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Searching the landscape of flux vacua with genetic algorithms

cam.depositDate2021-12-13
cam.issuedOnline2019-11-08
dc.contributor.authorCole, A
dc.contributor.authorSchachner, A
dc.contributor.authorShiu, G
dc.contributor.orcidCole, A [0000-0001-8035-4308]
dc.date.accessioned2021-12-24T00:30:11Z
dc.date.available2021-12-24T00:30:11Z
dc.date.issued2019
dc.date.updated2021-12-13T13:12:46Z
dc.description.abstractIn this paper, we employ genetic algorithms to explore the landscape of type IIB flux vacua. We show that genetic algorithms can efficiently scan the landscape for viable solutions satisfying various criteria. More specifically, we consider a symmetric $T^{6}$ as well as the conifold region of a Calabi-Yau hypersurface. We argue that in both cases genetic algorithms are powerful tools for finding flux vacua with interesting phenomenological properties. We also compare genetic algorithms to algorithms based on different breeding mechanisms as well as random walk approaches.
dc.identifier.doi10.17863/CAM.79204
dc.identifier.eissn1029-8479
dc.identifier.issn1126-6708
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/331755
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.publisher.departmentDept of Applied Mathematics & Theoretical Physics Student
dc.publisher.urlhttp://dx.doi.org/10.1007/JHEP11(2019)045
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSuperstring Vacua
dc.subjectFlux compactifications
dc.titleSearching the landscape of flux vacua with genetic algorithms
dc.typeArticle
prism.issueIdentifier11
prism.numberARTN 045
prism.publicationDate2019
prism.publicationNameJournal of High Energy Physics
prism.startingPage45
prism.volume2019
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
pubs.licence-identifierapollo-deposit-licence-2-1
rioxxterms.typeJournal Article/Review
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1007/JHEP11(2019)045

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