🔬 Category

physics.data-an

36 papers

Non-intrusive Monitoring of Sealed Microreactor Cores Using Physics-Informed Muon Scattering Tomography With Momentum Measurements

This paper introduces μ\muTRec, a physics-informed muon scattering tomography framework that significantly enhances the detection of missing fuel in sealed microreactor cores by reconstructing curved muon trajectories and incorporating momentum measurements, thereby outperforming conventional methods like PoCA in both sensitivity and speed under realistic cosmic-ray conditions.

Reshma Ughade, Stylianos ChatzidakisMon, 09 Ma🔬 physics.app-ph

Large Language Models -- the Future of Fundamental Physics?

This paper demonstrates that the Qwen2.5 Large Language Model, when combined with connector networks to form a "Lightcone LLM," can effectively analyze and generate 3D cosmological maps from SKA data, outperforming standard initialization methods and matching dedicated networks of similar size for tasks like parameter regression and lightcone generation.

Caroline Heneka, Florian Nieser, Ayodele Ore, Tilman Plehn, Daniel SchillerMon, 09 Ma⚛️ hep-ph

Extreme Value Analysis for Finite, Multivariate and Correlated Systems with Finance as an Example

This paper proposes a practical framework for analyzing extreme values in finite, multivariate, and correlated systems—demonstrated through high-frequency finance data—by rotating returns into the correlation matrix's eigenbasis to isolate collective and idiosyncratic effects, thereby enabling the use of univariate peaks-over-threshold methods to estimate tail risks while accounting for nonstationarity.

Benjamin Köhler, Anton J. Heckens, Thomas Guhr2026-03-06🔬 physics

Linear Acceleration Is a Primary Risk Factor for Concussion

This study challenges the prevailing hypothesis that rotational acceleration is the primary cause of concussion by demonstrating through direct in vivo measurements that linear acceleration is a significantly more precise predictor of injury, leading to the development of a liquid shock-absorbing helmet technology that could reduce concussion risk by up to 73%.

Jessica A. Towns, Nicholas J. Cecchi, James W. Hickey + 9 more2026-03-06🔬 physics

Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics

This paper introduces Structured Kolmogorov-Arnold Neural ODEs (SKANODEs), a framework that combines structured state-space modeling with Kolmogorov-Arnold Networks to accurately recover interpretable physical latent states and discover compact symbolic governing equations for nonlinear dynamical systems, outperforming black-box neural ODEs and classical identification methods across synthetic and real-world datasets.

Wei Liu, Kiran Bacsa, Loon Ching Tang + 1 more2026-03-06🔬 physics

Physics-Embedded Bayesian Neural Network (PE-BNN) to predict Energy Dependence of Fission Product Yields with Fine Structures

This paper introduces a physics-embedded Bayesian neural network (PE-BNN) framework that integrates an energy-independent phenomenological shell factor and WAIC-based hyperparameter optimization to accurately predict energy-dependent fission product yields with fine structures and close agreement with known nuclear shell effects.

Jingde Chen, Yuta Mukobara, Kazuki Fujio + 3 more2026-03-06🔬 physics

Structured generalized sliced Wasserstein distance for keV X-ray polarization analysis with Gas Pixel Detector

This paper proposes a data-driven "structured generalized sliced Wasserstein distance" method using randomized neural networks to directly analyze two-dimensional polarized images from Gas Pixel Detectors, successfully determining X-ray polarization and incident angles while demonstrating high consistency with traditional statistical models.

Pengcheng Ai, Hongtao Qin, Xiangming Sun + 3 more2026-03-05🔭 astro-ph