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Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network

A search for supersymmetry in proton-proton collisions at $\sqrt{s} = 7$ TeV is presented, focusing on events with a single isolated lepton, energetic jets, and large missing transverse momentum. The analyzed data corresponds to a total integrated luminosity of 4.98 fb$^{−1}$ recorded by the CMS exp...

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Detalles Bibliográficos
Autor principal: Chatterjee, Avishek
Lenguaje:eng
Publicado: 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1517069
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author Chatterjee, Avishek
author_facet Chatterjee, Avishek
author_sort Chatterjee, Avishek
collection CERN
description A search for supersymmetry in proton-proton collisions at $\sqrt{s} = 7$ TeV is presented, focusing on events with a single isolated lepton, energetic jets, and large missing transverse momentum. The analyzed data corresponds to a total integrated luminosity of 4.98 fb$^{−1}$ recorded by the CMS experiment. The search uses an artificial neural network to suppress Standard Model backgrounds, and estimates residual backgrounds using a fully data-driven method. The analysis is performed in both the muon and electron channels, and the combined result is interpreted in terms of limits on the CMSSM parameter space, as well as a simplified model.
id cern-1517069
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2013
record_format invenio
spelling cern-15170692019-09-30T06:29:59Zhttp://cds.cern.ch/record/1517069engChatterjee, AvishekSearch for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural networkParticle Physics - ExperimentA search for supersymmetry in proton-proton collisions at $\sqrt{s} = 7$ TeV is presented, focusing on events with a single isolated lepton, energetic jets, and large missing transverse momentum. The analyzed data corresponds to a total integrated luminosity of 4.98 fb$^{−1}$ recorded by the CMS experiment. The search uses an artificial neural network to suppress Standard Model backgrounds, and estimates residual backgrounds using a fully data-driven method. The analysis is performed in both the muon and electron channels, and the combined result is interpreted in terms of limits on the CMSSM parameter space, as well as a simplified model.CERN-THESIS-2013-006oai:cds.cern.ch:15170692013-02-18T20:29:41Z
spellingShingle Particle Physics - Experiment
Chatterjee, Avishek
Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title_full Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title_fullStr Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title_full_unstemmed Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title_short Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
title_sort search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network
topic Particle Physics - Experiment
url http://cds.cern.ch/record/1517069
work_keys_str_mv AT chatterjeeavishek searchforsupersymmetryineventswithasingleleptonjetsandmissingtransversemomentumusinganeuralnetwork