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The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow
Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
EDP Sciences
2018
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1051/epjconf/201921401039 http://cds.cern.ch/record/2649519 |
_version_ | 1780960744179761152 |
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author | Bouaouda, Khalil Schmitt, Stefan Benchekroun, Driss |
author_facet | Bouaouda, Khalil Schmitt, Stefan Benchekroun, Driss |
author_sort | Bouaouda, Khalil |
collection | CERN |
description | Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with $ p_T>1 $ GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCard (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article. |
id | cern-2649519 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2018 |
publisher | EDP Sciences |
record_format | invenio |
spelling | cern-26495192023-03-14T19:06:01Zdoi:10.1051/epjconf/201921401039http://cds.cern.ch/record/2649519engBouaouda, KhalilSchmitt, StefanBenchekroun, DrissThe impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flowParticle Physics - ExperimentOnline selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with $ p_T>1 $ GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCard (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with $p_T$ > 1 GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers.Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCards (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with $ p_{\textrm T}>1 $ GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCards (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.EDP SciencesarXiv:2010.04300ATL-DAQ-PROC-2018-042oai:cds.cern.ch:26495192018-12-01 |
spellingShingle | Particle Physics - Experiment Bouaouda, Khalil Schmitt, Stefan Benchekroun, Driss The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title | The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title_full | The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title_fullStr | The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title_full_unstemmed | The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title_short | The impact of applying WildCards to disabled modules for FTK pattern banks on efficiency and data flow |
title_sort | impact of applying wildcards to disabled modules for ftk pattern banks on efficiency and data flow |
topic | Particle Physics - Experiment |
url | https://dx.doi.org/10.1051/epjconf/201921401039 http://cds.cern.ch/record/2649519 |
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