Multi-element Metagrating Design With Densely-connected Neural Networks

Although metasurfaces offer unprecedented design flexibility, the discovery of optimal structures remains a challenging problem where techniques like Deep learning are becoming significant. We propose novel neural architectures beyond the traditionally employed feedforward architectures and explore their utility in the design of multiple-element metagratings.