Hauptseite > Publikationsdatenbank > Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems > print

001     910748
005     20230626065456.0
024 7 _ |a 10.1007/s11128-022-03476-y
|2 doi
024 7 _ |a 2128/32329
|2 Handle
024 7 _ |a WOS:000777119700001
|2 WOS
037 _ _ |a FZJ-2022-04118
082 _ _ |a 004
100 1 _ |a Willsch, Dennis
|0 P:(DE-Juel1)167542
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems
260 _ _ |a Dordrecht
|c 2022
|b Springer Science + Business Media B.V.
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1667476426_8821
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a We benchmark the quantum processing units of the largest quantum annealers to date, the 5000+ qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q, using tail assignment and exact cover problems from aircraft scheduling scenarios. The benchmark set contains small, intermediate, and large problems with both sparsely connected and almost fully connected instances. We find that Advantage outperforms D-Wave 2000Q for almost all problems, with a notable increase in success rate and problem size. In particular, Advantage is also able to solve the largest problems with 120 logical qubits that D-Wave 2000Q cannot solve anymore. Furthermore, problems that can still be solved by D-Wave 2000Q are solved faster by Advantage. We find, however, that D-Wave 2000Q can achieve better success rates for sparsely connected problems that do not require the many new couplers present on Advantage, so improving the connectivity of a quantum annealer does not per se improve its performance.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 0
536 _ _ |a OpenSuperQ - An Open Superconducting Quantum Computer (820363)
|0 G:(EU-Grant)820363
|c 820363
|f H2020-FETFLAG-2018-03
|x 1
700 1 _ |a Willsch, Madita
|0 P:(DE-Juel1)167543
|b 1
|u fzj
700 1 _ |a Gonzalez Calaza, Carlos Daniel
|0 P:(DE-Juel1)171436
|b 2
|u fzj
700 1 _ |a Jin, Fengping
|0 P:(DE-Juel1)144355
|b 3
|u fzj
700 1 _ |a De Raedt, Hans
|0 P:(DE-Juel1)179169
|b 4
|u fzj
700 1 _ |a Svensson, Marika
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Michielsen, Kristel
|0 P:(DE-Juel1)138295
|b 6
|u fzj
773 _ _ |a 10.1007/s11128-022-03476-y
|0 PERI:(DE-600)2088114-9
|p 141
|t Quantum information processing
|v 21
|y 2022
|x 1570-0755
856 4 _ |u https://juser.fz-juelich.de/record/910748/files/Willsch2022_Article_BenchmarkingAdvantageAndD-Wave.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:910748
|p openaire
|p open_access
|p OpenAPC_DEAL
|p driver
|p VDB
|p ec_fundedresources
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)167542
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)167543
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)171436
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)144355
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)179169
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)138295
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 0
914 1 _ |y 2022
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-02-02
915 _ _ |a DEAL Springer
|0 StatID:(DE-HGF)3002
|2 StatID
|d 2021-02-02
|w ger
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-02-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2022-11-12
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b QUANTUM INF PROCESS : 2021
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2022-11-12
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2022-11-12
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2022-11-12
915 p c |a APC keys set
|2 APC
|0 PC:(DE-HGF)0000
915 p c |a Local Funding
|2 APC
|0 PC:(DE-HGF)0001
915 p c |a DFG OA Publikationskosten
|2 APC
|0 PC:(DE-HGF)0002
915 p c |a DEAL: Springer Nature 2020
|2 APC
|0 PC:(DE-HGF)0113
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a APC

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21