{"title":"Experimental demonstration of reservoir computing with a silicon resonator and time multiplexing","authors":"M. Borghi, S. Biasi, Lorenzo Pavesi","doi":"10.1109/GFP51802.2021.9673869","DOIUrl":null,"url":null,"abstract":"Reservoir computing (RC) replaces the backbone of deep neural networks with the dynamics of a complex physical system in which only the output synapses are trained. Optical phenomena form a natural substrate for these architectures, while integrated optics can be used to enhance the nonlinear effects. Here, we propose and experimentally validate an all optical RC scheme based on a silicon on insulator microresonator (MR) and time multiplexing. We give proof of concept demonstrations of RC by solving two nontrivial tasks: the delayed XOR and the classification of the Iris flowers dataset. The approach could be scaled up to realize large hybrid spatio-temporal reservoirs of increased computational speed and complexity.","PeriodicalId":158770,"journal":{"name":"2021 IEEE 17th International Conference on Group IV Photonics (GFP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 17th International Conference on Group IV Photonics (GFP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GFP51802.2021.9673869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Reservoir computing (RC) replaces the backbone of deep neural networks with the dynamics of a complex physical system in which only the output synapses are trained. Optical phenomena form a natural substrate for these architectures, while integrated optics can be used to enhance the nonlinear effects. Here, we propose and experimentally validate an all optical RC scheme based on a silicon on insulator microresonator (MR) and time multiplexing. We give proof of concept demonstrations of RC by solving two nontrivial tasks: the delayed XOR and the classification of the Iris flowers dataset. The approach could be scaled up to realize large hybrid spatio-temporal reservoirs of increased computational speed and complexity.