Large-scale parameterized metasurface design using adjoint optimization

TL;DR

This paper introduces an efficient adjoint optimization method for designing large-scale, high-performance optical metasurfaces with parameterized meta-atoms, overcoming computational limitations of previous approaches.

Contribution

It presents a novel adjoint-optimization technique that enables scalable, accurate design of complex metasurfaces using parameterized meta-atoms, with lower computational cost than traditional topology optimization.

Findings

Designed high-efficiency metalenses with high numerical aperture

Demonstrated experimental validation of large-scale metasurfaces

Achieved significantly higher efficiencies than conventional designs

Abstract

Optical metasurfaces are planar arrangements of subwavelength meta-atoms that implement a wide range of transformations on incident light. The design of efficient metasurfaces requires that the responses of and interactions among meta-atoms are accurately modeled. Conventionally, each meta-atom's response is approximated by that of a meta-atom located in a periodic array. Although this approximation is accurate for metastructures with slowly varying meta-atoms, it does not accurately model the complex interactions among meta-atoms in more rapidly varying metasurfaces. Optimization-based design techniques that rely on full-wave simulations mitigate this problem but thus far have been mostly applied to topology optimization of small metasurfaces. Here, we describe an adjoint-optimization-based design technique that uses parameterized meta-atoms. Our technique has a lower computational cost than topology optimization approaches, enabling the design of large-scale metasurfaces that can be readily fabricated. As proof of concept, we present the design and experimental demonstration of high numerical aperture metalenses with significantly higher efficiencies than their conventionally-designed counterparts.