File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

우경석

Woo, Kyung Seok
Emerging Semiconductor Technology Laboratory
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.number 1 -
dc.citation.startPage 4656 -
dc.citation.title NATURE COMMUNICATIONS -
dc.citation.volume 15 -
dc.contributor.author Woo, Kyung Seok -
dc.contributor.author Zhang, Alan -
dc.contributor.author Arabelo, Allison -
dc.contributor.author Brown, Timothy D. -
dc.contributor.author Park, Minseong -
dc.contributor.author Talin, A. Alec -
dc.contributor.author Fuller, Elliot J. -
dc.contributor.author Bisht, Ravindra Singh -
dc.contributor.author Qian, Xiaofeng -
dc.contributor.author Arroyave, Raymundo -
dc.contributor.author Ramanathan, Shriram -
dc.contributor.author Thomas, Luke -
dc.contributor.author Williams, R. Stanley -
dc.contributor.author Kumar, Suhas -
dc.date.accessioned 2025-08-11T10:00:02Z -
dc.date.available 2025-08-11T10:00:02Z -
dc.date.created 2025-08-06 -
dc.date.issued 2024-05 -
dc.description.abstract While digital computers rely on software-generated pseudo-random number generators, hardware-based true random number generators (TRNGs), which employ the natural physics of the underlying hardware, provide true stochasticity, and power and area efficiency. Research into TRNGs has extensively relied on the unpredictability in phase transitions, but such phase transitions are difficult to control given their often abrupt and narrow parameter ranges (e.g., occurring in a small temperature window). Here we demonstrate a TRNG based on self-oscillations in LaCoO3 that is electrically biased within its spin crossover regime. The LaCoO3 TRNG passes all standard tests of true stochasticity and uses only half the number of components compared to prior TRNGs. Assisted by phase field modeling, we show how spin crossovers are fundamentally better in producing true stochasticity compared to traditional phase transitions. As a validation, by probabilistically solving the NP-hard max-cut problem in a memristor crossbar array using our TRNG as a source of the required stochasticity, we demonstrate solution quality exceeding that using software-generated randomness. -
dc.identifier.bibliographicCitation NATURE COMMUNICATIONS, v.15, no.1, pp.4656 -
dc.identifier.doi 10.1038/s41467-024-49149-5 -
dc.identifier.issn 2041-1723 -
dc.identifier.scopusid 2-s2.0-85194997132 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/87695 -
dc.identifier.wosid 001236598600024 -
dc.language 영어 -
dc.publisher NATURE PORTFOLIO -
dc.title True random number generation using the spin crossover in LaCoO3 -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Multidisciplinary Sciences -
dc.relation.journalResearchArea Science & Technology - Other Topics -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordPlus STATE TRANSITION -
dc.subject.keywordPlus DYNAMICS -
dc.subject.keywordPlus OPTIMIZATION -

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.