  We apply the deep learning neural network architecture to the two-level
system in quantum optics to solve the time-dependent Schrodinger equation. By
carefully designing the network structure and tuning parameters, above 90
percent accuracy in super long-term predictions can be achieved in the case of
random electric fields, which indicates a promising new method to solve the
time-dependent equation for two-level systems. By slightly modifying this
network, we think that this method can solve the two- or three-dimensional
time-dependent Schrodinger equation more efficiently than traditional
approaches.
