{"title":"Computing with two quantum reservoirs connected via optimized two-qubit nonselective measurements","authors":"S. Vintskevich, D. Grigoriev","doi":"10.1364/quantum.2022.qw2a.48","DOIUrl":null,"url":null,"abstract":"We propose a novel approach to link multipartite quantum systems - quantum reservoirs into a network to implement quantum reservoir computing. We present the machine learning-based heuristics to optimize performance and information transfer between systems.","PeriodicalId":369002,"journal":{"name":"Quantum 2.0 Conference and Exhibition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantum 2.0 Conference and Exhibition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/quantum.2022.qw2a.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We propose a novel approach to link multipartite quantum systems - quantum reservoirs into a network to implement quantum reservoir computing. We present the machine learning-based heuristics to optimize performance and information transfer between systems.
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