A neural network approach for two-body systems with spin and isospin degrees of freedom

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.