Deep learning improves performance of topological bending waveguides

This study introduced design informatics using deep learning in a topological photonics system and applied it to a topological waveguide with a sharp bending structure to further reduce propagation loss. The sharp bend in the topological waveguide composed of two photonic crystals wherein dielectrics having C symmetry were arranged in triangle lattices of hexagons, and the designing of parameters individually for 6 × 6 unit cells near the bending region using deep learning resulted in an output improvement of 60% compared to the initial structure. The proposed structural design method has high versatility and applicability for various topological photonic structures.