22 citations · 50 across the 7 of their papers we have counts for
4 papers · 1 filter
Systematic study of one-point kinetic energy density functionals for atomic nuclei
Tian Shuai Shang, Jian Li, Haozhao Liang +5
To explore the applicability of orbital-free density functional theory (OF-DFT) in nuclear physics, we perform a systematic benchmark of 36 one-point kinetic energy density functio…
Global prediction of nuclear charge density distributions using deep neural network
Tian Shuai Shang, Hui Hui Xie, Jian Li +1
A deep neural network (DNN) has been developed to generate the distributions of nuclear charge density, utilizing the training data from the relativistic density functional theory…
Nuclear mass predictions based on convolutional neural network
Yanhua Lu, Tianshuai Shang, Pengxiang Du +3
A convolutional neural network (CNN) is employed to investigate nuclear mass. By introducing the masses of neighboring nuclei and the paring effects at the input layer of the netwo…
A neural network approach for two-body systems with spin and isospin degrees of freedom
Chuanxin Wang, Tomoya Naito, Jian Li +1
We propose an enhanced machine learning method to calculate the ground state of two-body systems. By extending the original method [Naito, Naito, and Hashimoto, Phys. Rev. Research…