A neural network approach for two-body systems with spin and isospin degrees of freedom
Nuclear Theory
2026-04-21 v2 Computational Physics
Quantum Physics
Abstract
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 5, 033189 (2023)], the present method enables consideration of the spin and isospin degrees of freedom by employing a non-fully connected deep neural network and the unsupervised machine learning technique. The validity of this method is verified by calculating the unique bound state of the deuteron.
Keywords
Cite
@article{arxiv.2403.16819,
title = {A neural network approach for two-body systems with spin and isospin degrees of freedom},
author = {Chuanxin Wang and Tomoya Naito and Jian Li and Haozhao Liang},
journal= {arXiv preprint arXiv:2403.16819},
year = {2026}
}
Comments
10 pages, 5 figures, 4 tables