End-to-End Nanophotonic Inverse Design for Imaging and Polarimetry

TL;DR

This paper presents an end-to-end nanophotonic design approach that integrates optical and computational components for improved imaging and polarimetry, leveraging full Maxwell physics for enhanced noise robustness.

Contribution

It introduces a large-scale inverse design method coupling Maxwell equations with inverse scattering, producing novel nanostructures for superior imaging and polarization detection.

Findings

Significantly reduces noise sensitivity in imaging and polarimetry.

Creates nanostructures that outperform conventional optics and random microstructures.

Enables detection of spectral and polarization details discarded by traditional methods.

Abstract

By co-designing a meta-optical front end in conjunction with an image-processing back end, we demonstrate noise sensitivity and compactness substantially superior to either an optics-only or a computation-only approach, illustrated by two examples: subwavelength imaging and reconstruction of the full polarization coherence matrices of multiple light sources. Our end-to-end inverse designs couple the solution of the full Maxwell equations---exploiting all aspects of wave physics arising in subwavelength scatterers---with inverse-scattering algorithms in a single large-scale optimization involving $\gtrsim 10^4$ degrees of freedom. The resulting structures scatter light in a way that is radically different from either a conventional lens or a random microstructure, and suppress the noise sensitivity of the inverse-scattering computation by several orders of magnitude. Incorporating the full wave physics is especially crucial for detecting spectral and polarization information that is discarded by geometric optics and scalar diffraction theory.