1634 papers
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.
Using no-core shell model calculations, this study characterizes the halo structure of He by demonstrating that two-nucleon spatial correlations reveal a dominant spin-singlet configuration for valence neutrons and an off-centering effect relative to the core that primarily accounts for the nucleus's increased point-proton radius.
This paper demonstrates that quantum anomalies manifest in charge-flux detector correlators through a singular localization mechanism where massless limits collapse angular distributions onto beam-collinear directions, thereby preserving finite energy-weighted sum rules for axial-charge, higher-spin helicity (zilch), and mixed axial-gravitational fluxes.
This paper demonstrates that while machine learning models can successfully interpolate Equation of State parameters from core-collapse supernova gravitational waves within a training catalogue, they fail to generalize to unseen Equation of State families due to a significant generalization gap, highlighting the critical need for leave-family-out validation and physics-aware inference frameworks.
This paper employs a hybrid transverse momentum dependent approach to confirm the universality of the Collins function by successfully describing STAR proton-proton collision data and subsequently provides leading-order predictions for Electron-Ion Collider kinematics, demonstrating that quasireal photon exchange effects, while sizable, do not hinder the clear extraction of the transversity distribution and its sea-quark component in lepton-proton collisions.
This study demonstrates that machine learning algorithms, specifically supervised and unsupervised methods trained on transport model data (UrQMD, AMPT, and JAM), can robustly reconstruct the impact parameter in Au+Au collisions at 4 and 11 GeV with high accuracy and superior generalization compared to traditional polynomial fitting, suggesting strong potential for application to real experimental data.
This paper presents new analytical expressions and predictions for double quarkonium production in unpolarized and polarized hadronic collisions at fixed-target experiments, utilizing transverse momentum dependent factorization combined with the Color-Singlet Model to describe angular structures, cross sections, and transverse single-spin asymmetries for current and future CERN and LHC facilities.
Using the functional renormalization group approach, this study demonstrates that while scalar-pseudoscalar four-quark channels dominate in the vacuum, other channels become significant near the critical end point, collectively shifting the QCD critical end point to a higher baryon chemical potential and lower temperature while slightly increasing the curvature of the phase boundary.
This paper demonstrates that Bayesian neural networks outperform Gaussian processes in extracting fusion barrier distributions from experimental cross-section data by providing more faithful reconstructions with quantified uncertainties, while also identifying key regions for future experimental impact and highlighting that the fidelity of all methods depends primarily on the magnitude of experimental uncertainties.
This paper presents the first calculation of single inclusive hadron and jet production at large transverse momentum in lepton-hadron scattering using a joint QCD+QED factorization framework, which introduces universal lepton distribution functions with combined evolution kernels and provides predictions for experiments at Jefferson Lab and the future Electron-Ion Collider.
This study employs time-dependent superfluid density functional theory (TDSLDA) to demonstrate that pairing correlations significantly enhance two-neutron transfer probabilities in the channel during sub-barrier Ca + Zr collisions, successfully reproducing experimental enhancement factors and confirming the critical role of nuclear superfluidity in reaction dynamics.