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research article

Holographic multiplexing metasurface with twisted diffractive neural network

Fan, Zhixiang
•
Qian, Chao
•
Jia, Yuetian
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December 1, 2024
Nature Communications

As the cornerstone of AI generated content, data drives human-machine interaction and is essential for developing sophisticated deep learning agents. Nevertheless, the associated data storage poses a formidable challenge from conventional energy-intensive planar storage, high maintenance cost, and the susceptibility to electromagnetic interference. In this work, we introduce the concept of metasurface disk, meta-disk, to expand the capacity limits of optical holographic storage by leveraging uncorrelated structural twist. We develop a physical twisted neural network to describe the optical behavior of the meta-disk and conduct a comprehensive lateral error analysis, where the meta-disk stores large volumes of information through internal structural multiplexing. Two-layer 640 µm x 640 µm meta-disk is sufficient to store over hundreds of high-fidelity images with SSIM of 0.8. By harnessing advanced three-dimensional (3D) printing technology, optical holographic storage is experimentally demonstrated with Pancharatnam-Berry metasurfaces. Our technology provides essential backing for the next generation of optical storage, display, encryption, and multifunctional optical analog computing.

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Type
research article
DOI
10.1038/s41467-024-53749-6
Scopus ID

2-s2.0-85208291814

PubMed ID

39482288

Author(s)
Fan, Zhixiang

Zhejiang University

Qian, Chao

Zhejiang University

Jia, Yuetian

Zhejiang University

Feng, Yiming

Zhejiang University

Qian, Haoliang

Zhejiang University

Li, Er Ping

Zhejiang University

Fleury, Romain  

École Polytechnique Fédérale de Lausanne

Chen, Hongsheng

Zhejiang University

Date Issued

2024-12-01

Publisher

Nature Research

Published in
Nature Communications
Volume

15

Issue

1

Article Number

9416

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LWE  
FunderFunding(s)Grant NumberGrant URL

Top-Notch Young Talents Program of China

Fundamental Research Funds for the Central Universities

Ministry of Science and Technology

2022YFA1404704,2022YFA1404902,2022YFA1405200

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Available on Infoscience
January 25, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/244067
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