditional DSMC method by two orders of magnitude. The performance gain becomes even greater at smaller Knudsen numbers. The proposed method holds great potential for engineering applications.
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All authors Bin Hu, Liyan Luo, Kaiyuan Wang, Lei Wu
Fluid Dynamics
Latent-Space Non-Linear Model Predictive Control for Partially-Observable Systems
Luigi Marra, Onofrio Semeraro, Lionel Mathelin et al. (+2 more)
This work presents a scalable control framework based on nonlinear Model Predictive Control for high-dimensional dynamical systems. The proposed approach addresses the key challenges of model scalability and partial observability by integrating data-driven reduced order modelling, control in a latent space, and state estimation within a unified formulation. A predictive model is constructed via Operator Inference on a Proper Orthogonal Decomposition basis, yielding a compact latent representation that captures the dominant system dynamics. State estimation is achieved through an Unscented Kalman Filter, which reconstructs the latent space from sparse and noisy measurements, enabling closed-loop control. The input signals are computed directly in the reduced-order latent space, improving computational efficiency with negligible impact on predictive capability. The methodology is validated on the one- and two-dimensional Kuramoto–Sivashinsky equations, serving as
benchmarks for chaotic and spatially-extended systems. Numerical experiments demonstrate that the proposed framework achieves accurate stabilisation. Overall, the framework provides a practical approach for nonlinear control of complex, high-dimensional systems where full-state measurements are often inaccessible or infeasible.
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All authors Luigi Marra, Onofrio Semeraro, Lionel Mathelin, Andrea Meilán-Vila, Stefano Discetti
Physics and Society
Trade-Off Between Multiplicity and Specificity in the Inter-layer Connectivity of non-identical Multilayer Networks
Aradhana Singh, Amod Rai, Sheksha Dudekula et al. (+2 more)
We study the coupled dynamics of multilayer networks with symmetric (MLs) and asymmetric (MLas) inter-layer connections. The symmetric inter-layer connections arise from a one-to-one correspondence between the nodes of different layers. In contrast, asymmetry results from the multiplicity of inter-layer connections, achieved by randomizing the links while preserving their overall density, thereby allowing one-to-many inter-layer connections. We investigate how different types of inter-layer coupling impact the dynamics of non-identical multilayer networks. We find that the specificity of one-to-one inter-layer connections facilitates intra-layer synchronization (ILS). In contrast, for networks with random inter-layer connectivity, ILS depends on how randomness affects intra-layer homomorphism (the set of permutations that preserve the network structure). Furthermore, amplitude death (AD) in MLs is observed at lower connectivity strength and frequency mismatch than the MLas. Moreover, AD in MLs depends on the density and
topology, but does not depend on the size of the networks. On the other hand, AD in MLas is influenced by network size in addition to density,
topology, and inter-layer mismatches. Moreover, both the MLs and MLas exhibit multi-stability, with the faster layer exhibiting a remanent periodic phase-locked oscillation, irrespective of the
topology and inter-layer connectivity. In addition, remnant synchrony between nodes with homomorphic relationships is observed in the slower layer. Overall, we propose that symmetric inter-layer connections should be preferable for achieving intra-layer synchronization-regardless of global synchronization-and for sustaining permanent
memory in multilayer networks with mismatched nodes across layers. However, to mitigate AD at low coupling values and layer mismatch, asymmetric inter-layer connectivity is more advantageous.
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All authors Aradhana Singh, Amod Rai, Sheksha Dudekula, Devanarayanan P, Antonio Palacios
Plasma Physics
Bell Plesset Effects on Rayleigh Taylor Instability of Three Dimensional Spherical Geometry
Xilai Li, Yilin Wu, Zhengnuo Chen et al. (+2 more)
We develop a weakly nonlinear, multi-mode theory for the Rayleigh-Taylor instability (RTI) on a time-varying spherical interface, fully incorporating mode couplings and the Bell-Plesset (BP) effects arising from interface convergence. Our model extends prior analyses, which have been largely restricted to static backgrounds, 2D cylindrical geometries, or single-mode initial condition. We present a framework capable of evolving arbitrary, fully three-dimensional initial perturbations on a dynamic background. At the first order, mode amplitudes respond to the time-varying interface acceleration with an exponential-like growth, in qualitative agreement with classic static results. At second order, nonlinear mode coupling reveals a powerful selection rule: energy is preferentially channeled into axisymmetric (m=0) modes. We find that the BP effects dramatically amplify the instability growth by a few orders of magnitude, with this amplification being even more significant for second order couplings. Despite this strong channeling, the second order amplitudes remain small relative to the first order, validating the perturbative approach. These findings offer new physical insights into time-dependent interface instabilities relevant to applications such as astrophysical shell collapse and inertial confinement fusion, highlighting the uniquely dominant role of axisymmetric modes in BP-driven convergent flows.
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All authors Xilai Li, Yilin Wu, Zhengnuo Chen, Mengqi Yang, Jie Zhang
Physics and Society
Arriving Young, Leaving Old(er): Age-Structured International Migration on Subnational Scale in Austria
Carsten Källner, Ola Ali, Andrea Vismara et al. (+2 more)
Modelling migration is complicated, as people move for many reasons. Some leave their country for the first time, others return to places they once called home, or move on to new destinations. However, most models focus only on who arrives, missing the full picture of how migrant populations evolve. We introduce a model for diaspora flows that estimates both arrivals and exits using daily migration flow rates, disaggregated by age and nationality. Drawing on high-resolution administrative data from Austria covering over 1.8 million foreign nationals, the model allocates these movements across more than 2,000 municipalities based on the size of local diaspora communities. We find that exits are not exceptions but a consistent and predictable feature across all groups. Migration rejuvenates Austria's population, as both arriving and departing migrants are younger than the average resident. This effect has distinct age-geography patterns: younger migrants are drawn to cities, while older migrants are more evenly distributed in the country. By capturing both arrivals and exits simultaneously, our approach provides a more comprehensive and interpretable picture of migration dynamics, how populations change over time, and how they are influenced by space, age, and national origins.
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All authors Carsten Källner, Ola Ali, Andrea Vismara, Guillermo Prieto-Viertel, Rafael Prieto-Curiel
Chemical Physics
CHAOS – A Consistent Large-scale Database for Sigma-Profiles and Other Molecular Descriptors
Dominik Gond, Justus Arweiler, Thomas Specht et al. (+2 more)
Sigma-profiles obtained from
quantum-chemical calculations are key molecular descriptors for solvent selection, thermodynamic modeling, and data-driven molecular design. However, existing sigma-profile libraries are limited in size and inconsistent in quality, which restricts their utility. In this work, we introduce CHAOS (Computed High-Accuracy Observables and Sigma Profiles), a large-scale and internally consistent database providing sigma-profiles for 53091 molecules, along with additional
quantum-chemical observables including gas-phase geometries, single-point conductor-like polarizable continuum (C-PCM) data, infrared spectra, ideal-gas heat capacities and
entropies, and atomic orbital
nuclear magnetic resonance (NMR) shielding tensors. All data were generated using a standardized
quantum-chemical workflow based on an wB97X-D/def2-TZVP level of theory. The CHAOS database covers molecules composed of a diverse set of elements, with molecular masses up to 400 amu and dipole moments up to 15 D, and is freely available on Zenodo under an open license. It extends the number of molecules for which sigma-profiles are publicly available by more than an order of magnitude and systematically links them to a broad range of other
quantum-chemical molecular descriptors. CHAOS provides a comprehensive and consistent foundation for developing models of molecular and thermodynamic properties – both physics-based and machine-learning approaches – across chemistry, chemical engineering, and materials science, greatly extending the possibilities and the available
quantum-chemical data basis.
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All authors Dominik Gond, Justus Arweiler, Thomas Specht, Hans Hasse, Fabian Jirasek
Chemical Physics
Tuning Domain-Based Charge Transfer in Organic Dyes: Impact of Heteroatom Doping on the $\pi$-Linker of Carbazole-Based Systems
Ram Dhari Pandey, Marta Galynska, Katharina Boguslawski et al. (+1 more)
This work presents an innovative computational study of domain-based charge transfer that leverages the localized orbitals of pair coupled cluster doubles (pCCD). This method enables both directional monitoring and quantitative assessment of charge transfer among donor (D), bridge (B), and acceptor (A) moieties. We applied this approach to a series of newly designed carbazole-based prototypical organic dyes, doping the bridge at positions 1, 2, and 3 with nitrogen, oxygen, and sulfur atoms to generate mono-, di-, and tri-doped variants. Our results demonstrate a clear and progressive enhancement in charge transfer as the degree of nitrogen or oxygen doping increases from mono- to di- to tri-doped systems. For mono-doped dyes, the highest forward charge transfer from donor to bridge to acceptor (D$\xrightarrow{}$B$\xrightarrow{}$A) occurs when a heteroatom (N or O) is placed in the terminal ring of the bridge, closer to the acceptor. In di-doped dyes, the largest forward charge transfer is observed when heteroatoms occupy both terminal positions, with one atom (N or S) adjacent to the donor and the other (N) near the acceptor. Nitrogen-doped systems consistently outperform their oxygen and sulfur counterparts. Among all variants, the organic dye doped with three nitrogen atoms at the bridge exhibits the most efficient and highest directional donor-to-acceptor charge transfer (42.6%), making it the most promising candidate for potential applications in dye-sensitized
solar cells. Finally, our calculations predict weak charge separation in all systems, indicating that charge transfer predominantly occurs from the bridge to the acceptor.
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All authors Ram Dhari Pandey, Marta Galynska, Katharina Boguslawski, Pawel Tecmer
Optics
MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design
S. Rodionov, A. Burguete-Lopez, M. Makarenko et al. (+3 more)
Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains for a broad range of applications. However, the lack of large and diverse
datasets limits the development of FM in nanophotonics. This work presents MOCLIP (Metasurface Optics Contrastive Learning Pretrained), a nanophotonic foundation model that integrates metasurface geometry and spectra within a shared latent space. MOCLIP employs contrastive learning to align geometry and spectral representations using an experimentally acquired
dataset with a sample density comparable to ImageNet-1K. The study demonstrates MOCLIP inverse design capabilities for high-throughput zero-shot prediction at a rate of 0.2 million samples per second, enabling the design of a full 4-inch wafer populated with high-density metasurfaces in minutes. It also shows generative latent-space optimization reaching 97 percent accuracy. Finally, we introduce an optical information storage concept that uses MOCLIP to achieve a density of 0.1 Gbit per square millimeter at the resolution limit, exceeding commercial optical media by a factor of six. These results position MOCLIP as a scalable and versatile platform for next-generation photonic design and data-driven applications.
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All authors S. Rodionov, A. Burguete-Lopez, M. Makarenko, Q. Wang, F. Getman, A. Fratalocchi
Fluid Dynamics · Cross-listed from math.AP
Self-Similar Radially Symmetric Solutions of the Relativistic Euler Equations with Synge Energy
Tommaso Ruggeri, Ferdinand Thein and Qinghua Xiao
We consider self-similar, radially symmetric solutions of the relativistic Euler equations with constitutive relations from relativistic kinetic theory, based on Synge energies for monatomic and its extension to diatomic gases. For the corresponding initial–boundary value problem, including the spherical piston problem, we prove existence and uniqueness of solutions valid for all values of the relativistic parameter $\gamma = mc^{2}/(k_{B}T)$, thus covering both the classical limit $(\gamma \to \infty)$ and the ultra-relativistic regime $(\gamma \to 0)$. We further establish key structural properties of Synge energies, showing the strict negativity of the second derivative with respect to pressure at constant
entropy and the monotone dependence of the characteristic velocity on $\gamma$. These results extend the classical theory of self-similar flows to the relativistic framework with kinetic-theory-based constitutive equations.
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Applied Physics
A silicon-based device for dynamic control of thermal emission
Sid Assawaworrarit, Alex Song and Shanhui Fan
Control of thermal emission is important in a number of applications from thermal energy harvesting and management and sensing of gas and chemical to thermal camouflage.
Semiconductor-based devices can be engineered to enable electrical control of thermal emission, offering high modulation speed and ease of voltage control. Existing device designs for modulating thermal emission rely on
semiconductors other than silicon, such as III-V and II-VI compounds, which are expensive. The silicon platform offers several advantages, including significantly lower cost, CMOS compatibility, and mature fabrication processes. However, a silicon-based design for modulating thermal emission remains absent. Here, we present an all-silicon device utilising electrical control over carrier dynamics to modulate a narrowband thermal emission in the mid-infrared region. We design a silicon device exhibiting voltage-controlled narrowband thermal emission at 10 {\mu}m and confirm its performance using electromagnetic calculations. This work paves the way for scalable, low-cost, and integrated thermal emission devices made possible by the silicon platform.
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Plasma Physics
Ion Temperature Anisotropy Limits from Magnetic Curvature Scattering in Magnetotail Reconnection Jets
Louis Richard, Anton V. Artemyev, Cecilia Norgren et al. (+3 more)
In collisionless
plasmas, relaxation of the deviations of ion velocity distribution functions (VDFs) from local thermodynamic
equilibrium occurs through particle interactions with electromagnetic fields. In particular, in the Earth's magnetotail, the deviations of the ion VDFs, typically consisting of multiple components, from the
equilibrium must be limited to maintain stability of the current sheet.
Curvature scattering is a leading candidate mechanism to limit such deviations, but its role remains insufficiently understood. We investigate the limits of ion temperature anisotropy in a magnetotail-like configuration by modeling a quasi-1D current sheet with a finite
magnetic field
curvature and three ion populations. We derive analytical thresholds for anisotropy based on current sheet stability and validate against spacecraft observations and numerical simulations. Our findings demonstrate that
curvature scattering imposes limits on ion anisotropies, thereby maintaining the stability of the current sheet.
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All authors Louis Richard, Anton V. Artemyev, Cecilia Norgren, Xin An, Sergey R. Kamaletdinov, Yuri V. Khotyaintsev
Geophysics · Cross-listed from astro-ph.EP
On the weak synchronization of a nonlinear solar dynamo oscillator by coherent planetary timing
Jean-Louis Le Mouël, Vincent Courtillot, Vladimir Kossobokov et al. (+4 more)
The
solar cycle is commonly interpreted as an internally generated
magnetic oscillation, yet its phase stability and long-term amplitude modulation remain difficult to explain through autonomous dynamo physics alone. We test the narrower hypothesis that the
solar dynamo behaves as a self-excited nonlinear oscillator whose phase and envelope may be weakly modulated by coherent astronomical timing. Using historical sunspot numbers, terrestrial length-of-day records, and ephemeris-based planetary descriptors, we identify shared long-period pseudo-cycles across
solar, geophysical, and astronomical observables. Singular Spectrum Analysis is used only as a non-parametric decomposition method. We then drive a reduced nonlinear $\alpha$–$\Omega$ oscillator with prescribed planetary timing signals.
Solar barycentric angular momentum is treated as a mechanically defined ephemeris descriptor, whereas summed planetary right ascension is retained solely as an empirical geometrical phase proxy. We also introduce the physical planetary quadrupolar
tidal tensor and use its equatorial off-diagonal component, $2T_{xy}$, as an independent timing descriptor. Forcing by normalized $2T_{xy}$ yields synchronization comparable to, and slightly better than, right ascension: $r=0.660$ and $\mathrm{RMSE}*{z}=0.824$, versus $r=0.655$ and $\mathrm{RMSE}*{z}=0.831$. Planetary forcing is not proposed to power or replace the internal dynamo, but only to provide weak timing. A possible relay involves planetary tides, tachocline magneto-Rossby dynamics, and nonlinear dynamo response. These results do not establish a complete coupling mechanism, but support the possibility that the
solar cycle is susceptible to weak astronomical synchronization.
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All authors Jean-Louis Le Mouël, Vincent Courtillot, Vladimir Kossobokov, Dominique Gibert, Fernando Lopes, Jean-Baptiste Boulé, Pierpaolo Zuddas
Medical Physics
Measuring thermal contact resistances between metallic rods using laser spot heating and infrared thermography. Part 1
Thomas Lahens, Alain Sommier, Marie-Marthe Groz et al. (+1 more)
Estimation of thermal contact resistances between cylinders can be achieved using heating on the cross sections by a
laser spot and measurement of the temperature response by IR thermography. This type of measurement makes it possible to characterise contacts in clusters of cylinders to simulate clusters of grains, or the properties of fibrous media in the transverse direction or, under certain conditions, to detect emerging thermal resistances (cracks perpendicular to the observation plane) by IR thermography. Here, the thermal model is simplified because the temperature field in relaxation on either side of the resistance can be considered isothermal with a separation of transfers in the plane and along the thickness. The mathematical model is then analytical (relaxation of a linear system), and the processing of the temperature field can be inversed thanks to the consideration of the logarithm of
matrices, useful when studying the propagation of measurement noise. The method proposed in the case of two or three cylinders is a first step and a validation for applications to the study of more complex media (large number of cylinders, granular media).
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All authors Thomas Lahens, Alain Sommier, Marie-Marthe Groz, Jean-Christophe Batsale
Optics
Dispersion-Aware Modeling Framework for Parallel Optical Computing
Ziqi Wei, Yuanjian Wan, Yuhu Cheng et al. (+2 more)
Optical computing represents a groundbreaking technology that leverages the unique properties of
photons, with innate parallelism standing as its most compelling advantage. Parallel optical computing like cascaded Mach-Zehnder interferometers (MZIs) based offers powerful computational capabilities but also introduces new challenges, particularly concerning dispersion due to the introduction of new frequencies. In this work, we extend existing theories of cascaded MZI systems to develop a generalized model tailored for wavelength-multiplexed parallel optical computing. Our comprehensive model incorporates component dispersion characteristics into a wavelength-dependent transfer
matrix framework and is experimentally validated. We propose a computationally efficient compensation strategy that reduces global dispersion error within a 40 nm range from 0.22 to 0.039 using edge-spectrum calibration. This work establishes a fundamental framework for dispersion-aware model and error correction in MZI-based parallel optical computing chips, advancing the reliability of multi-wavelength photonic processors.
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All authors Ziqi Wei, Yuanjian Wan, Yuhu Cheng, Xiao Yu, Peng Xie
Accelerator Physics
Strong Energy Dependent Transition Radiation in a Photonic Crystal
V.Gareyan and Zh.Gevorkian
Radiation of a charged particle crossing an alternating stack of slabs in the optical region is considered. Both disordered and periodic stacks are investigated. It is shown that for special type of alternating disordered and periodic stacks the radiation problem can be solved exactly for backward and forward Brewster observation angles. Strong $N^2$ dependence of radiation intensity on slab number is re-established in special case of the disordered stack. This leads to strong directivity either on forward or on backward Brewster angles depending on the type of stack randomness. In certain type of periodic photonic
crystal, a strong energy dependence $E^4$ for relativistic particles of the radiation intensity, observed at Brewster's angle is found. Further increment of particle energy leads to saturation. The band structure of the corresponding photonic
crystal (PhC) has a behavior, analogous to the Dirac cones in
graphene. We suggest this special type $1D$ photonic
crystal for application as a detector of relativistic particles.
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Optics · Cross-listed from cond-mat.mtrl-sci
Observation of cooperative strong coupling between optical phonon and crystal-field excitations in a pseudo Jahn-Teller system
Fangliang Wu, Xiaoxuan Ma, Zhongwei Zhang et al. (+6 more)
Cooperative interactions between localized electronic excitations and
crystal lattice are central to the emergence of complex structural phases in materials. However, the scaling relations governing these collective behaviors remain largely unexplored. Here, using magneto-Raman spectroscopy, we report the direct observation of the strongly coupled optical
phonon and non-degenerate
crystal-field excitations (CFEs) in ErFeO3. By independently tuning the effective population of Jahn-Teller-active erbium ions through temperature and chemical dilution with Jahn-Teller-inactive yttrium ions, we identify the coupling strength varies linearly with the square root of electronic excitations population. Notably, Y-doping reveals the hybridization gap reduces significantly faster than predicted by density scaling alone, indicating
phonon coherence is essential for establishing this cooperative interaction. Our findings highlight the role of optical
phonons in mediating short-range interactions that drive cooperative Jahn-Teller effect, evidencing the pathway for tailoring electronic and vibrational properties of Jahn-Teller materials through population control.
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All authors Fangliang Wu, Xiaoxuan Ma, Zhongwei Zhang, Motoaki Bamba, Haowen Wu, Jian Sun, Yuan Wan, Shixun Cao, Qi Zhang
Atomic Physics
Theoretical study on excited states of ICl+ molecular ion considering spin-orbit coupling
Rui Li, Ronglong Dou, Ting Gao et al. (+2 more)
The electronic structure of the ICl+ molecular ion is investigated by using high-level multireference configuration interaction (MRCI) method. To improve computational accuracy, Davidson corrections,
spin-orbit coupling (SOC), and core-valence electron correlations effects are incorporated into the calculations. The potential energy curves (PECs) of 21 electronic states associated with the two lowest dissociation limits are obtained. The dipole moments (DMs) of the 21 electronic states of ICl+ are systematically studied, and the variations of DMs of the identical
symmetry state in the avoided crossing regions are elucidated by analyzing the dominant electronic configuration. With the help of the calculated SOC
matrix element, the interaction between crossing states can be elucidated.
Spin-orbit coupling
matrix elements involving the several states are calculated. By analyzing potential energy curves of these states and the nearby electronic states, the possible predissociation channels are provided. Based on the computed PECs, the spectroscopic constants of bound states are determined. The comparison of the spectroscopic constants including and excluding SOC effect indicates that the SOC effect has an obvious correction to the spectroscopic properties of low-lying states. Finally, the transition properties between excited states and the ground state are studied. Based on the computed transition dipole moments and Franck-Condon Factors, radiative lifetimes for the low-lying vibrational levels of excited states are evaluated.
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All authors Rui Li, Ronglong Dou, Ting Gao, Qinan Li, Chaoqun Song
Chemical Physics
Ab initio derivation of the crystal field parameters for lanthanide ions: The f$^1$ case
Dumitru-Claudiu Sergentu, Gwenhaël Duplaix-Rata, Ionel Humelnicu et al. (+2 more)
The
crystal field theory as explained by Abragam and Bleaney in their landmark 1970 book on transition-ion electron paramagnetic resonance remains a cornerstone in the development of luminescence applications and molecular magnets based on the $f$-elements. The modern numerical derivation of the 27 $B_k^q$ Stevens
crystal field parameters (CFPs), which describe the splitting of the energy levels of a central ion, is traditionally achieved through the effective
Hamiltonian theory and multiconfiguration wavefunction theory calculations, insofar as the lowest $J$ level fully captures the targeted low-energy physics. In this work, we present a novel theoretical approach for determining the CFPs. The procedure resembles the traditional extraction path but crucially accounts for the full $\ket{J,M_J}$ space of an ion configuration with $L=3$ and $S=\nicefrac{1}{2}$. By demonstrating the extraction procedure using the simplest case of a Ce$^\text{III}$ 4f$^1$ ion with a
crystal-field split $J \in \{\nicefrac{5}{2}, \nicefrac{7}{2}\}$
manifold, it is shown for the first time that a unique set of CFPs describes the splitting and mixing both the $J$
manifolds. In fact, this $J/J^\prime$ mixing is analogous to the “
spin mixing” in binuclear transition metal complexes. At the employed level of calculation, we demonstrate that there is no
spin-orbit coupling influence on the CFP values, contrary to previous beliefs. This study represents the first step of a larger effort in reviewing the theory and extraction procedures of CFPs in f-element complexes.
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All authors Dumitru-Claudiu Sergentu, Gwenhaël Duplaix-Rata, Ionel Humelnicu, Boris Le Guennic, Rémi Maurice
Fluid Dynamics
Unsupervised simulation of incompressible flows with physics- and equality- constrained artificial neural networks
Qifeng Hu and Inanc Senocak
Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations, yet their success in simulating incompressible flows at high Reynolds numbers remains limited. Existing approaches rely on auxiliary labeled data, supervised pretraining, or reference solutions, and no purely unsupervised method comparable to conventional finite-difference or finite-volume solvers has been demonstrated. We attribute this gap to the absence of a mechanism for enforcing the divergence-free constraint and boundary conditions to strict tolerances. To address this, we adopt the physics- and equality-constrained artificial neural network (PECANN) framework with a conditionally adaptive augmented Lagrangian method (CA-ALM), and introduce a pressure-Poisson-based objective. The residual of the pressure Poisson equation is minimized subject to the momentum and continuity equations and boundary conditions on the primitive variables as equality constraints, with CA-ALM enforcing all constraints tightly. For advection-dominated, high-Reynolds-number flows, we further propose an adaptive vanishing
entropy viscosity that stabilizes early training without influencing the converged solution. A baseline that instead uses the momentum residual as the objective proves ineffective under the same machinery, underscoring the critical role of the pressure-Poisson objective. The method is assessed on lid-driven cavity flow up to $Re=7{,}500$, three-dimensional unsteady Beltrami flow, and steady and unsteady flow past a circular cylinder with general inflow-
outflow boundary conditions, including an ablation study identifying admissible outlet conditions – all without labeled data or supervised pretraining. Notably, it captures the spontaneous onset of periodic
vortex shedding in unsteady cylinder flow without external perturbations, starting from a randomly initialized network.
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Fluid Dynamics
Toward end-to-end quantum simulation of rapidly distorted turbulence
Zhaoyuan Meng, Leyu Chen, Jin-Peng Liu et al. (+1 more)
We propose an end-to-end
quantum algorithm to simulate rapidly distorted
turbulence via linear combination of
Hamiltonian (LCHS). The
algorithm comprises three primary stages: the efficient preparation of an initial turbulent state with a prescribed energy spectrum, its subsequent time
evolution via LCHS, and the direct measurement of key
turbulence statistics. Our analysis indicates that the
algorithm can offer a practical
quantum speedup over the classical simulation methods for a sufficiently large computational grid. We evaluate the
quantum resource requirements for simulating a minimal instance of non-trivial
turbulence with classical validation. The numerical results show excellent agreement with ground-truth solutions, capturing both the qualitative
evolution of turbulent fields and the quantitative behavior of statistics, including the Reynolds stresses and the fluctuating velocity spectrum. Despite its linearity, rapidly distorted
turbulence captures essential
turbulence mechanisms and may inform the development of
quantum algorithms for the Navier-Stokes equations. Our work establishes a foundation for addressing more complex turbulent phenomena on future fault-tolerant
quantum computers.
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All authors Zhaoyuan Meng, Leyu Chen, Jin-Peng Liu, Guowei He
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Detecting Linear Dichroism with Atomic Resolution
Roger Guzman, Ján Rusz, Ang Li et al. (+3 more)
X-ray linear dichroism has been pivotal for probing electronic anisotropies, but its inherent limited spatial resolution precludes atomic-scale investigations of orbital polarization. Here we introduce a versatile electron linear dichroism methodology in scanning transmission electron microscopy that overcomes these constraints. By exploiting momentum-transfer-dependent electron energy-loss spectroscopy with an atomic-sized probe, we directly visualize orbital occupation at individual atomic columns in real space. Using strained La0.7Sr0.3MnO3 thin films as a model system, we resolve the Mn-3d eg orbital polarization with sub-angstrom precision. We show that compressive strain stabilizes 3z2-r2 occupation while tensile strain favors x2-y2. These results validate our approach against established X-ray measurements while achieving the ultimate single atomic-column sensitivity. We further demonstrate two optimized signal extraction protocols that adapt to experimental constraints without compromising sensitivity. This generalizable platform opens unprecedented opportunities to study
symmetry-breaking phenomena at individual defects, interfaces, and in
quantum materials where atomic-scale electronic anisotropy governs emergent functionality.
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All authors Roger Guzman, Ján Rusz, Ang Li, Juan Carlos Idrobo, Wu Zhou, Jaume Gazquez
Geophysics · Cross-listed from astro-ph.EP
Jun Kimura
In the outer
solar system beyond Jupiter, water ice is a dominant component of planetary bodies, and most solid objects in this region are classified as icy bodies. Icy bodies display a remarkable diversity of geological, geophysical, and atmospheric processes, which differ fundamentally from those of the rocky terrestrial
planets. Evidence from past and ongoing spacecraft missions has revealed subsurface oceans, cryovolcanic activity, and tenuous but persistent atmospheres, showing that icy bodies are active and evolving worlds. At the same time, major questions remain unresolved, including the chemical properties of icy materials, the geological histories of their surfaces, and the coupling between internal
evolution and orbital dynamics. Current knowledge of the surfaces, interiors, and atmospheres of the principal icy bodies is built on spacecraft measurements, telescopic observations, laboratory experiments, and theoretical modeling. Recent contributions from Juno, JWST, and
stellar occultation studies have added valuable constraints on atmospheric composition, interior structure, and surface activity. Looking ahead, missions such as JUICE, Europa Clipper, Dragonfly, and the Uranus Orbiter and Probe are expected to deliver substantial progress in the study of icy bodies. Their findings, combined with continued Earth- and space-based observations and laboratory studies, will be critical for assessing the potential habitability of these environments and for placing them within a broader framework of planetary system formation and
evolution.
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Medical Physics
On the Appropriateness of Linear Stress Recovery in Biomechanical Analysis of Abdominal Aortic Aneurysm
Alastair Catlin, Mostafa Jamshidian, Adam Wittek et al. (+1 more)
Abdominal aortic aneurysm (AAA) wall stress is a candidate rupture risk marker but is typically computed from single-phase images without known cardiac phase. Linear stress recovery methods, which solve a single geometrically linear
equilibrium problem on the imaged, already-loaded geometry, have been validated for static stress estimation, but their robustness to unknown imaging phase remains unexplored. We investigated whether imaging phase materially biases 99th percentile stress recovered linearly, and whether linear recovery agrees with non-linear analysis under matched loads. Two patient-specific AAAs from a public 4D-CTA cohort (Case 1: 5.5% strain; Case 2: 4.5% strain) were analyzed. For each, we analyzed diastolic and synthetic systolic geometry, the latter generated by warping the diastolic mesh via displacements from non-linear hyperelastic analysis. Linear stresses were recovered on both geometries under systolic pressure and compared via 99th-percentile maximum principal stress, stress distributions, and 3D stress differential contours. Linear stresses under pulse pressure were compared against non-linear stresses. 99th-percentile stresses from linear recovery on diastolic vs synthetic systolic geometries under systolic pressure differed by 8.6% (Case 1) and 3.5% (Case 2), within
segmentation uncertainty. 99th-percentile stresses from linear recovery and non-linear analysis under pulse pressure agreed closely: 0% difference (Case 1) and 1.1% (Case 2), with nearly identical distributions. These findings support linear stress recovery for patient-specific AAA analysis in clinical settings with static single-phase imaging, offering a computationally efficient alternative without compromising accuracy or requiring patient-specific wall properties.
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All authors Alastair Catlin, Mostafa Jamshidian, Adam Wittek, Karol Miller