Deep learning assisted design of high reflectivity metamirrors

Abstract

The advent of optical metasurfaces, i.e. carefully designed two-dimensional nanostructures, allows unique control of electromagnetic waves. To unlock the full potential of optical metasurfaces to match even complex optical functionalities, machine learning provides elegant solutions. However, these methods struggle to meet the tight requirements when it comes to metasurface devices for the optical performance, as it is the case, for instance, in applications for high-precision optical metrology. Here, we utilize a tandem neural network framework to render a focusing metamirror with high mean and maximum reflectivity of R mean = 99.993 % and R max = 99.9998 %, respectively, and a minimal phase mismatch of Δ ϕ = 0.016 % that is comparable to state-of-art dielectric mirrors.