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 C6v symmetry were arranged in triangle lattices of hexagons, and the designing of parameters individually for 6 x 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.