• Advanced Photonics Nexus
  • Vol. 4, Issue 1, 016010 (2025)
Jianan Feng1、2, Chang Li1、2, Dahai Yang3、4, Yang Liu1、2, Jianyang Hu1、2, Chen Chen5, Yiqun Wang5, Jie Lin1、6、*, Lei Wang2, and Peng Jin1、2、*
Author Affiliations
  • 1Harbin Institute of Technology, Ministry of Education, Key Laboratory of Micro-systems and Micro-structures Manufacturing, Harbin, China
  • 2Harbin Institute of Technology, School of Instrumentation Science and Engineering, Harbin, China
  • 3Great Bay University, School of Physical Sciences, Dongguan, China
  • 4Great Bay University, Great Bay Institute for Advanced Study, Dongguan, China
  • 5Chinese Academy of Sciences, Suzhou Institute of Nano-Tech and Nano-Bionics, Suzhou, China
  • 6Harbin Institute of Technology, School of Physics, Harbin, China
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    DOI: 10.1117/1.APN.4.1.016010 Cite this Article Set citation alerts
    Jianan Feng, Chang Li, Dahai Yang, Yang Liu, Jianyang Hu, Chen Chen, Yiqun Wang, Jie Lin, Lei Wang, Peng Jin, "Compact planar-waveguide integrated diffractive optical neural network chip," Adv. Photon. Nexus 4, 016010 (2025) Copy Citation Text show less

    Abstract

    Diffractive optical neural networks (DONNs) have exhibited the advantages of parallelization, high speed, and low consumption. However, the existing DONNs based on free-space diffractive optical elements are bulky and unsteady. In this study, we propose a planar-waveguide integrated diffractive neural network chip architecture. The three diffractive layers are engraved on the same side of a quartz wafer. The three-layer chip is designed with 32-mm3 processing space and enables a computing speed of 3.1 × 109 Tera operations per second. The results show that the proposed chip achieves 73.4% experimental accuracy for the Modified National Institute of Standards and Technology database while showing the system’s robustness in a cycle test. The consistency of experiments is 88.6%, and the arithmetic mean standard deviation of the results is ~4.7%. The proposed chip architecture can potentially revolutionize high-resolution optical processing tasks with high robustness.
    Uout(x,y)=F1{F{Uin(x,y)}H(ξ,η)},

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    H(ξ,η)=exp[jkz1λ2(ξ2+η2)],

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    Uout(x,y)=F1{F{t(xi,yi)exp(jkwxsinθ)}H(ξ,η)},

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    Jianan Feng, Chang Li, Dahai Yang, Yang Liu, Jianyang Hu, Chen Chen, Yiqun Wang, Jie Lin, Lei Wang, Peng Jin, "Compact planar-waveguide integrated diffractive optical neural network chip," Adv. Photon. Nexus 4, 016010 (2025)
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