Cargando…

Inclusive tagging of B-flavour at LHCb [Vidyo]

<!--HTML-->One of the most important procedure needed for the study of CP violation in Beauty sector is the tagging of the flavour of neutral B-mesons at production. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present a proposal to...

Descripción completa

Detalles Bibliográficos
Autor principal: Rogozhnikov, Aleksei
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:http://cds.cern.ch/record/2256697
_version_ 1780953750902407168
author Rogozhnikov, Aleksei
author_facet Rogozhnikov, Aleksei
author_sort Rogozhnikov, Aleksei
collection CERN
description <!--HTML-->One of the most important procedure needed for the study of CP violation in Beauty sector is the tagging of the flavour of neutral B-mesons at production. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present a proposal to upgrade current flavour tagging strategy in LHCb experiment. This strategy consists of inclusive tagging ensemble methods (i.e: the use inclusive information about the event without a firm selection rule), which are combined using a probabilistic model for each event. The probabilistic model uses all reconstructed tracks and secondary vertices to obtain well-determined probability of B flavour at production. Such approach reduces the dependence on the performance of lower level identification capacities and thus has the potential to increase the overall performance.
id cern-2256697
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
record_format invenio
spelling cern-22566972022-11-02T22:34:07Zhttp://cds.cern.ch/record/2256697engRogozhnikov, AlekseiInclusive tagging of B-flavour at LHCb [Vidyo]IML Machine Learning WorkshopMachine Learning<!--HTML-->One of the most important procedure needed for the study of CP violation in Beauty sector is the tagging of the flavour of neutral B-mesons at production. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present a proposal to upgrade current flavour tagging strategy in LHCb experiment. This strategy consists of inclusive tagging ensemble methods (i.e: the use inclusive information about the event without a firm selection rule), which are combined using a probabilistic model for each event. The probabilistic model uses all reconstructed tracks and secondary vertices to obtain well-determined probability of B flavour at production. Such approach reduces the dependence on the performance of lower level identification capacities and thus has the potential to increase the overall performance.oai:cds.cern.ch:22566972017
spellingShingle Machine Learning
Rogozhnikov, Aleksei
Inclusive tagging of B-flavour at LHCb [Vidyo]
title Inclusive tagging of B-flavour at LHCb [Vidyo]
title_full Inclusive tagging of B-flavour at LHCb [Vidyo]
title_fullStr Inclusive tagging of B-flavour at LHCb [Vidyo]
title_full_unstemmed Inclusive tagging of B-flavour at LHCb [Vidyo]
title_short Inclusive tagging of B-flavour at LHCb [Vidyo]
title_sort inclusive tagging of b-flavour at lhcb [vidyo]
topic Machine Learning
url http://cds.cern.ch/record/2256697
work_keys_str_mv AT rogozhnikovaleksei inclusivetaggingofbflavouratlhcbvidyo
AT rogozhnikovaleksei imlmachinelearningworkshop