Shouvanik Chakrabarti, Andrew M. Childs, S. Hung, Tongyang Li, C. Wang, Xiaodi Wu
{"title":"Quantum Algorithm for Estimating Volumes of Convex Bodies","authors":"Shouvanik Chakrabarti, Andrew M. Childs, S. Hung, Tongyang Li, C. Wang, Xiaodi Wu","doi":"10.1145/3588579","DOIUrl":null,"url":null,"abstract":"Estimating the volume of a convex body is a central problem in convex geometry and can be viewed as a continuous version of counting. We present a quantum algorithm that estimates the volume of an n-dimensional convex body within multiplicative error ε using Õ(n3 + n2.5/ε) queries to a membership oracle and Õ(n5+n4.5/ε) additional arithmetic operations. For comparison, the best known classical algorithm uses Õ(n3.5+n3/ε2) queries and Õ(n5.5+n5/ε2) additional arithmetic operations. To the best of our knowledge, this is the first quantum speedup for volume estimation. Our algorithm is based on a refined framework for speeding up simulated annealing algorithms that might be of independent interest. This framework applies in the setting of “Chebyshev cooling,” where the solution is expressed as a telescoping product of ratios, each having bounded variance. We develop several novel techniques when implementing our framework, including a theory of continuous-space quantum walks with rigorous bounds on discretization error. To complement our quantum algorithms, we also prove that volume estimation requires Ω (√ n+1/ε) quantum membership queries, which rules out the possibility of exponential quantum speedup in n and shows optimality of our algorithm in 1/ε up to poly-logarithmic factors.","PeriodicalId":365166,"journal":{"name":"ACM Transactions on Quantum Computing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Quantum Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3588579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Estimating the volume of a convex body is a central problem in convex geometry and can be viewed as a continuous version of counting. We present a quantum algorithm that estimates the volume of an n-dimensional convex body within multiplicative error ε using Õ(n3 + n2.5/ε) queries to a membership oracle and Õ(n5+n4.5/ε) additional arithmetic operations. For comparison, the best known classical algorithm uses Õ(n3.5+n3/ε2) queries and Õ(n5.5+n5/ε2) additional arithmetic operations. To the best of our knowledge, this is the first quantum speedup for volume estimation. Our algorithm is based on a refined framework for speeding up simulated annealing algorithms that might be of independent interest. This framework applies in the setting of “Chebyshev cooling,” where the solution is expressed as a telescoping product of ratios, each having bounded variance. We develop several novel techniques when implementing our framework, including a theory of continuous-space quantum walks with rigorous bounds on discretization error. To complement our quantum algorithms, we also prove that volume estimation requires Ω (√ n+1/ε) quantum membership queries, which rules out the possibility of exponential quantum speedup in n and shows optimality of our algorithm in 1/ε up to poly-logarithmic factors.