A brief review of integrated and passive photonic reservoir computing systems and an approach for achieving extra non-linearity in passive devices

作     者：Dachuan WU Yasha YI Yuxiao ZHANG Dachuan WU;Yasha YI;Yuxiao ZHANG

作者机构：Integrated Nano Optoelectronics Laboratory Department of Electrical and Computer Engineering University of Michigan Energy Institute University of Michigan 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2020年第63卷第6期

页      面：97-104页

核心收录：

学科分类：080903[工学-微电子学与固体电子学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 080501[工学-材料物理与化学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Science Foundation (Grant No. NSF-1710885) 

主　　题：reservoir computing integrated photonics neural network non-linearity 

摘      要：Photonic-based reservoir computing(RC) systems have attracted significant attention. Integrated and purely passive systems are compatible with complementary metal-oxide-semiconductor devices,but are limited by the lack of non-linear components. This study consists of two parts: firstly, a review on the published integrated and passive RC system is presented. The review focuses on the structural configuration(rather than the mathematical model) of the neural network; secondly, a new approach for achieving an integrated and passive photonic RC system is introduced and discussed. This approach employs a mode combiner in front of the reservoir to achieve an extra non-linearity in a purely passive device. Moreover,the approach is numerically investigated, and an XOR(exclusive or) task is used to test the device, and the result shows that the new approach satisfies the requirement of an RC system.