Deep Learning Techniques for Top-Quark Reconstruction

Top quarks are unique probes of the standard model (SM) predictions and have the potential to be a window for physics beyond the SM (BSM). Top quarks decay to a $Wb$ pair, and the $W$ can decay in leptons or jets. In a top pair event, assigning jets to their correct source is a challenge. In this st...

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Detalles Bibliográficos
Autor principal: Naderi, Kiarash
Lenguaje:eng
Publicado: 2017
Materias:
Computing and Computers
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2280195
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author Naderi, Kiarash
author_facet Naderi, Kiarash
author_sort Naderi, Kiarash
collection CERN
description Top quarks are unique probes of the standard model (SM) predictions and have the potential to be a window for physics beyond the SM (BSM). Top quarks decay to a $Wb$ pair, and the $W$ can decay in leptons or jets. In a top pair event, assigning jets to their correct source is a challenge. In this study, I studied different methods for improving top reconstruction. The main motivation was to use Deep Learning Techniques in order to enhance the precision of top reconstruction.
id cern-2280195
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
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spelling cern-22801952019-09-30T06:29:59Zhttp://cds.cern.ch/record/2280195engNaderi, KiarashDeep Learning Techniques for Top-Quark ReconstructionComputing and ComputersParticle Physics - ExperimentTop quarks are unique probes of the standard model (SM) predictions and have the potential to be a window for physics beyond the SM (BSM). Top quarks decay to a $Wb$ pair, and the $W$ can decay in leptons or jets. In a top pair event, assigning jets to their correct source is a challenge. In this study, I studied different methods for improving top reconstruction. The main motivation was to use Deep Learning Techniques in order to enhance the precision of top reconstruction.CERN-STUDENTS-Note-2017-087oai:cds.cern.ch:22801952017-08-18
spellingShingle Computing and Computers
Particle Physics - Experiment
Naderi, Kiarash
Deep Learning Techniques for Top-Quark Reconstruction
title Deep Learning Techniques for Top-Quark Reconstruction
title_full Deep Learning Techniques for Top-Quark Reconstruction
title_fullStr Deep Learning Techniques for Top-Quark Reconstruction
title_full_unstemmed Deep Learning Techniques for Top-Quark Reconstruction
title_short Deep Learning Techniques for Top-Quark Reconstruction
title_sort deep learning techniques for top-quark reconstruction
topic Computing and Computers
Particle Physics - Experiment
url http://cds.cern.ch/record/2280195
work_keys_str_mv AT naderikiarash deeplearningtechniquesfortopquarkreconstruction

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