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.
This paper presents a machine learning-based b-jet tagging method using a convolutional neural network trained on jet, track, and secondary vertex information for anti- jets in 13 TeV $pp$ collisions, demonstrating superior performance over traditional tagging techniques.
This paper presents a new quantum model demonstrating that bremsstrahlung emission in the ternary fission of Cf is highly sensitive to the process's geometry and dynamics, particularly the relative motion of heavy fragments, with theoretical predictions aligning well with preliminary experimental data.
This paper proposes a method to significantly reduce the uncertainty in nuclear matrix elements for neutrinoless double-beta decay by utilizing a phenomenological effective axial-vector coupling derived from measured two-neutrino double-beta decay half-lives, thereby refining the constraints on the effective neutrino mass.
This paper develops a new resonating group method formalism that accommodates unequal harmonic-oscillator frequencies for baryons with distinct quantum numbers, applying it to the system within a chiral SU(3) quark model to provide a unified framework for describing both single-baryon properties and baryon-baryon interactions.
This study employs a Bayesian analysis of mock neutron star radius measurements to demonstrate that while high-precision data can tightly constrain symmetry-energy parameters and transition densities, it cannot uniquely identify the underlying mass-radius topology or fully determine high-density quark-matter properties without complementary probes.
This paper proposes a modified Polyakov-Nambu-Jona-Lasinio model with a chemical potential-dependent Polyakov potential to describe cold dense matter, demonstrating that repulsive vector interactions and a stiff hadronic equation of state are essential for forming stable hybrid stars with quarkyonic or deconfined cores that exceed two solar masses.
This paper employs the WKB approximation on the 1+1 dimensional Dirac equation to derive a corrected relativistic penetration probability using an effective potential that systematically increases predicted proton emission half-lives, with effects reaching up to 84% for high orbital angular momentum cases like .
This study investigates thermal photon production in a magnetized quark-gluon plasma using (1+1)-dimensional relativistic magnetohydrodynamics, revealing that while photon yields are primarily determined by the initial magnetic field strength and its decay, weak-field quantum corrections to quark distribution functions significantly enhance production at intermediate transverse momenta, whereas magnetic susceptibility has a negligible effect.
This study introduces an energy-dependent scaling factor for charge-changing cross sections of light elements (Be–F) within the Glauber model framework, successfully predicting experimental data across a wide energy range and offering a practical scheme for inferring proton radii where measurements are scarce.
Using lattice theory as a proof of principle, this paper demonstrates that classical field simulations can effectively model particle production and subsequent equilibration in nonequilibrium quantum field dynamics, establishing a scalable pathway for future quantum computing applications in studying pre-equilibrium systems like the early Universe and heavy-ion collisions.