Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV

The properties of pixel clusters in dense environments are studied with $\sqrt{s}$ = 13 TeV proton-proton collisions from the LHC, recorded by ATLAS from June to July 2015. A novel method to evaluate the performance of the artificial neural network used for identifying pixel clusters created by mult...

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Detalles Bibliográficos
Autor principal: The ATLAS collaboration
Lenguaje:eng
Publicado: 2015
Materias:
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2054921
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author The ATLAS collaboration
author_facet The ATLAS collaboration
author_sort The ATLAS collaboration
collection CERN
description The properties of pixel clusters in dense environments are studied with $\sqrt{s}$ = 13 TeV proton-proton collisions from the LHC, recorded by ATLAS from June to July 2015. A novel method to evaluate the performance of the artificial neural network used for identifying pixel clusters created by multiple particles is presented. Using this method, the results in data and Monte Carlo simulation are compared. The neural network, as part of the track reconstruction, shows the expected response when used on collimated tracks.
id cern-2054921
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
record_format invenio
spelling cern-20549212021-04-18T19:40:46Zhttp://cds.cern.ch/record/2054921engThe ATLAS collaborationMeasurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeVParticle Physics - ExperimentThe properties of pixel clusters in dense environments are studied with $\sqrt{s}$ = 13 TeV proton-proton collisions from the LHC, recorded by ATLAS from June to July 2015. A novel method to evaluate the performance of the artificial neural network used for identifying pixel clusters created by multiple particles is presented. Using this method, the results in data and Monte Carlo simulation are compared. The neural network, as part of the track reconstruction, shows the expected response when used on collimated tracks.ATL-PHYS-PUB-2015-044oai:cds.cern.ch:20549212015-09-24
spellingShingle Particle Physics - Experiment
The ATLAS collaboration
Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title_full Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title_fullStr Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title_full_unstemmed Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title_short Measurement of performance of the pixel neural network clustering algorithm of the ATLAS experiment at $\sqrt{s}$ = 13 TeV
title_sort measurement of performance of the pixel neural network clustering algorithm of the atlas experiment at $\sqrt{s}$ = 13 tev
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2054921
work_keys_str_mv AT theatlascollaboration measurementofperformanceofthepixelneuralnetworkclusteringalgorithmoftheatlasexperimentatsqrts13tev

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