Dijet Resonance Search with Weak Supervision Using s =13 TeV pp Collisions in the ATLAS Detector

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dc.contributor.authorAad, G.
dc.contributor.authorAbbott, B.
dc.contributor.authorAbbott, D.C.
dc.contributor.authorAbed Abud, A.
dc.contributor.authorAbeling, K.
dc.contributor.authorAbhayasinghe, D.K.
dc.contributor.authorAbidi, S.H.
dc.contributor.authorAbouzeid, O.S.
dc.contributor.authorAbraham, N.L.
dc.contributor.authorAbramowicz, H.
dc.contributor.authorAbreu, H.
dc.contributor.authorAbulaiti, Y.
dc.date.accessioned2022-06-02T14:25:07Z
dc.date.available2022-06-02T14:25:07Z
dc.date.issued2020-09
dc.descriptionIndexación: Scopus.es
dc.description.abstractThis Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A→BC, for mA∼O(TeV), mB,mC∼O(100 GeV) and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 s=13 TeV pp collision dataset of 139 fb-1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA=3 TeV and mBâ200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model bosons. © 2020 CERN.es
dc.description.urihttps://journals-aps-org.recursosbiblioteca.unab.cl/prl/abstract/10.1103/PhysRevLett.125.131801
dc.identifier.citationPhysical Review LettersOpen AccessVolume 125, Issue 13September 2020 Article number 131801es
dc.identifier.doi10.1103/PhysRevLett.125.131801
dc.identifier.issn0031-9007
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/22696
dc.language.isoenes
dc.publisherAmerican Physical Societyes
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAnomaly detectiones
dc.subjectGermanium compoundses
dc.subjectLarge datasetes
dc.subjectMachine learninges
dc.subjectMass spectrometryes
dc.subjectTuring machineses
dc.subjectbody weightes
dc.subjectbosones
dc.subjecthadrones
dc.subjecthumanes
dc.subjectpunishmentes
dc.titleDijet Resonance Search with Weak Supervision Using s =13 TeV pp Collisions in the ATLAS Detectores
dc.typeArtículoes
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