A neural network approach for two-body systems with spin and isospin degrees of freedom
This paper proposes an enhanced unsupervised machine learning method using a non-fully connected deep neural network to calculate the ground states of two-body systems with spin and isospin degrees of freedom, successfully validating the approach by reproducing the unique bound state of the deuteron.