All-optical computing based on convolutional neural networks

作     者：Kun Liao Ye Chen Zhongcheng Yu Xiaoyong Hu Xingyuan Wang Cuicui Lu Hongtao Lin Qingyang Du Juejun Hu Qihuang Gong Kun Liao;Ye Chen;Zhongcheng Yu;Xiaoyong Hu;Xingyuan Wang;Cuicui Lu;Hongtao Lin;Qingyang Du;Juejun Hu;Qihuang Gong

作者机构：State Key Laboratory for Mesoscopic Physics&Department of PhysicsCollaborative Innovation Center of Quantum MatterBeijing Academy of Quantum Information SciencesNano-optoelectronics Frontier Center of Ministry of EducationPeking UniversityBeijing 100871China Collaborative Innovation Center of Extreme OpticsShanxi UniversityTaiyuan 030006China College of Mathematics and PhysicsBeijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of TechnologyBeijing 100081China College of Information Science&Electronic EngineeringZhejiang UniversityHangzhou 310027China Department of Materials Science and EngineeringMassachusetts Institute of TechnologyCambridgeMA 02139USA 

出 版 物：《Opto-Electronic Advances》 (光电进展（英文）)

年 卷 期：2021年第4卷第11期

页      面：46-54页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 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：financial supports from the National Key Research and Development Program of China(2018YFB2200403) National Natural Sci-ence Foundation of China(NSFC)(61775003,11734001,91950204,11527901,11604378,91850117) 

主　　题：convolutional neural networks all-optical computing mathematical operations cascaded silicon waveguides 

摘      要：The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-en-ergy-consumption *** computing instruments are pre-dominantly electronic processors,which use elec-trons as information carriers and possess von Neumann architecture featured by physical separation of storage and *** scaling of computing speed is limited not only by data transfer between memory and processing units,but also by RC delay associated with integrated ***,excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption *** photons as information carriers is a promising *** to the weak third-order optical nonlinearity of conventional materials,building integrated photonic com-puting chips under traditional von Neumann architecture has been a ***,we report a new all-optical comput-ing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural *** device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed“weight modulatorsto enable complete phase and amplitude control in each waveguide *** generic device concept can be used for equation solving,multifunctional logic operations as well as many other mathematical *** computing functions including transcendental equation solvers,multifarious logic gate operators,and half-adders were experimentally demonstrated to validate the all-optical computing *** time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per *** approach can be further expan-ded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical comp