Chip-Based High-Dimensional Optical Neural Network

查看全文 作　　者：Xinyu [1]Wang;Peng [2]Xie;Bohan [2]Chen;Xingcai [3,4]Zhang

机构地区：[1]School of Future Technology,University of Chinese Academy of Sciences,Beijing 100049,China;[2]Department of Engineering Science,University of Oxford,Parks Road,Oxford OX13PJ,UK;[3]School of Engineering,Massachusetts Institute of Technology,Cambridge,MA 02139,USA;[4]John A.Paulson School of Engineering and Applied Sciences,Harvard University,Cambridge,MA 02138,USA

出　　处：《Nano-Micro Letters》索引2022年第14卷第12期,共9页

基　　金：Peng Xie acknowledges the support from the China Scholarship Council(Grant no.201804910829). 摘　　要：Parallel multi-thread processing in advanced intelligent processors is the core to realize high-speed and high-capacity signal processing systems.Optical neural network(ONN)has the native advantages of high parallelization,large bandwidth,and low power consumption to meet the demand of big data.Here,we demonstrate the dual-layer ONN with Mach-Zehnder interferometer(MZI)network and nonlinear layer,while the nonlinear activation function is achieved by optical-electronic signal conversion.Two frequency components from the microcomb source carrying digit datasets are simultaneously imposed and intelligently recognized through the ONN.We successfully achieve the digit classification of different frequency components by demultiplexing the output signal and testing power distribution.Efficient parallelization feasibility with wavelength division multiplexing is demonstrated in our high-dimensional ONN.This work provides a high-performance architecture for future parallel high-capacity optical analog computing. 关键词：Integrated optics Optical neural network High-dimension Mach-Zehnder interferometer Nonlinear activation function Parallel high-capacity analog computing

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Chip-Based High-Dimensional Optical Neural Network

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