Comb-based photonic neural population for parallel and nonlinear processing  

作　　者：BOWEN MA JUNFENG ZHANG WEIWEN ZOU 

机构地区：[1]State Key Laboratory of Advanced Optical Communication Systems and Networks,Intelligent Microwave Lightwave Integration Innovation Center(imLic),Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《Photonics Research》2022年第1期174-182,共9页光子学研究（英文版）

基　　金：National Key Research and Development Program of China (2019YFB2203700);National Natural Science Foundation of China (61822508)。

摘　　要：It is believed that neural information representation and processing relies on the neural population instead of a single neuron.In neuromorphic photonics,photonic neurons in the form of nonlinear responses have been extensively studied in single devices and temporal nodes.However,to construct a photonic neural population(PNP),the process of scaling up and massive interconnections remain challenging considering the physical complexity and response latency.Here,we propose a comb-based PNP interconnected by carrier coupling with superior scalability.Two unique properties of neural population are theoretically and experimentally demonstrated in the comb-based PNP,including nonlinear response curves and population activities coding.A classification task of three input patterns with dual radio-frequency(RF) tones is successfully implemented in a time-efficient manner,which allows the comb-based PNP to make effective use of the ultra-broad bandwidth of photonics for parallel and nonlinear processing.

关 键 词：nonlinear SCALING NEURAL 

分 类 号：O43[机械工程—光学工程]