Cargando…
Real-time flavour tagging selection in ATLAS
In high-energy physics experiments, online selection is crucial to identify the few interesting collisions from the large data volume processed. In the overall ATLAS trigger strategy, b-jet triggers are designed to identify heavy-flavour content in real-time and, in particular, provide the only opti...
Autor principal: | |
---|---|
Lenguaje: | eng |
Publicado: |
2015
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2049448 |
_version_ | 1780948035539304448 |
---|---|
author | Bogavac, Danijela |
author_facet | Bogavac, Danijela |
author_sort | Bogavac, Danijela |
collection | CERN |
description | In high-energy physics experiments, online selection is crucial to identify the few interesting collisions from the large data volume processed. In the overall ATLAS trigger strategy, b-jet triggers are designed to identify heavy-flavour content in real-time and, in particular, provide the only option to efficiently record events with fully hadronic final states containing b-jets. In doing so, two different, but related, challenges are faced. The physics goal is to optimise as far as possible the rejection of light jets from multijet processes, while retaining a high efficiency on selecting jets from beauty, and maintaining affordable trigger rates without raising jet energy thresholds. This maps into a challenging computing task, as charged tracks and their corresponding vertexes must be reconstructed and analysed for each jet above the desired threshold, regardless of the increasingly harsh pile-up conditions. The performance of b-jet triggers during the LHC Run 1 data-taking campaigns is presented, together with an overview and preliminary results of the new online b-tagging strategy and algorithms, designed to face the above mentioned challenges, which will be adopted during Run 2. |
id | cern-2049448 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
record_format | invenio |
spelling | cern-20494482019-09-30T06:29:59Zhttp://cds.cern.ch/record/2049448engBogavac, DanijelaReal-time flavour tagging selection in ATLASParticle Physics - ExperimentIn high-energy physics experiments, online selection is crucial to identify the few interesting collisions from the large data volume processed. In the overall ATLAS trigger strategy, b-jet triggers are designed to identify heavy-flavour content in real-time and, in particular, provide the only option to efficiently record events with fully hadronic final states containing b-jets. In doing so, two different, but related, challenges are faced. The physics goal is to optimise as far as possible the rejection of light jets from multijet processes, while retaining a high efficiency on selecting jets from beauty, and maintaining affordable trigger rates without raising jet energy thresholds. This maps into a challenging computing task, as charged tracks and their corresponding vertexes must be reconstructed and analysed for each jet above the desired threshold, regardless of the increasingly harsh pile-up conditions. The performance of b-jet triggers during the LHC Run 1 data-taking campaigns is presented, together with an overview and preliminary results of the new online b-tagging strategy and algorithms, designed to face the above mentioned challenges, which will be adopted during Run 2.ATL-DAQ-SLIDE-2015-564oai:cds.cern.ch:20494482015-09-07 |
spellingShingle | Particle Physics - Experiment Bogavac, Danijela Real-time flavour tagging selection in ATLAS |
title | Real-time flavour tagging selection in ATLAS |
title_full | Real-time flavour tagging selection in ATLAS |
title_fullStr | Real-time flavour tagging selection in ATLAS |
title_full_unstemmed | Real-time flavour tagging selection in ATLAS |
title_short | Real-time flavour tagging selection in ATLAS |
title_sort | real-time flavour tagging selection in atlas |
topic | Particle Physics - Experiment |
url | http://cds.cern.ch/record/2049448 |
work_keys_str_mv | AT bogavacdanijela realtimeflavourtaggingselectioninatlas |