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
Xiao Lin (xiaolinbnwj@ntu.edu.sg)
Baile Zhang (blzhang@ntu.edu.sg)
Hongsheng Chen(hansomchen@zju.edu.cn)
纸质出版日期:2020,
网络出版日期:2020-04-13,
收稿日期:2019-11-25,
修回日期:2020-03-19,
录用日期:2020-03-24
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Performing optical logic operations by a diffractive neural network[J]. LSA, 2020,9(3):620-626.
Qian, C. et al. Performing optical logic operations by a diffractive neural network. Light: Science & Applications, 9, 620-626 (2020).
Performing optical logic operations by a diffractive neural network[J]. LSA, 2020,9(3):620-626. DOI: 10.1038/s41377-020-0303-2.
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.
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
OR
and AND) are experimentally demonstrated at microwave frequencies.
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