1422 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.
This paper employs a microscopic cluster model with folding potentials and the Multiple Internal Reflections method to demonstrate that the synthesis of Mg via C + C pycnonuclear reactions in neutron stars is most probable through the formation of a new excited compound nucleus in quasibound states, offering a more precise description than traditional Woods-Saxon potentials.
This paper demonstrates that two-proton emitters with initial diproton correlations, such as Ne, can serve as sources of spin-entangled proton pairs exhibiting correlations that exceed local-hidden-variable bounds, provided the emission occurs via a democratic three-body process rather than sequential decay.
This paper investigates the dependence of octupole excitations on surface energy in Pb using various Skyrme interactions and finds a strong positive linear correlation between the surface energy of the interaction and the predicted energy of the first octupole excitation.
This paper outlines a modern, transparent, and methodologically robust effort to improve the precision and reliability of nuclear charge radii determinations by integrating complementary experimental techniques with advanced theoretical frameworks.
This study employs covariant density functional theory to investigate the structural evolution of even-even tungsten isotopes from W to W, revealing dynamic shape transitions, identifying a potential subshell closure at , predicting a neutron drip line at , and validating these findings against experimental data and other theoretical models to enhance understanding of nuclear structure and r-process nucleosynthesis.
This paper presents a numerical program that calculates deep inelastic scattering structure functions at next-to-leading order accuracy within the dipole picture, utilizing a reformulated expression for massive quark impact factors to ensure stable cross-section evaluations.
The paper introduces NucleiML, a machine learning framework that accelerates Bayesian exploration of nuclear equations of state by providing a -fold speedup in calculating finite nuclei ground-state properties while maintaining reasonable accuracy, thereby enabling the efficient integration of finite nuclei and neutron star constraints.
This paper utilizes a phenomenological spectrum shift model to demonstrate a striking correlation between average partonic transverse momentum loss and the initial energy density of the Quark-Gluon Plasma across a wide range of collision energies, while also successfully predicting high- hadron elliptic flow by coupling the model to geometric event shape estimates.
This paper provides approximate neutrino interaction rates for binary neutron star merger simulations in strong magnetic fields, incorporating Landau quantization and anomalous magnetic moments with controlled errors, while also identifying a low-density neutrino production channel from individual neutrons.
This paper introduces perturbation theory quantum Monte Carlo (PTQMC), a stochastic method that efficiently computes high-order many-body perturbative corrections by using random walkers to avoid exponential scaling, while also providing a new complexity metric () to better assess the validity of perturbative expansions.