Meta-optics for spatial optical analog computing

TL;DR

This paper reviews recent advances in meta-optics for spatial optical analog computing, highlighting fundamental approaches, experimental demonstrations, challenges, and future directions in this innovative field.

Contribution

It provides a comprehensive overview of computational meta-structures for optical computing, emphasizing new methods, experimental results, and future research pathways.

Findings

Demonstrated optical surfaces for solving mathematical problems

Reviewed approaches based on Fourier transformation and Green's function

Identified challenges and potential solutions in computational meta-optics

Abstract

Rapidly growing demands for high-performance computing, powerful data processing systems, and big data necessitate the advent of novel optical devices to perform demanding computing processes effectively. Due to its unprecedented growth in the past two decades, the field of meta-optics offers a viable solution for spatially, spectrally, and/or even temporally sculpting amplitude, phase, polarization, and/or dispersion of optical wavefronts. In this Review, we discuss state-of-the-art developments as well as emerging trends in computational meta-structures as disruptive platforms for spatial optical analog computation. Two fundamental approaches based on general concepts of spatial Fourier transformation and Green's function are discussed in detail. Moreover, numerical investigations and experimental demonstrations of computational optical surfaces and meta-structures for solving a diverse set of mathematical problems (e.g., integro-differentiation and convolution equations) necessary for on-demand applications (e.g., edge detection) are reviewed. Finally, we explore the current challenges and the potential resolutions in computational meta-optics followed by our perspective on future research directions and possible developments in this promising area.