001     1027544
005     20250401102819.0
024 7 _ |a 10.3389/fcomp.2024.1286057
|2 doi
024 7 _ |a 10.34734/FZJ-2024-03947
|2 datacite_doi
024 7 _ |a WOS:001249804500001
|2 WOS
037 _ _ |a FZJ-2024-03947
082 _ _ |a 004
100 1 _ |a Vert, Daniel
|0 P:(DE-HGF)0
|b 0
245 _ _ |a Benchmarking quantum annealing with maximum cardinality matching problems
260 _ _ |a Lausanne
|c 2024
|b Frontiers Media
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 1721651232_3862
|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 Quantum Annealing (QA) vs. Simulated Annealing (SA) with a focus on the impact of the embedding of problems onto the different topologies of the D-Wave quantum annealers. The series of problems we study are especially designed instances of the maximum cardinality matching problem that are easy to solve classically but difficult for SA and, as found experimentally, not easy for QA either. In addition to using several D-Wave processors, we simulate the QA process by numerically solving the time-dependent Schrödinger equation. We find that the embedded problems can be significantly more difficult than the unembedded problems, and some parameters, such as the chain strength, can be very impactful for finding the optimal solution. Thus, finding a good embedding and optimal parameter values can improve the results considerably. Interestingly, we find that although SA succeeds for the unembedded problems, the SA results obtained for the embedded version scale quite poorly in comparison with what we can achieve on the D-Wave quantum annealers.
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 AIDAS - Joint Virtual Laboratory for AI, Data Analytics and Scalable Simulation (aidas_20200731)
|0 G:(DE-Juel-1)aidas_20200731
|c aidas_20200731
|x 1
536 _ _ |a DFG project 390534769 - EXC 2004: Materie und Licht für Quanteninformation (ML4Q) (390534769)
|0 G:(GEPRIS)390534769
|c 390534769
|x 2
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Willsch, Madita
|0 P:(DE-Juel1)167543
|b 1
|u fzj
700 1 _ |a Yenilen, Berat
|0 P:(DE-Juel1)195771
|b 2
|u fzj
700 1 _ |a Sirdey, Renaud
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Louise, Stéphane
|0 P:(DE-HGF)0
|b 4
|e Corresponding author
700 1 _ |a Michielsen, Kristel
|0 P:(DE-Juel1)138295
|b 5
|e Corresponding author
|u fzj
773 _ _ |a 10.3389/fcomp.2024.1286057
|g Vol. 6, p. 1286057
|0 PERI:(DE-600)3010036-7
|p 1286057
|t Frontiers in computer science
|v 6
|y 2024
|x 2624-9898
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/1027544/files/fcomp-06-1286057.pdf
856 4 _ |y OpenAccess
|x icon
|u https://juser.fz-juelich.de/record/1027544/files/fcomp-06-1286057.gif?subformat=icon
856 4 _ |y OpenAccess
|x icon-1440
|u https://juser.fz-juelich.de/record/1027544/files/fcomp-06-1286057.jpg?subformat=icon-1440
856 4 _ |y OpenAccess
|x icon-180
|u https://juser.fz-juelich.de/record/1027544/files/fcomp-06-1286057.jpg?subformat=icon-180
856 4 _ |y OpenAccess
|x icon-640
|u https://juser.fz-juelich.de/record/1027544/files/fcomp-06-1286057.jpg?subformat=icon-640
909 C O |o oai:juser.fz-juelich.de:1027544
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
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)195771
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|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 2024
915 p c |a APC keys set
|0 PC:(DE-HGF)0000
|2 APC
915 p c |a Local Funding
|0 PC:(DE-HGF)0001
|2 APC
915 p c |a DFG OA Publikationskosten
|0 PC:(DE-HGF)0002
|2 APC
915 p c |a DOAJ Journal
|0 PC:(DE-HGF)0003
|2 APC
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-08-29
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-08-29
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b FRONT COMP SCI-SWITZ : 2022
|d 2024-12-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2023-12-08T13:21:54Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2023-12-08T13:21:54Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2023-12-08T13:21:54Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-12
915 _ _ |a WoS
|0 StatID:(DE-HGF)0112
|2 StatID
|b Emerging Sources Citation Index
|d 2024-12-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-12
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2024-12-12
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a APC
980 1 _ |a APC
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21