{"title":"通过优化的双量子位非选择性测量连接的两个量子库的计算","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":"{\"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}","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}
Computing with two quantum reservoirs connected via optimized two-qubit nonselective measurements
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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