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dc.contributor.authorHan, Ki Hyuk-
dc.contributor.authorKim, Yongjin-
dc.contributor.authorKoo, Hyun Cheol-
dc.contributor.authorLee, Oukjae-
dc.contributor.authorHong, Seokmin-
dc.date.accessioned2024-10-28T08:30:13Z-
dc.date.available2024-10-28T08:30:13Z-
dc.date.created2024-10-25-
dc.date.issued2024-09-
dc.identifier.issn0003-6951-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/150903-
dc.description.abstractHardware acceleration of probabilistic computing has recently attracted significant attention in the slowing down of Moore's law. A randomly fluctuating bit called as p-bit constitutes a fundamental building block for this type of physics-inspired computing scheme, which can be efficiently built out of emerging devices. Here, we report a probabilistic computing set-up, where random numbers are sampled from stochastic magnetic tunnel junctions with in-plane magnetic anisotropy. Although the sampled data have largely bipolar-like probability distributions compared to the ideally uniform ones, the results show a reasonable performance in a standard simulated annealing process on Boolean satisfiability problems up to 100 variables. The systematic simulations suggest the importance of probability distribution where some additional intermediate states help to increase the performance.-
dc.languageEnglish-
dc.publisherAmerican Institute of Physics-
dc.titleProbabilistic computing enabled by continuous random numbers sampled from in-plane magnetized stochastic magnetic tunnel junctions-
dc.typeArticle-
dc.identifier.doi10.1063/5.0223479-
dc.description.journalClass1-
dc.identifier.bibliographicCitationApplied Physics Letters, v.125, no.14-
dc.citation.titleApplied Physics Letters-
dc.citation.volume125-
dc.citation.number14-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid001326834200001-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.relation.journalResearchAreaPhysics-
dc.type.docTypeArticle-
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KIST Article > 2024
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