931 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 analyzes and compares the -ray spectra of various -process trajectories over timescales ranging from hours to 50,000 years to identify significant contributing nuclei and discuss the potential and challenges of using these spectral features to probe the fundamental physics of the -process.
This paper introduces a general framework for deriving linearized dispersion spectra in Lorentz boosted frames using only local rest-frame data, revealing the emergence of causality-violating "spurious modes" and establishing a direct link between mode conservation and the causality of relativistic fluid theories.
Motivated by recent HAL QCD simulations, this study employs a first-principles few-body framework to predict the existence of deeply and moderately bound -mesic nuclei (, , and ), demonstrating that strong short-range attraction in the channel is the key binding mechanism.
Using soft X-ray data from India's Chandrayaan-2 mission, this study sets significantly stronger constraints on axion-nucleon and axion-photon couplings for solar axions produced in Fe nuclear transitions compared to those from Kr, due to a nearly three-order-of-magnitude difference in their respective fluxes despite similar effective couplings.
Using time-dependent density functional theory, this study demonstrates that incorporating non-axial deformations in the spontaneous fission of Cf enables axial tilting rotations and broadens spin distributions, thereby reducing spin-spin correlations along the fission axis compared to axially symmetric trajectories.
This paper presents a unified classification-quantification framework using the dimensionless $BHTU$ parameters to systematically characterize bubble-like nuclear morphologies across the AME2020 database within the extended quantum molecular dynamics model, revealing widespread bubble and toroidal structures in medium-mass, heavy, and superheavy nuclei.
This paper proposes that thermal inhomogeneity at the surface of neutron star nuclear pasta, combined with nuclear spin-orbit coupling, induces anomalous spin polarization in surface-localized neutrons even in the absence of a magnetic field, thereby bridging neutron star physics and solid-state spintronics.
This paper investigates the form-factor dependence of Reggeized spin-2 Pomeron and spin-3 Odderon exchanges in high-energy elastic $pp$ and scattering, demonstrating that an exponential Odderon-proton form factor provides a superior fit to global data compared to other parametrizations and reveals a peripheral soft Odderon interaction with hadronic-scale transverse structure.
This paper investigates the intermittency and fractal behavior of charged particles in Pb-Pb collisions at 5.02 TeV using EPOS4 and PYTHIA8 simulations to analyze large density fluctuations as potential signatures of the QCD phase transition and critical point.
This paper utilizes the String Melting mode of the AMPT model to investigate the scaling behavior and intermittency of charged particle multiplicity fluctuations in Xe–Xe collisions at = 5.44 TeV, determining key parameters such as anomalous fractal dimensions and scaling exponents to characterize the system's self-similar dynamics and provide baseline predictions.