Inverse design of thermally tunable metasurfaces for selective multi-channel terahertz wavefront manipulation
The emergence of deep neural networks (DNNs) has greatly alleviated the time-consuming and phase-discretization problems in conventional metasurface design processes. However, most DNN-assisted design methods are constrained by predefined target electromagnetic (EM) parameter formats, making retraining unavoidable when...