Advanced all-optical classification using orbitalangular-momentum-encoded diffractive networks  

作　　者：Kuo Zhang Kun Liao Haohang Cheng Shuai Feng Xiaoyong Hu 

机构地区：[1]Minzu University of China,School of Science,Beijing,China [2]Peking University,Collaborative Innovation Center of Quantum Matter,Nano-Optoelectronics Frontier Center of Ministry of Education,State Key Laboratory for Mesoscopic Physics,Department of Physics,Beijing,China [3]Shanxi University,Collaborative Innovation Center of Extreme Optics,Taiyuan,China [4]Peking University Yangtze Delta Institute of Optoelectronics,Nantong,China

出　　处：《Advanced Photonics Nexus》2023年第6期51-64,共14页先进光子学通讯（英文）

基　　金：supported by the National Key Research and Development Program of China(Grant Nos.2021YFB2800604,2021YFB2800302,and 2018YFB2200403);the National Natural Science Foundation of China(Grant Nos.12274478,91950204,and 92150302);the Graduate Research and Practice Projects of Minzu University of China.

摘　　要：As a successful case of combining deep learning with photonics,the research on optical machine learning has recently undergone rapid development.Among various optical classification frameworks,diffractive networks have been shown to have unique advantages in all-optical reasoning.As an important property of light,the orbital angular momentum(OAM)of light shows orthogonality and mode-infinity,which can enhance the ability of parallel classification in information processing.However,there have been few all-optical diffractive networks under the OAM mode encoding.Here,we report a strategy of OAM-encoded diffractive deep neural network(OAM-encoded D2NN)that encodes the spatial information of objects into the OAM spectrum of the diffracted light to perform all-optical object classification.We demonstrated three different OAM-encoded D2NNs to realize(1)single detector OAM-encoded D2NN for single task classification,(2)single detector OAM-encoded D2NN for multitask classification,and(3)multidetector OAM-encoded D2NN for repeatable multitask classification.We provide a feasible way to improve the performance of all-optical object classification and open up promising research directions for D2NN by proposing OAMencoded D2NN.

关 键 词：diffractive deep neural network deep learning orbital angular momentum multiplexing optical classification 

分 类 号：TN2[电子电信—物理电子学]