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https://hdl.handle.net/10316/106901
Título: | Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC | Autor: | Santos, S. P. Amor dos Fiolhais, M. C. N. Galhardo, B. Veloso, F. Wolters, H. ATLAS Collaboration |
Data: | 2019 | Editora: | Springer Nature | Título da revista, periódico, livro ou evento: | European Physical Journal C | Volume: | 79 | Número: | 5 | Resumo: | 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. | URI: | https://hdl.handle.net/10316/106901 | DOI: | 10.1140/epjc/s10052-019-6847-8 | Direitos: | openAccess |
Aparece nas coleções: | FCTUC Física - Artigos em Revistas Internacionais |
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Ficheiro | Descrição | Tamanho | Formato | |
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Performance-of-topquark-and-W-boson-tagging-with-ATLAS-in-Run-2-of-the-LHCEuropean-Physical-Journal-C.pdf | 4 MB | Adobe PDF | Ver/Abrir |
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