Flat optics for analog computing: from fundamental mechanisms to advanced meta-processors
Abstract
As the explosive growth of visual data increasingly strains the latency and energy limits of conventional electronic computing, optical analog computing has re-emerged as a disruptive paradigm for zero-power, speed-of-light information processing. Propelled by the unprecedented wave-manipulation capabilities of optical metasurfaces, this field is undergoing a rapid transition from macroscopic physical optics to ultra-compact, on-chip meta-processors. This Review examines the fundamental mechanisms of metasurface-empowered optical computing spanning Fourier-domain, nonlocal spatial-domain, and interferometric architectures that perform mathematical operations, with a particular focus on spatial differentiation and edge detection as representative computing tasks. By emphasizing recent breakthroughs, we highlight the evolution of meta-processors from static, linear regimes to dynamically reconfigurable, nonlinear, and quantum-assisted multidimensional platforms. We also envision how the synergy of AI-driven inverse design and the integration of analog meta-front-ends with optical neural networks will synergistically revolutionize next-generation intelligent machine vision.
Cite
@article{arxiv.2604.16849,
title = {Flat optics for analog computing: from fundamental mechanisms to advanced meta-processors},
author = {Tingting Liu and Jumin Qiu and Xintong Shi and Qiegen Liu and Shuyuan Xiao},
journal= {arXiv preprint arXiv:2604.16849},
year = {2026}
}