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Inclusive Flavour Tagging Algorithm

Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm...

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Detalles Bibliográficos
Autores principales: Likhomanenko, Tatiana, Derkach, Denis, Rogozhnikov, Alex
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/762/1/012045
http://cds.cern.ch/record/2272640
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author Likhomanenko, Tatiana
Derkach, Denis
Rogozhnikov, Alex
author_facet Likhomanenko, Tatiana
Derkach, Denis
Rogozhnikov, Alex
author_sort Likhomanenko, Tatiana
collection CERN
description Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
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spelling cern-22726402023-03-14T20:14:57Zdoi:10.1088/1742-6596/762/1/012045doi:10.1088/1742-6596/762/1/012045http://cds.cern.ch/record/2272640engLikhomanenko, TatianaDerkach, DenisRogozhnikov, AlexInclusive Flavour Tagging Algorithmhep-exParticle Physics - ExperimentIdentifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment.Identifying the flavour of neutral $B$ mesons production is one of the most important components needed in the study of time-dependent $CP$ violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of $B$ mesons in any proton-proton experiment.arXiv:1705.08707oai:cds.cern.ch:22726402017-05-24
spellingShingle hep-ex
Particle Physics - Experiment
Likhomanenko, Tatiana
Derkach, Denis
Rogozhnikov, Alex
Inclusive Flavour Tagging Algorithm
title Inclusive Flavour Tagging Algorithm
title_full Inclusive Flavour Tagging Algorithm
title_fullStr Inclusive Flavour Tagging Algorithm
title_full_unstemmed Inclusive Flavour Tagging Algorithm
title_short Inclusive Flavour Tagging Algorithm
title_sort inclusive flavour tagging algorithm
topic hep-ex
Particle Physics - Experiment
url https://dx.doi.org/10.1088/1742-6596/762/1/012045
https://dx.doi.org/10.1088/1742-6596/762/1/012045
http://cds.cern.ch/record/2272640
work_keys_str_mv AT likhomanenkotatiana inclusiveflavourtaggingalgorithm
AT derkachdenis inclusiveflavourtaggingalgorithm
AT rogozhnikovalex inclusiveflavourtaggingalgorithm