Computational inverse design for cascaded systems of metasurface optics

TL;DR

This paper introduces a computational inverse design method for creating complex cascaded metasurface optical systems, enabling efficient optimization of multiple metasurfaces for various advanced optical functionalities.

Contribution

It presents a scalable inverse design approach for multi-element metasurface systems, expanding the capabilities of metasurface-based optics.

Findings

Designed an achromatic doublet metasurface lens

Created a spectrally-multiplexed holographic element

Developed an ultra-compact optical neural network

Abstract

Metasurfaces are an emerging technology that may supplant many of the conventional optics found in imaging devices, displays, and precision scientific instruments. Here, we develop a method for designing optical systems composed of multiple unique metasurfaces aligned in sequence. Our approach is based on computational inverse design, also known as the adjoint-gradient method. This technique enables thousands or millions of independent design variables to be optimized in parallel, with little or no intervention required by the user. To demonstrate the broad applicability of our method, we use it to design an achromatic doublet metasurface lens, a spectrally-multiplexed holographic element, and an ultra-compact optical neural network for classifying handwritten digits.