A deep-learning approach for modeling phase-change metasurface in the mid-infrared

Reconfigurable metasurface constitutes an important block for future adaptive and smart nanophotonic applications. In this work we introduce a new modeling approach for the fast design of tunable and reconfigurable metasurface structures using convolutional deep learning network. The metasurface structure is modeled as a multilayer image tensor to model the material properties as image maps. The dimensionality mismatch problem is avoided by …