Performing optical logic operations by a diffractive neural network

Chao Qian; Xiao Lin; Xiaobin Lin; Jian Xu; Yang Sun; Erping Li; Baile Zhang; Hongsheng Chen

doi:10.1038/s41377-020-0303-2

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Performing optical logic operations by a diffractive neural network

Original Articles

- Performing optical logic operations by a diffractive neural network
- Light: Science & Applications Vol. 9, Issue 3, Pages: 620-626(2020)
- Affiliations：
  
  1.Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, College of Information Science and Electronic Engineering, Zhejiang University, 310027 Hangzhou, China
  2.ZJU-Hangzhou Global Science and Technology Innovation Center, Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang, Zhejiang University, 310027 Hangzhou, China
  3.Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
  4.ZJU-UIUC Institute, Zhejiang University, 310027 Hangzhou, China
  5.Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
- Author bio：
  
  Xiao Lin (xiaolinbnwj@ntu.edu.sg)
  Baile Zhang (blzhang@ntu.edu.sg)
  Hongsheng Chen(hansomchen@zju.edu.cn)
- Funds：
- DOI：10.1038/s41377-020-0303-2
  CLC：
- Published：2020，
  
  Published Online：13 April 2020，
  
  Received：25 November 2019，
  
  Revised：19 March 2020，
  
  Accepted：24 March 2020
- Accepted：
Scan QR Code
Qian, C. et al. Performing optical logic operations by a diffractive neural network. Light: Science & Applications, 9, 620-626 (2020).
DOI：

Qian, C. et al. Performing optical logic operations by a diffractive neural network. Light: Science & Applications, 9, 620-626 (2020). DOI： 10.1038/s41377-020-0303-2.

摘要

Abstract

Optical logic operations lie at the heart of optical computing

and they enable many applications such as ultrahigh-speed information processing. However

the reported optical logic gates rely heavily on the precise control of input light signals

including their phase difference

polarization

and intensity and the size of the incident beams. Due to the complexity and difficulty in these precise controls

the two output optical logic states may suffer from an inherent instability and a low contrast ratio of intensity. Moreover

the miniaturization of optical logic gates becomes difficult if the extra bulky apparatus for these controls is considered. As such

it is desirable to get rid of these complicated controls and to achieve full logic functionality in a compact photonic system. Such a goal remains challenging. Here

we introduce a simple yet universal design strategy

capable of using plane waves as the incident signal

to perform optical logic operations via a diffractive neural network. Physically

the incident plane wave is first spatially encoded by a specific logic operation at the input layer and

further decoded through the hidden layers

namely

a compound Huygens' metasurface. That is

the judiciously designed metasurface scatters the encoded light into one of two small designated areas at the output layer

which provides the information of output logic states. Importantly

after training of the diffractive neural network

all seven

basic types of optical logic operations can be realized by the same metasurface. As a conceptual illustration

three logic operations (NOT

and AND) are experimentally demonstrated at microwave frequencies.

关键词

Keywords

references

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