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Identification of Additional Jets in the t(t)over-barb(b)over-bar Events by Using Deep Neural Network

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dc.contributor.authorChoi, Jieun-
dc.contributor.authorKim, Tae Jeong-
dc.contributor.authorLim, Jongwon-
dc.contributor.authorPark, Jiwon-
dc.contributor.authorRyou, Yeonsu-
dc.contributor.authorSong, Juhee-
dc.contributor.authorYun, Soohyun-
dc.date.accessioned2022-07-07T09:33:03Z-
dc.date.available2022-07-07T09:33:03Z-
dc.date.created2021-05-11-
dc.date.issued2020-12-
dc.identifier.issn0374-4884-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/144277-
dc.description.abstractIn the top quark pair production in association with the Higgs boson decaying to a b quark pair (tt¯H(bb¯)), the final state has an irreducible nonresonant background from the production of a top quark pair in association with a b quark pair (tt¯bb¯). Therefore, understanding of the tt¯bb¯ process precisely in particular differential cross-section as functions of the properties of the additional b jets not from the top quark decay is essential for improving the sensitivity of a search for the tt¯H(bb¯)process. The two additional b jets can be identified by using various approaches. In this paper, the performances are compared quantitatively in the lepton+jets decay channel in terms of the matching efficiency of assigning two additional b jets as a figure of merit. We showed that a matching efficiency of around 40% could be achieved using a deep neural network method. In the events with at least 4 b jets, this performance is 8% better than that achieved using minimum △R(b,b¯) method. This is consistent with the boosted decision tree method within its statistical uncertainty.-
dc.language영어-
dc.language.isoen-
dc.publisherKOREAN PHYSICAL SOC-
dc.titleIdentification of Additional Jets in the t(t)over-barb(b)over-bar Events by Using Deep Neural Network-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Tae Jeong-
dc.identifier.doi10.3938/jkps.77.1100-
dc.identifier.scopusid2-s2.0-85096290961-
dc.identifier.wosid000590984800005-
dc.identifier.bibliographicCitationJOURNAL OF THE KOREAN PHYSICAL SOCIETY, v.77, no.12, pp.1100 - 1106-
dc.relation.isPartOfJOURNAL OF THE KOREAN PHYSICAL SOCIETY-
dc.citation.titleJOURNAL OF THE KOREAN PHYSICAL SOCIETY-
dc.citation.volume77-
dc.citation.number12-
dc.citation.startPage1100-
dc.citation.endPage1106-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryPhysics, Multidisciplinary-
dc.subject.keywordPlusPP COLLISIONS-
dc.subject.keywordPlusASSOCIATION-
dc.subject.keywordAuthorTop quark-
dc.subject.keywordAuthorBottom quark-
dc.subject.keywordAuthorDeep neural network-
dc.identifier.urlhttps://link.springer.com/article/10.3938%2Fjkps.77.1100-
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