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Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC
- Source :
- Miucci, Antonio; Merlassino, Claudia; Haug, Sigve; Weber, Michael; Anders, John Kenneth; Beck, Hans Peter; Ereditato, Antonio; Rimoldi, Marco; Weston, Thomas Daniel (2019). Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC. The European physical journal. C, Particles and fields, 79(5) Springer 10.1140/epjc/s10052-019-6847-8
- Publication Year :
- 2019
- Publisher :
- Springer, 2019.
-
Abstract
- The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s = 13 TeV 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 36.1 fb−1 for the tt¯ and γ+jet and 36.7 fb−1 for the dijet event topologies.
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Miucci, Antonio; Merlassino, Claudia; Haug, Sigve; Weber, Michael; Anders, John Kenneth; Beck, Hans Peter; Ereditato, Antonio; Rimoldi, Marco; Weston, Thomas Daniel (2019). Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC. The European physical journal. C, Particles and fields, 79(5) Springer 10.1140/epjc/s10052-019-6847-8 <http://dx.doi.org/10.1140/epjc/s10052-019-6847-8>
- Accession number :
- edsair.doi.dedup.....54c674d789a1237b40630628264eef8f