Ultracompact meta-imagers for arbitrary all-optical convolution

Weiwei Fu; Dong Zhao; Ziqin Li; Songde Liu; Chao Tian; Kun Huang

doi:10.1038/s41377-022-00752-5

Light: Science & Applications (Mar 2022)

Ultracompact meta-imagers for arbitrary all-optical convolution

Weiwei Fu,
Dong Zhao,
Ziqin Li,
Songde Liu,
Chao Tian,
Kun Huang

Affiliations

Weiwei Fu: Department of Optics and Optical Engineering, University of Science and Technology of China
Dong Zhao: Department of Optics and Optical Engineering, University of Science and Technology of China
Ziqin Li: Department of Optics and Optical Engineering, University of Science and Technology of China
Songde Liu: Institute of Artificial Intelligence, Hefei Comprehensive National Science Center
Chao Tian: Institute of Artificial Intelligence, Hefei Comprehensive National Science Center
Kun Huang: Department of Optics and Optical Engineering, University of Science and Technology of China

DOI: https://doi.org/10.1038/s41377-022-00752-5
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 13

Abstract

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An ultra-compact metasurface-based imager with modified point spread function is demonstrated to realize arbitrary all-optical parallel picture convolution that is highly compatible to convolutional neural network.

Published in Light: Science & Applications

ISSN: 2047-7538 (Online)
Publisher: Nature Publishing Group
Country of publisher: United Kingdom
LCC subjects: Technology: Engineering (General). Civil engineering (General): Applied optics. Photonics; Science: Physics: Optics. Light
Website: https://www.nature.com/lsa/

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