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

We propose an enhanced machine learning method to calculate the ground state of two-body systems. By extending the original method [Phys. Rev. Res. 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 unsupervised machine learning technique. The validity of this method is verified by calculating the unique bound state of the deuteron.