| Home > Publications database > Correction: Benchmarking quantum annealing with maximum cardinality matching problems > print |
| 001 | 1051620 | ||
| 005 | 20260116204431.0 | ||
| 024 | 7 | _ | |a 10.3389/fcomp.2025.1744088 |2 doi |
| 024 | 7 | _ | |a 10.34734/FZJ-2026-00542 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2026-00542 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Vert, Daniel |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Correction: Benchmarking quantum annealing with maximum cardinality matching problems |
| 260 | _ | _ | |a Lausanne |c 2025 |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 1768575485_21098 |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) witha focus on the impact of the embedding of problems onto the differenttopologies of the D-Wave quantum annealers. The series of problems we studyare especially designed instances of the maximum cardinality matching problemthat 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, wesimulate the QA process by numerically solving the time-dependent Schrödingerequation. We find that the embedded problems can be significantly moredifficult than the unembedded problems, and some parameters, such as thechain strength, can be very impactful for finding the optimal solution. Thus,finding a good embedding and optimal parameter values can improve theresults considerably. Interestingly, we find that although SA succeeds for theunembedded problems, the SA results obtained for the embedded versionscale quite poorly in comparison with what we can achieve on the D-Wavequantum 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 EXC 2004: Matter and Light for Quantum Computing (ML4Q) (390534769) |0 G:(BMBF)390534769 |c 390534769 |x 2 |
| 536 | _ | _ | |a DFG project G:(GEPRIS)390534769 - EXC 2004: Materie und Licht für Quanteninformation (ML4Q) (390534769) |0 G:(GEPRIS)390534769 |c 390534769 |x 3 |
| 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-HGF)0 |b 2 |
| 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.2025.1744088 |g Vol. 7, p. 1744088 |0 PERI:(DE-600)3010036-7 |p 1744088 |t Frontiers in computer science |v 7 |y 2025 |x 2624-9898 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/1051620/files/Correction%20%28not%20the%20full%20article%29.pdf |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/1051620/files/Original%20publication.pdf |
| 909 | C | O | |o oai:juser.fz-juelich.de:1051620 |p openaire |p open_access |p VDB |p driver |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 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 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-12 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0112 |2 StatID |b Emerging Sources Citation Index |d 2024-12-12 |
| 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)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 Fees |0 StatID:(DE-HGF)0700 |2 StatID |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 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Anonymous peer review |d 2023-12-08T13:21:54Z |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |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)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2024-12-12 |
| 920 | _ | _ | |l yes |
| 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 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|