Nucl-Ex represents the dynamic frontier where scientists probe the fundamental building blocks of matter through high-energy experiments. By smashing particles together at incredible speeds or observing rare cosmic events, researchers uncover the forces that govern our universe and test the limits of our current understanding of physics.

At Gist.Science, we ensure these breakthroughs reach a broader audience by processing every new preprint in this field directly from arXiv. For each study, we provide both a clear, plain-language explanation of the core discoveries and a detailed technical summary for those seeking deeper insights. Below are the latest papers in nuclear experiment research, curated to help you stay informed on the latest developments from the lab.

Physics-Informed Global Extraction of the Universal Small-xx Dipole Amplitude

This paper presents a physics-informed neural network approach to extract a universal small-xx dipole scattering amplitude directly from global DIS and photoproduction data without rigid parametric assumptions, successfully resolving the long-standing tension between total and charm cross-section channels while providing a smooth, non-negative input for Color Glass Condensate phenomenology.

Si-Wei Dai, Fu-Peng Li, Long-Gang Pang, Guang-You Qin, Shu-Yi Wei, Han-Zhong Zhang, Wenbin Zhao2026-03-10⚛️ hep-ph

Study of the in34in ^{34}Ar(α,p\alpha,p)37^{37}K reaction rate via proton scattering on 37^{37}K, and its impact on properties of modeled X-Ray bursts

This study constrains the properties of resonances in 38^{38}Ca via proton scattering on an unstable 37^{37}K beam to refine the 34^{34}Ar(α,p\alpha,p)37^{37}K reaction rate, ultimately finding that the updated rate does not significantly alter the light curve features of modeled Type I X-Ray bursts.

A. Lauer-Coles, C. M. Deibel, J. C. Blackmon, A. Hood, E. C. Good, K. T. Macon, D. Santiago-Gonzalez, H. Schatz, T. Ahn, J. Browne, F. Montes, K. Schmidt, 4 W. J. Ong, K. A. Chipps, S. D. Pain, I. Wie (…)2026-03-09⚛️ nucl-ex

Precision Mass Measurements of \textsuperscript{130}Te, \textsuperscript{130}Sn, and Their Impact on Models for R-Process Nucleosynthesis

This paper reports the first precision mass measurements of \textsuperscript{130}Te, \textsuperscript{130}Sn, and \textsuperscript{130}Sn\textsuperscript{m} using the Phase-Imaging Ion Cyclotron Resonance technique, demonstrating improved precision for \textsuperscript{130}Sn and utilizing these new values in SkyNet simulations to refine models of r-process nucleosynthesis and distinguish between cold and hot astrophysical scenarios.

A. Cannon, W. S. Porter, A. A. Valverde, D. P. Burdette, A. M. Houff, B. Liu, A. Mitra, G. E. Morgan, C. Quick, D. Ray, L. Varriano, M. Brodeur, J. A. Clark, G. Savard, G. J. Mathews2026-03-09⚛️ nucl-ex

A Lattice QCD study of pΛp-\Lambda scattering in continuum and chiral limits

This paper presents the first systematic lattice QCD study of I=1/2I=1/2 proton-Λ\Lambda scattering across multiple pion masses and lattice spacings, yielding scattering parameters and cross sections that agree with experimental data and confirm attractive interactions critical for nuclear theory and neutron star modeling.

Hang Liu, Liuming Liu, Jin-Xin Tan, Wei Wang, Haobo Yan, Qian-Teng Zhu2026-03-09⚛️ hep-ph

Implications for Type Ia Supernova Nucleosynthesis from an Experimentally Constrained 16^{16}O(p,α)13(p,\alpha)^{13}N Reaction Rate

By performing the first direct measurement of the 16^{16}O(p,α)13(p,\alpha)^{13}N reaction at astrophysical energies, researchers determined a thermonuclear rate approximately 1.5 times higher than standard values, thereby ruling out a previously suggested seven-fold enhancement and concluding that this reaction alone cannot explain observed calcium-to-sulphur and argon-to-sulphur ratio variations in Type Ia supernovae.

M. Alruwaili (University of York, UK, Northern Border University, Saudi Arabia), C. Fougeres (Argonne National Laboratory, USA), A. M. Laird (University of York, UK), H. Jayatissa (Argonne National La (…)2026-03-09🔭 astro-ph

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, Satoshi Chiba, Tatsuya Katabuchi, Chikako Ishizuka2026-03-06🔬 physics