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Real-time flavour tagging selection in ATLAS
In high-energy physics experiments, online selection is crucial to select interesting collisions from the large data volume. ATLAS b-jet triggers are designed to identify heavy-flavour content in real-time and provide the only option to efficiently record events with fully hadronic final states cont...
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Lenguaje: | eng |
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2020
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Acceso en línea: | http://cds.cern.ch/record/2728707 |
_version_ | 1780966383257911296 |
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author | Varni, Carlo |
author_facet | Varni, Carlo |
author_sort | Varni, Carlo |
collection | CERN |
description | In high-energy physics experiments, online selection is crucial to select interesting collisions from the large data volume. ATLAS b-jet triggers are designed to identify heavy-flavour content in real-time and 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, while retaining a high efficiency on selecting b-jets and maintaining affordable trigger rates without raising jet energy thresholds. This maps into a challenging computing task, as 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. We present an overview of the ATLAS strategy for online b-jet selection for the LHC Run 2, including the use of novel methods and sophisticated algorithms designed to face the above mentioned challenges. The evolution of the performance of b-jet triggers in Run 2 data is presented, including the use of novel triggers designed to select events containing heavy flavour jets in heavy ion collisions. |
id | cern-2728707 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
spelling | cern-27287072020-08-25T20:15:57Zhttp://cds.cern.ch/record/2728707engVarni, CarloReal-time flavour tagging selection in ATLASParticle Physics - ExperimentIn high-energy physics experiments, online selection is crucial to select interesting collisions from the large data volume. ATLAS b-jet triggers are designed to identify heavy-flavour content in real-time and 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, while retaining a high efficiency on selecting b-jets and maintaining affordable trigger rates without raising jet energy thresholds. This maps into a challenging computing task, as 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. We present an overview of the ATLAS strategy for online b-jet selection for the LHC Run 2, including the use of novel methods and sophisticated algorithms designed to face the above mentioned challenges. The evolution of the performance of b-jet triggers in Run 2 data is presented, including the use of novel triggers designed to select events containing heavy flavour jets in heavy ion collisions.ATL-DAQ-SLIDE-2020-335oai:cds.cern.ch:27287072020-08-25 |
spellingShingle | Particle Physics - Experiment Varni, Carlo 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/2728707 |
work_keys_str_mv | AT varnicarlo realtimeflavourtaggingselectioninatlas |