Single-layer spatial analog meta-processor for imaging processing

TLDR

Computational meta‑optics and metasurfaces enable ultrafast, low‑power, parallel optical processing, but nonlocal or multilayer designs are limited by constrained operations or large footprints. The authors present a Fourier‑based metaprocessor that imparts customizable, highly flexible transfer functions on a single‑layer Huygens metasurface for analog computing. The device performs basic mathematical operations—including differentiation and cross‑correlation—by directly modulating complex wavefronts in the spatial Fourier domain. These operations enable edge detection and pattern recognition, demonstrating an ultracompact, powerful kernel processor with promising applications in optical analog computing and image processing.

Abstract

Abstract Computational meta-optics brings a twist on the accelerating hardware with the benefits of ultrafast speed, ultra-low power consumption, and parallel information processing in versatile applications. Recent advent of metasurfaces have enabled the full manipulation of electromagnetic waves within subwavelength scales, promising the multifunctional, high-throughput, compact and flat optical processors. In this trend, metasurfaces with nonlocality or multi-layer structures are proposed to perform analog optical computations based on Green’s function or Fourier transform, intrinsically constrained by limited operations or large footprints/volume. Here, we showcase a Fourier-based metaprocessor to impart customized highly flexible transfer functions for analog computing upon our single-layer Huygens’ metasurface. Basic mathematical operations, including differentiation and cross-correlation, are performed by directly modulating complex wavefronts in spatial Fourier domain, facilitating edge detection and pattern recognition of various image processing. Our work substantiates an ultracompact and powerful kernel processor, which could find important applications for optical analog computing and image processing.