Engineering the point spread function of layered metamaterials

TL;DR

This paper reviews recent advances in engineering layered metamaterials' spatial filtering properties and introduces a numerical optimization framework using evolutionary algorithms to tailor their diffraction characteristics.

Contribution

It presents a novel optimization method for designing layered metamaterials with specific spatial filtering responses, incorporating a similarity measure based on Hoelder's inequality.

Findings

Optimization framework effectively designs metamaterials with desired diffraction properties

Surface roughness impacts imaging quality in layered metamaterials

Evolutionary algorithms improve the design process for nanoscale optical devices

Abstract

Layered metal-dielectric metamaterials have filtering properties both in the frequency domain and in the spatial frequency domain. Engineering their spatial filtering response is a way of designing structures with specific diffraction properties for such applications as sub-diffraction imaging, supercollimation, or optical signal processing at the nanoscale. In this paper we review the recent progress in this field. We also present a numerical optimization framework for layered metamaterials, based on the use of evolutionary algorithms. A measure of similarity obtained using Hoelder's inequality is adapted to construct the overall criterion function. We analyze the influence of surface roughness on the quality of imaging.