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

TitleDijet Resonance Search with Weak Supervision Using √s=13 TeV pp Collisions in the ATLAS Detector
Authors
KeywordsConfidence levels
Invariant-mass spectra
Large Hadron Collider
Potential signal
Production cross section
Issue Date2020
PublisherAmerican Physical Society. The Journal's web site is located at https://journals.aps.org/prl/
Citation
Physical Review Letters, 2020, v. 125 n. 13, p. article no. 131801 How to Cite?
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.
Persistent Identifierhttp://hdl.handle.net/10722/289471
ISSN
2020 Impact Factor: 9.161
2015 SCImago Journal Rankings: 3.731
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLo, CY-
dc.contributor.authorParedes Hernandez, D-
dc.contributor.authorSalvucci, A-
dc.contributor.authorTAM, KC-
dc.contributor.authorTu, Y-
dc.contributor.authorATLAS Collaboration-
dc.date.accessioned2020-10-22T08:13:09Z-
dc.date.available2020-10-22T08:13:09Z-
dc.date.issued2020-
dc.identifier.citationPhysical Review Letters, 2020, v. 125 n. 13, p. article no. 131801-
dc.identifier.issn0031-9007-
dc.identifier.urihttp://hdl.handle.net/10722/289471-
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.-
dc.languageeng-
dc.publisherAmerican Physical Society. The Journal's web site is located at https://journals.aps.org/prl/-
dc.relation.ispartofPhysical Review Letters-
dc.rightsCopyright [2020] by The American Physical Society. This article is available online at [http://dx.doi.org/10.1103/PhysRevLett.125.131801].-
dc.subjectConfidence levels-
dc.subjectInvariant-mass spectra-
dc.subjectLarge Hadron Collider-
dc.subjectPotential signal-
dc.subjectProduction cross section-
dc.titleDijet Resonance Search with Weak Supervision Using √s=13 TeV pp Collisions in the ATLAS Detector-
dc.typeArticle-
dc.identifier.emailLo, CY: samuel3@hku.hk-
dc.identifier.emailParedes Hernandez, D: dparedes@hku.hk-
dc.identifier.emailTu, Y: yanjuntu@hku.hk-
dc.identifier.authorityTu, Y=rp01971-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1103/PhysRevLett.125.131801-
dc.identifier.pmid33034503-
dc.identifier.scopuseid_2-s2.0-85092801738-
dc.identifier.hkuros316190-
dc.identifier.volume125-
dc.identifier.issue13-
dc.identifier.spagearticle no. 131801-
dc.identifier.epagearticle no. 131801-
dc.identifier.isiWOS:000571399800004-
dc.publisher.placeUnited States-
dc.identifier.issnl0031-9007-

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