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Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (taggers) for hadronically decaying top quarks and W bosons in pp collisions at = 13TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optima...

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Hauptverfasser: Aaboud, Morad (VerfasserIn) , Anders, Christoph (VerfasserIn) , Andrei, George Victor (VerfasserIn) , Antel, Claire (VerfasserIn) , Baas, Alessandra Edda (VerfasserIn) , Bolz, Arthur (VerfasserIn) , Brandt, Oleg (VerfasserIn) , Chouridou, Sofia (VerfasserIn) , Djuvsland, Julia Isabell (VerfasserIn) , Dunford, Monica (VerfasserIn) , Ferreira de Lima, Danilo Enoque (VerfasserIn) , Franchino, Silvia (VerfasserIn) , Geisler, Manuel Patrice (VerfasserIn) , Giulini, Maddalena (VerfasserIn) , Hanke, Paul (VerfasserIn) , Jongmanns, Jan (VerfasserIn) , Kolb, Mathis (VerfasserIn) , Kugel, Andreas (VerfasserIn) , Lisovyi, Mykhailo (VerfasserIn) , Meyer zu Theenhausen, Hanno (VerfasserIn) , Narrias Villar, Daniel Isaac (VerfasserIn) , Napolitano, Fabrizio (VerfasserIn) , S̜ahinsoy, Merve (VerfasserIn) , Schöning, André (VerfasserIn) , Schultz-Coulon, Hans-Christian (VerfasserIn) , Spieker, Thomas (VerfasserIn) , Stamen, Rainer (VerfasserIn) , Starovoitov, Pavel (VerfasserIn) , Suchek, Stanislav (VerfasserIn)
Körperschaft: ATLAS Collaboration (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 30 April 2019
In: The European physical journal. C, Particles and fields
Year: 2019, Jahrgang: 79, Heft: 5
ISSN:1434-6052
DOI:10.1140/epjc/s10052-019-6847-8
Online-Zugang:Verlag, Volltext: https://doi.org/10.1140/epjc/s10052-019-6847-8
Volltext
Verfasserangaben:ATLAS Collaboration
Beschreibung
Zusammenfassung:The performance of identification algorithms (taggers) for hadronically decaying top quarks and W bosons in pp collisions at = 13TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1fb-1 for the tt and +jet and 36.7-1 for the dijet event topologies.
Beschreibung:Gesehen am 28.11.2019
The ALICE collaboration: M. Aaboud [und 2875 weitere Personen]
Im Titel ist 'W' kursiv dargestellt
Beschreibung:Online Resource
ISSN:1434-6052
DOI:10.1140/epjc/s10052-019-6847-8

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