{"title":"组合优化绝热量子系统的实验评价","authors":"Catherine C. McGeoch, Cong Wang","doi":"10.1145/2482767.2482797","DOIUrl":null,"url":null,"abstract":"This paper describes an experimental study of a novel computing system (algorithm plus platform) that carries out quantum annealing, a type of adiabatic quantum computation, to solve optimization problems. We compare this system to three conventional software solvers, using instances from three NP-hard problem domains. We also describe experiments to learn how performance of the quantum annealing algorithm depends on input.","PeriodicalId":430420,"journal":{"name":"ACM International Conference on Computing Frontiers","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"152","resultStr":"{\"title\":\"Experimental evaluation of an adiabiatic quantum system for combinatorial optimization\",\"authors\":\"Catherine C. McGeoch, Cong Wang\",\"doi\":\"10.1145/2482767.2482797\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an experimental study of a novel computing system (algorithm plus platform) that carries out quantum annealing, a type of adiabatic quantum computation, to solve optimization problems. We compare this system to three conventional software solvers, using instances from three NP-hard problem domains. We also describe experiments to learn how performance of the quantum annealing algorithm depends on input.\",\"PeriodicalId\":430420,\"journal\":{\"name\":\"ACM International Conference on Computing Frontiers\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"152\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM International Conference on Computing Frontiers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2482767.2482797\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM International Conference on Computing Frontiers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2482767.2482797","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Experimental evaluation of an adiabiatic quantum system for combinatorial optimization
This paper describes an experimental study of a novel computing system (algorithm plus platform) that carries out quantum annealing, a type of adiabatic quantum computation, to solve optimization problems. We compare this system to three conventional software solvers, using instances from three NP-hard problem domains. We also describe experiments to learn how performance of the quantum annealing algorithm depends on input.