Solving the Schrödinger Equation with deep neural networks

A deep (convolutional) neural network is trained to predict the ground-state energy of an electron in two-dimensional potentials. The machinery of deep learning is developed to learn the mapping between potential and energy, which bypasses the need to numerically solve the Schrödinger equation and the need for computing wave functions.