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dc.contributor.authorGhafari, Farzad
dc.contributor.authorTischler, Nora
dc.contributor.authorThompson, Jayne
dc.contributor.authorGu, Mile
dc.contributor.authorShalm, Lynden K
dc.contributor.authorVerma, Varun B
dc.contributor.authorNam, Sae Woo
dc.contributor.authorPatel, Raj B
dc.contributor.authorWiseman, Howard M
dc.contributor.authorPryde, Geoff J
dc.date.accessioned2019-12-04T01:11:31Z
dc.date.available2019-12-04T01:11:31Z
dc.date.issued2019
dc.identifier.issn2160-3308
dc.identifier.doi10.1103/PhysRevX.9.041013
dc.identifier.urihttp://hdl.handle.net/10072/389477
dc.description.abstractStochastic processes underlie a vast range of natural and social phenomena. Some processes such as atomic decay feature intrinsic randomness, whereas other complex processes, e.g., traffic congestion, are effectively probabilistic because we cannot track all relevant variables. To simulate a stochastic system's future behavior, information about its past must be stored, and thus memory is a key resource. Quantum information processing promises a memory advantage for stochastic simulation. Here, we report the first experimental demonstration that a quantum stochastic simulator can encode the required information in fewer dimensions than any classical simulator, thereby achieving a quantum advantage in minimal memory requirements using an individual simulator. This advantage is in contrast to recent proof-of-concept experiments, where the memory saving would only become accessible in the limit of a large number of parallel simulations. In those examples, the minimal memory registers of individual quantum simulators had the same dimensionality as their classical counterparts. Our photonic experiment thus establishes the potential of new, practical resource savings in the simulation of complex systems.
dc.description.peerreviewedYes
dc.description.sponsorshipGriffith University
dc.languageEnglish
dc.language.isoeng
dc.publisherAmerican Physical Society
dc.relation.ispartofpagefrom041013:1
dc.relation.ispartofpageto041013:8
dc.relation.ispartofissue4
dc.relation.ispartofjournalPhysical Review X
dc.relation.ispartofvolume9
dc.subject.fieldofresearchAstronomical and Space Sciences
dc.subject.fieldofresearchCondensed Matter Physics
dc.subject.fieldofresearchQuantum Physics
dc.subject.fieldofresearchcode0201
dc.subject.fieldofresearchcode0204
dc.subject.fieldofresearchcode0206
dc.subject.keywordsScience & Technology
dc.subject.keywordsPhysical Sciences
dc.subject.keywordsPhysics, Multidisciplinary
dc.subject.keywordsCOMPUTATIONAL MECHANICS
dc.titleDimensional Quantum Memory Advantage in the Simulation of Stochastic Processes
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationGhafari, F; Tischler, N; Thompson, J; Gu, M; Shalm, LK; Verma, VB; Nam, SW; Patel, RB; Wiseman, HM; Pryde, GJ, Dimensional Quantum Memory Advantage in the Simulation of Stochastic Processes, Physical Review X, 2019, 9 (4), pp. 041013:1-041013:8
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.date.updated2019-12-03T06:10:33Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2019. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
gro.hasfulltextFull Text
gro.griffith.authorPatel, Raj B.
gro.griffith.authorWiseman, Howard M.
gro.griffith.authorPryde, Geoff
gro.griffith.authorTischler, Nora
gro.griffith.authorGhafari Jouneghani, Farzad


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