Free-form optimization of nanophotonic devices: from classical methods to deep learning

Abstract Nanophotonic devices have enabled microscopic control of light with an unprecedented spatial resolution by employing subwavelength optical elements that can strongly interact incident waves. However, to date, most nanophotonic been designed based on fixed-shape elements, and a large portion their design potential has remained unexplored. It is only recently free-form schemes spotlighted in nanophotonics, offering routes make break from conventional constraints utilize the full potential. In this review, we systematically overview nascent yet rapidly growing field device design. We attempt define term “free-form” context photonic design, survey different strategies for optimization spanning classical methods, adjoint-based contemporary machine-learning-based approaches.