Nuclear theory sits at the fascinating intersection of particle physics and the forces that hold our universe together. This field explores how protons and neutrons bind inside atomic nuclei, seeking to understand the fundamental interactions that govern matter at its most dense and energetic levels. While the mathematics involved can be incredibly complex, the core questions are deeply human: how does the universe function at its smallest scales, and what happens when we push matter to its limits?

At Gist.Science, we make these cutting-edge discoveries accessible by processing every new preprint published in this category on arXiv. Our team transforms dense academic manuscripts into clear, plain-language summaries alongside detailed technical overviews, ensuring that both experts and curious readers can grasp the latest breakthroughs without getting lost in the jargon. Below are the latest papers in nuclear theory, distilled and ready for you to explore.

Proton Structure from Neural Simulation-Based Inference at the LHC

This paper demonstrates for the first time that neural simulation-based inference (NSBI) can effectively constrain proton parton distribution functions using high-dimensional, unbinned LHC data, achieving significantly improved precision over traditional binned analyses by fully exploiting statistical power and reducing reliance on coarse uncertainty approximations.

Ricardo Barrué, Lisa Benato, Ali Kaan Güven, Elie Hammou, Jaco ter Hoeve, Claudius Krause, Ang Li, Luca Mantani, Juan Rojo, Sergio Sánchez Cruz, Robert Schöfbeck, Maria Ubiali, Daohan Wang2026-04-16⚛️ hep-ph

AI-assisted modeling and Bayesian inference of unpolarized quark transverse momentum distributions from Drell-Yan data

This paper presents a global Bayesian analysis of unpolarized quark transverse-momentum-dependent parton distribution functions using Drell-Yan data at N3LO{\rm N^3LO} and N4LL{\rm N^4LL} accuracy, leveraging AI-driven functional form selection and machine-learning emulators to enable efficient Markov Chain Monte Carlo sampling and quantify uncertainties.

Zhong-Bo Kang, Luke Sellers, Congyue Zhang, Curtis Zhou2026-04-16⚛️ nucl-th

Diffractive vector meson photo-production in oxygen-oxygen and neon-neon ultraperipheral collisions at energies available at the CERN Large Hadron Collider

This paper utilizes the energy-dependent hotspot model with various nuclear shape prescriptions to predict cross sections for coherent and incoherent diffractive vector meson (ρ0\rho^0 and J/ψ\psi) photo-production in oxygen-oxygen and neon-neon ultraperipheral collisions at the LHC, demonstrating that simultaneous measurements of these processes can constrain nuclear models and probe the gluon-saturation regime.

J. Cepila, J. G. Contreras, M. Matas, A. Ridzikova2026-04-15⚛️ nucl-th

Decomposition of angular momentum projected nuclear wave function

This paper derives a new identity that decomposes conventional angular momentum projected nuclear wave functions into coupled neutron-proton projected bases, revealing that nucleons in even-even ground states are not fully paired and demonstrating that this decomposition enables further improvements to variation after projection shell model wave functions.

Wen Chen, Zhan-Jiang Lian, Xue-Wei Li, Xin-Yang Xia, Zi-Yang He, Ke-Zheng Ruan, Zao-Chun Gao2026-04-15⚛️ nucl-th