Simulated annealing algorithm with neural network for designing topological photonic crystals.

In this work, we utilize simulated annealing algorithm with neural network, to achieve rapid design of topological photonic crystals. We firstly train a high-accuracy neural network that predicts the band structure of hexagonal lattice photonic crystals. Subsequently, we embed the neural network into the simulated annealing algorithm, and choose the on-demand evaluation functions for optimizing topological band gaps.