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dc.contributor.authorJi, Zhengfeng
dc.contributor.authorYu, Nengkun
dc.contributor.authorHaah, Jeongwan
dc.contributor.authorWu, Xiaodi
dc.contributor.authorHarrow, Aram W.
dc.date.accessioned2017-07-25T18:59:16Z
dc.date.available2017-07-25T18:59:16Z
dc.date.issued2016-06
dc.identifier.isbn9781450341325
dc.identifier.urihttp://hdl.handle.net/1721.1/110843
dc.description.abstractIt is a fundamental problem to decide how many copies of an unknown mixed quantum state are necessary and sufficient to determine the state. This is the quantum analogue of the problem of estimating a probability distribution given some number of samples. Previously, it was known only that estimating states to error є in trace distance required O(dr2/є2) copies for a d-dimensional density matrix of rank r. Here, we give a measurement scheme (POVM) that uses O( (dr/ δ ) ln(d/δ) ) copies to estimate ρ to error δ in infidelity. This implies O( (dr / є2)· ln(d/є) ) copies suffice to achieve error є in trace distance. For fixed d, our measurement can be implemented on a quantum computer in time polynomial in n. We also use the Holevo bound from quantum information theory to prove a lower bound of Ω(dr/є2)/ log(d/rє) copies needed to achieve error є in trace distance. This implies a lower bound Ω(dr/δ)/log(d/rδ) for the estimation error δ in infidelity. These match our upper bounds up to log factors. Our techniques can also show an Ω(r2d/δ) lower bound for measurement strategies in which each copy is measured individually and then the outcomes are classically post-processed to produce an estimate. This matches the known achievability results and proves for the first time that such “product” measurements have asymptotically suboptimal scaling with d and r.en_US
dc.description.sponsorshipMassachusetts Institute of Technology (MIT Pappalardo Fellowship in Physics)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (grant CCF-1111382)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (grant CCF-1111382)en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada. Discovery Accelerator Supplements Programen_US
dc.description.sponsorshipCRCen_US
dc.description.sponsorshipCanadian Institute for Advanced Researchen_US
dc.description.sponsorshipUnited States. Army Research Office (contract W911NF-12-1-0486)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Waterman Award)en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofhttps://doi.org/10.1145/2897518.2897585en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceHarrowen_US
dc.titleSample-optimal tomography of quantum statesen_US
dc.typeArticleen_US
dc.identifier.citationHaah, Jeongwan, Aram W. Harrow, Zhengfeng Ji, Xiaodi Wu, and Nengkun Yu. “Sample-Optimal Tomography of Quantum States.” Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016 (2016).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Theoretical Physicsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mathematicsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physicsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Nuclear Scienceen_US
dc.contributor.approverHarrow, Aram W.en_US
dc.contributor.mitauthorHaah, Jeongwan
dc.contributor.mitauthorHarrow, Aram W
dc.contributor.mitauthorWu, Xiaodi
dc.relation.journalProceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing - STOC 2016en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsHaah, Jeongwan; Harrow, Aram W.; Ji, Zhengfeng; Wu, Xiaodi; Yu, Nengkunen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-4420-4932
dc.identifier.orcidhttps://orcid.org/0000-0003-3220-7682
dc.identifier.orcidhttps://orcid.org/0000-0002-0094-9510
mit.licenseOPEN_ACCESS_POLICYen_US


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