Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC

A neural network technique is used here to discriminate between quark and gluon jets produced in the qg-> q+photon and qq-> g+photon processes at the LHC. Considering the network as a trigger and using the PYTHIA event generator and the full event fast simulation package for the CMS detector C...

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Detalles Bibliográficos
Autores principales: Bandurin, D.V., Skachkov, N.B.
Lenguaje:eng
Publicado: 2001
Materias:
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/516497
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author Bandurin, D.V.
Skachkov, N.B.
author_facet Bandurin, D.V.
Skachkov, N.B.
author_sort Bandurin, D.V.
collection CERN
description A neural network technique is used here to discriminate between quark and gluon jets produced in the qg-> q+photon and qq-> g+photon processes at the LHC. Considering the network as a trigger and using the PYTHIA event generator and the full event fast simulation package for the CMS detector CMSJET the signal to background ratios are obtained.
id cern-516497
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2001
record_format invenio
spelling cern-5164972023-03-14T18:20:12Zhttp://cds.cern.ch/record/516497engBandurin, D.V.Skachkov, N.B.Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHCParticle Physics - ExperimentA neural network technique is used here to discriminate between quark and gluon jets produced in the qg-> q+photon and qq-> g+photon processes at the LHC. Considering the network as a trigger and using the PYTHIA event generator and the full event fast simulation package for the CMS detector CMSJET the signal to background ratios are obtained.A neural network technique is used to discriminate between quark and gluon jets produced in the qg->q+photon and q q->g+photon processes at the LHC. Considering the network as a trigger and using the PYTHIA event generator and the full event fast simulation package for the CMS detector CMSJET we obtain signal-to-background ratios.hep-ex/0109001oai:cds.cern.ch:5164972001-09-02
spellingShingle Particle Physics - Experiment
Bandurin, D.V.
Skachkov, N.B.
Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title_full Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title_fullStr Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title_full_unstemmed Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title_short Separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the LHC
title_sort separation of quark and gluon jets using neural network approach in the processes with the direct photon production at the lhc
topic Particle Physics - Experiment
url http://cds.cern.ch/record/516497
work_keys_str_mv AT bandurindv separationofquarkandgluonjetsusingneuralnetworkapproachintheprocesseswiththedirectphotonproductionatthelhc
AT skachkovnb separationofquarkandgluonjetsusingneuralnetworkapproachintheprocesseswiththedirectphotonproductionatthelhc

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