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Dynamic recognition and mirage using neuro-metamaterials

Author

Listed:
  • Chao Qian

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Zhedong Wang

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Haoliang Qian

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Tong Cai

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Bin Zheng

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Xiao Lin

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Yichen Shen

    (Lightelligence Inc.)

  • Ido Kaminer

    (Technion–Israel Institute of Technology)

  • Erping Li

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

  • Hongsheng Chen

    (Zhejiang University
    Zhejiang University
    Zhejiang University)

Abstract

Breakthroughs in the field of object recognition facilitate ubiquitous applications in the modern world, ranging from security and surveillance equipment to accessibility devices for the visually impaired. Recently-emerged optical computing provides a fundamentally new computing modality to accelerate its solution with photons; however, it still necessitates digital processing for in situ application, inextricably tied to Moore’s law. Here, from an entirely optical perspective, we introduce the concept of neuro-metamaterials that can be applied to realize a dynamic object- recognition system. The neuro-metamaterials are fabricated from inhomogeneous metamaterials or transmission metasurfaces, and optimized using, such as topology optimization and deep learning. We demonstrate the concept in experiments where living rabbits play freely in front of the neuro-metamaterials, which enable to perceive in light speed the rabbits’ representative postures. Furthermore, we show how this capability enables a new physical mechanism for creating dynamic optical mirages, through which a sequence of rabbit movements is converted into a holographic video of a different animal. Our work provides deep insight into how metamaterials could facilitate a myriad of in situ applications, such as illusive cloaking and speed-of-light information display, processing, and encryption, possibly ushering in an “Optical Internet of Things” era.

Suggested Citation

  • Chao Qian & Zhedong Wang & Haoliang Qian & Tong Cai & Bin Zheng & Xiao Lin & Yichen Shen & Ido Kaminer & Erping Li & Hongsheng Chen, 2022. "Dynamic recognition and mirage using neuro-metamaterials," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30377-6
    DOI: 10.1038/s41467-022-30377-6
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    References listed on IDEAS

    as
    1. Jingkai Weng & Yujiang Ding & Chengbo Hu & Xue-Feng Zhu & Bin Liang & Jing Yang & Jianchun Cheng, 2020. "Meta-neural-network for real-time and passive deep-learning-based object recognition," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    2. Nicolas K. Fontaine & Roland Ryf & Haoshuo Chen & David T. Neilson & Kwangwoong Kim & Joel Carpenter, 2019. "Laguerre-Gaussian mode sorter," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    3. Tengfeng Zhu & Yihan Zhou & Yijie Lou & Hui Ye & Min Qiu & Zhichao Ruan & Shanhui Fan, 2017. "Plasmonic computing of spatial differentiation," Nature Communications, Nature, vol. 8(1), pages 1-6, August.
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    Cited by:

    1. Chao Qian & Yi Yang & Yifei Hua & Chan Wang & Xiao Lin & Tong Cai & Dexin Ye & Erping Li & Ido Kaminer & Hongsheng Chen, 2022. "Breaking the fundamental scattering limit with gain metasurfaces," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    2. Jieting Chen & Chao Qian & Jie Zhang & Yuetian Jia & Hongsheng Chen, 2023. "Correlating metasurface spectra with a generation-elimination framework," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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