From the 1 of 6 linked papers with an AI index.
6 papers
Microscopic Statistical Calculation of Nuclear Level Density Based on Relativistic Density Functional Theory
Zi-Cheng Wang, Peng-Xiang Du, Jian Li +2
A microscopic statistical model based on the relativistic density functional theory (RDFT) is developed to calculate the nuclear level density (NLD). The approach employs self-cons…
Microscopic Study of Charge Properties in Halo Nuclei
Yun Dong Wang, Hui Hui Xie, Tian Shuai Shang +3
The paper uses relativistic continuum Hartree‑Bogoliubov theory with electromagnetic corrections to study charge distributions in neutron‑halo nuclei of neon and phosphorus isotope…
The Pseudospectral Method for the Dirac Equation with Confining Potential
Dengshan Liu, Huihui Xie, Pengxiang Du +2
We observe that solving the Dirac equation for confined potentials using the generalized pseudospectral (GPS) method leads to deteriorating convergence of energy eigenvalues and hi…
Nuclear level densities in the relativistic Hartree-Bogoliubov plus combinatorial framework
Pengxiang Du, Jian Li
A systematic study of nuclear level densities has been carried out within the relativistic Hartree-Bogoliubov plus combinatorial framework. Calculations were performed for even-eve…
Predictions of charge density distributions for nuclei with
Yun Dong Wang, Tian Shuai Shang, Hui Hui Xie +3
A deep neural network (DNN) has been developed to accurately predict nuclear charge density distributions for nuclei with proton numbers . By incorporating essential nucl…
Bridging Theory and Data: Correcting Nuclear Mass Models with Interpretable Machine Learning
Yanhua Lu, Tianshuai Shang, Pengxiang Du +2
Nuclear mass prediction is one of the core issues in nuclear physics research, yet it faces the challenge of small-sample datasets with high complexity. This study introduces the K…