• Journal of Infrared and Millimeter Waves
  • Vol. 39, Issue 1, 13 (2020)
Hai-Sha NIU1, Ming-Xin YU1, Bo-Fei ZHU2, Qi-Feng YAO1, Qian-Kun ZHANG1, Li-Dan LU1, Guo-Shun ZHONG3, and Lian-Qing ZHU1、*
Author Affiliations
  • 1Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing0092, China
  • 2Beijing ZX Intelligent Chip Technology Co., Ltd., Beijing100876,China
  • 3The 11th Research Institute of China Electronic Science & Technology Group Inc., Beijing100015,China
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    DOI: 10.11972/j.issn.1001-9014.2020.01.003 Cite this Article
    Hai-Sha NIU, Ming-Xin YU, Bo-Fei ZHU, Qi-Feng YAO, Qian-Kun ZHANG, Li-Dan LU, Guo-Shun ZHONG, Lian-Qing ZHU. Design and implementation of diffraction grating based on 10.6μm all-optical depth neural network[J]. Journal of Infrared and Millimeter Waves, 2020, 39(1): 13 Copy Citation Text show less

    Abstract

    The photonic artificial intelligent chip performs calculations at the speed of light, and has the advantages of low power consumption, low delay, and anti-electromagnetic interference. Miniaturization and integration are the key steps to realize this technological innovation. In this paper, lithography is applied to the fabrication of diffraction gratings. A design and implementation method of all-optics diffraction deep learning neural network grating based on 10.6 micron laser is proposed. Since the wavelength of the light source evolved from the millimeter wave to micrometer wave, the characteristic scale of the neuron are reduced to 20 micrometers. Compared with the existing optical computing neural network, the feature size of the deep learning neural network is reduced by 80 times, which laid the foundation for further large-scale integration of photonic computing chips.
    Hai-Sha NIU, Ming-Xin YU, Bo-Fei ZHU, Qi-Feng YAO, Qian-Kun ZHANG, Li-Dan LU, Guo-Shun ZHONG, Lian-Qing ZHU. Design and implementation of diffraction grating based on 10.6μm all-optical depth neural network[J]. Journal of Infrared and Millimeter Waves, 2020, 39(1): 13
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