001047045 001__ 1047045
001047045 005__ 20251129202118.0
001047045 0247_ $$2doi$$a10.1103/8n7p-7lh2
001047045 0247_ $$2ISSN$$a2470-0045
001047045 0247_ $$2ISSN$$a2470-0061
001047045 0247_ $$2ISSN$$a1063-651X
001047045 0247_ $$2ISSN$$a1095-3787
001047045 0247_ $$2ISSN$$a1538-4519
001047045 0247_ $$2ISSN$$a1539-3755
001047045 0247_ $$2ISSN$$a1550-2376
001047045 0247_ $$2ISSN$$a2470-0053
001047045 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-04091
001047045 037__ $$aFZJ-2025-04091
001047045 041__ $$aEnglish
001047045 082__ $$a530
001047045 1001_ $$00000-0003-1384-0626$$aIrbäck, Anders$$b0$$eCorresponding author
001047045 245__ $$aFolding lattice proteins confined on minimal grids using a quantum-inspired encoding
001047045 260__ $$aWoodbury, NY$$bInst.$$c2025
001047045 3367_ $$2DRIVER$$aarticle
001047045 3367_ $$2DataCite$$aOutput Types/Journal article
001047045 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1764417915_31362
001047045 3367_ $$2BibTeX$$aARTICLE
001047045 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001047045 3367_ $$00$$2EndNote$$aJournal Article
001047045 520__ $$aSteric clashes pose a challenge when exploring dense protein systems using conventional explicit-chain methods. A minimal example is a single lattice protein confined on a minimal grid, with no free sites. Finding its minimum energy is a hard optimization problem, with similarities to scheduling problems. It can be recast as a quadratic unconstrained binary optimization (QUBO) problem amenable to classical and quantum approaches. We show that this problem in its QUBO form can be swiftly and consistently solved for chain length 48, using either classical simulated annealing or hybrid quantum-classical annealing on a D-Wave system. In fact, the latter computations required about 10 s. We also test linear and quadratic programming methods, which work well for a lattice gas but struggle with chain constraints. All methods are benchmarked against exact results obtained from exhaustive structure enumeration, at a high computational cost.
001047045 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001047045 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001047045 7001_ $$00000-0003-1080-200X$$aKnuthson, Lucas$$b1
001047045 7001_ $$0P:(DE-Juel1)132590$$aMohanty, Sandipan$$b2
001047045 773__ $$0PERI:(DE-600)2844562-4$$a10.1103/8n7p-7lh2$$gVol. 112, no. 4, p. 045302$$n4$$p045302$$tPhysical review / E$$v112$$x2470-0045$$y2025
001047045 8564_ $$uhttps://juser.fz-juelich.de/record/1047045/files/8n7p-7lh2.pdf$$yOpenAccess
001047045 8564_ $$uhttps://juser.fz-juelich.de/record/1047045/files/maxcomp.pdf$$yOpenAccess
001047045 909CO $$ooai:juser.fz-juelich.de:1047045$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
001047045 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132590$$aForschungszentrum Jülich$$b2$$kFZJ
001047045 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001047045 9141_ $$y2025
001047045 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)1230$$2StatID$$aDBCoverage$$bCurrent Contents - Electronics and Telecommunications Collection$$d2024-12-10
001047045 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001047045 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001047045 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPHYS REV E : 2022$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-10
001047045 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-10
001047045 920__ $$lyes
001047045 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001047045 980__ $$ajournal
001047045 980__ $$aVDB
001047045 980__ $$aUNRESTRICTED
001047045 980__ $$aI:(DE-Juel1)JSC-20090406
001047045 9801_ $$aFullTexts