Single-layer spatial analog meta-processor for imaging processing

Zhuochao Wang, Guangwei Hu, Xinwei Wang, Xumin Ding (), Kuang Zhang (), Haoyu Li (), Shah Nawaz Burokur (), Qun Wu, Jian Liu, Jiubin Tan and Cheng-Wei Qiu ()
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Zhuochao Wang: Harbin Institute of Technology
Guangwei Hu: National University of Singapore
Xinwei Wang: Harbin Institute of Technology
Xumin Ding: Harbin Institute of Technology
Kuang Zhang: Harbin Institute of Technology
Haoyu Li: Harbin Institute of Technology
Shah Nawaz Burokur: Univ Paris Nanterre
Qun Wu: Harbin Institute of Technology
Jian Liu: Harbin Institute of Technology
Jiubin Tan: Harbin Institute of Technology
Cheng-Wei Qiu: National University of Singapore

Nature Communications, 2022, vol. 13, issue 1, 1-10

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.

Date: 2022
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DOI: 10.1038/s41467-022-29732-4

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