Calibration of nuclear charge density distribution by back-propagation neural networks
Calibration of nuclear charge density distribution by back-propagation neural networks
Based on the back-propagation neural networks and density functional theory, a supervised learning is performed firstly to generate the nuclear charge density distributions. The charge density is further calibrated to the experimental charge radii by a composite loss function. It is found that, when the parity, pairing, and shell effects …