Related papers: A Data-Driven Density Functional Model for Nuclear…
A molecule model is proposed for the description of the properties of the kaonic nuclear cluster (KNC) anti-KNN with the structure N(ant-KN)_(I = 0) and quantum numbers I(J^P) = 1/2(0^-), the large binding energy B^(\exp)_(anti-KNN) =…
The neutron-skin thickness of asymmetric semi-infinite nuclear matter is shown to be a function of Coulomb energy, the asymmetry-energy coefficient($J$), the slope($L$) of the asymmetry energy, and the incompressibility coefficient, in…
This study explores the application of Kolmogorov-Arnold Networks (KANs) in predicting nuclear binding energies, leveraging their ability to decompose complex multi-parameter systems into simpler univariate functions. By utilizing data from…
A simple and efficient method to treat nuclear pairing correlations within a simple Hartree-Fock--plus-BCS description is proposed and discussed. It relies on the fact that the intensity of pairing correlations depends crucially on level…
We show that deep neural networks can be integrated into, or fully replace, the Kohn-Sham density functional theory scheme for multi-electron systems in simple harmonic oscillator and random external potentials with no feature engineering.…
Concepts from information geometry are used to analyse parameter sensitivity for a nuclear energy density functional, representative of a class of semi-empirical functionals that start from a microscopically motivated ansatz for the density…
The neutron skin thickness in neutron-rich nuclei has traditionally been measured using elastic fixed target electron-nucleus scattering since the 1970s. In this paper, we propose a novel probe of the neutron skin thickness through deep…
Nuclear and neutron matters are investigated in the low density region, well below the nuclear saturation density. Microscopic calculations, based on the Bethe-Brueckner approach with a few realistic nucleon-nucleon potentials, are compared…
Nuclear density functional theory provides a unified description of finite nuclei and bulk nuclear matter, and is widely used to model the neutron star equation of state. However, extrapolations to supra-saturation densities require a…
In the distributed nucleus approximation we represent the singular nucleus as smeared over a smallportion of a Cartesian grid. Delocalizing the nucleus allows us to solve the Poisson equation for theoverall electrostatic potential using a…
The bulk properties of nuclear matter and neutron stars with the newly generated relativistic interaction DBHP are investigated which provides an opportunity to modify the coupling parameters keeping in view the finite nuclei, nuclear…
The global behavior of the nuclear equation of state (EoS) is commonly studied using data from finite nuclei (FN), heavy-ion collisions, and astrophysical observations of neutron stars (NS). The constraints derived from FN such as binding…
We formulate a time-dependent density functional theory for the coupled dynamics of electrons and nuclei that goes beyond the Born-Oppenheimer (BO) approximation. We prove that the time-dependent marginal nuclear probability density…
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, ranging from materials science to biochemistry to…
Eighty years after its experimental discovery, a microscopic description of induced nuclear fission based solely on the interactions between neutrons and protons and quantum many-body methods still poses formidable challenges. The goal of…
An accurately calibrated relativistic parametrization is introduced to compute the ground state properties of finite nuclei, their linear response, and the structure of neutron stars. While similar in spirit to the successful NL3 parameter…
We describe the most recent energy density functional derived within the quark meson coupling model. Although fit to the binding energies and charge radii of just seventy magic nuclei, the accuracy with which it reproduces nuclear…
We describe the main features of our most recent Hartree-Fock-Bogoliubov nuclear mass models, based on 16-parameter generalized Skyrme forces. They have been fitted to the data of the 2012 Atomic Mass Evaluation, and favour a value of 30…
This study investigates the application of deep learning models-recurrent neural networks, gated recurrent units, and long short-term memory networks-for predicting nuclear binding energies. Utilizing data from the Atomic Mass Evaluation…
Background: Nuclear energy-density functional (EDF) approach has been widely used to describe nuclear-matter equations of state (EoS) and properties of finite nuclei. Recent advancements in neutron-star (NS) observations have put…