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dc.contributor.authorBulmer, Jacob FF
dc.contributor.authorBell, Bryn A
dc.contributor.authorChadwick, Rachel S
dc.contributor.authorJones, Alex E
dc.contributor.authorMoise, Diana
dc.contributor.authorRigazzi, Alessandro
dc.contributor.authorThorbecke, Jan
dc.contributor.authorHaus, Utz-Uwe
dc.contributor.authorVan Vaerenbergh, Thomas
dc.contributor.authorPatel, Raj B
dc.contributor.authorWalmsley, Ian A
dc.contributor.authorLaing, Anthony
dc.date.accessioned2022-05-11T02:21:03Z
dc.date.available2022-05-11T02:21:03Z
dc.date.issued2022
dc.identifier.issn2375-2548
dc.identifier.doi10.1126/sciadv.abl9236
dc.identifier.urihttp://hdl.handle.net/10072/414475
dc.description.abstractIdentifying the boundary beyond which quantum machines provide a computational advantage over their classical counterparts is a crucial step in charting their usefulness. Gaussian boson sampling (GBS), in which photons are measured from a highly entangled Gaussian state, is a leading approach in pursuing quantum advantage. State-of-the-art GBS experiments that run in minutes would require 600 million years to simulate using the best preexisting classical algorithms. Here, we present faster classical GBS simulation methods, including speed and accuracy improvements to the calculation of loop hafnians. We test these on a ∼100,000-core supercomputer to emulate GBS experiments with up to 100 modes and up to 92 photons. This reduces the simulation time for state-of-the-art GBS experiments to several months, a nine-orders of magnitude improvement over previous estimates. Last, we introduce a distribution that is efficient to sample from classically and that passes a variety of GBS validation methods.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherThe American Association for the Advancement of Science
dc.relation.ispartofissue4
dc.relation.ispartofjournalScience Advances
dc.relation.ispartofvolume8
dc.subject.fieldofresearchQuantum computation
dc.subject.fieldofresearchcode461307
dc.subject.keywordsScience & Technology
dc.subject.keywordsMultidisciplinary Sciences
dc.subject.keywordsScience & Technology - Other Topics
dc.subject.keywordsPERFORMANCE
dc.subject.keywordsquant-ph
dc.titleThe boundary for quantum advantage in Gaussian boson sampling
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationBulmer, JFF; Bell, BA; Chadwick, RS; Jones, AE; Moise, D; Rigazzi, A; Thorbecke, J; Haus, U-U; Van Vaerenbergh, T; Patel, RB; Walmsley, IA; Laing, A, The boundary for quantum advantage in Gaussian boson sampling, Science Advances, 2022, 8 (4)
dcterms.licensehttps://creativecommons.org/licenses/by/4.0/
dc.date.updated2022-05-10T23:41:14Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).
gro.hasfulltextFull Text
gro.griffith.authorPatel, Raj B.


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