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Real time data analysis with the ATLAS Trigger at the LHC in Run-2

The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton bunch crossing. A new hardware system, designed to analyse real...

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Autor principal: Beauchemin, Pierre-Hugues
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1109/TNS.2020.2967761
http://cds.cern.ch/record/2624583
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author Beauchemin, Pierre-Hugues
author_facet Beauchemin, Pierre-Hugues
author_sort Beauchemin, Pierre-Hugues
collection CERN
description The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton bunch crossing. A new hardware system, designed to analyse real time event-topologies at Level-1 came to full use in 2017. A hardware-based track reconstruction system, expected to be used real-time in 2018, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger selections are largely relying on offline-like reconstruction techniques, and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and therefore also in CPU usage of the trigger algorithms, the set of triggers (so called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system, and the use of a levelling luminosity scheme in agreement with LHC and other experiments. This presentation gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) as well as details on some aspects of the algorithms which are run real-time on the High Level Trigger CPU farm.
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spelling cern-26245832023-03-14T19:19:06Zdoi:10.1109/TNS.2020.2967761http://cds.cern.ch/record/2624583engBeauchemin, Pierre-HuguesReal time data analysis with the ATLAS Trigger at the LHC in Run-2Particle Physics - ExperimentDetectors and Experimental TechniquesThe trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton bunch crossing. A new hardware system, designed to analyse real time event-topologies at Level-1 came to full use in 2017. A hardware-based track reconstruction system, expected to be used real-time in 2018, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger selections are largely relying on offline-like reconstruction techniques, and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and therefore also in CPU usage of the trigger algorithms, the set of triggers (so called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system, and the use of a levelling luminosity scheme in agreement with LHC and other experiments. This presentation gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) as well as details on some aspects of the algorithms which are run real-time on the High Level Trigger CPU farm.The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the Large Hadron Collider (LHC) Run-2 in order to cope with the higher event rates and with a large number of simultaneous interactions (pile-up) per proton–proton bunch crossing. A new hardware system, designed to analyze real-time event-topologies at level-1, came to full use in 2017. A hardware-based track reconstruction system, expected to be used real time in run-3, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger (HLT) selections largely rely on off-line-like reconstruction techniques and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and, therefore, also in CPU usage of the trigger algorithms, the set of triggers (so-called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system and the use of a leveling luminosity scheme in agreement with LHC and other experiments. This article gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) and details on some aspects of the algorithms which are run real time on the HLT CPU farm will be presented.The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton bunch crossing. A new hardware system, designed to analyse real time event-topologies at Level-1 came to full use in 2017. A hardware-based track reconstruction system, expected to be used real-time in 2018, is designed to provide track information to the high-level software trigger at its full input rate. The high-level trigger selections are largely relying on offline-like reconstruction techniques, and in some cases multivariate analysis methods. Despite the sudden change in LHC operations during the second half of 2017, which caused an increase in pile-up and therefore also in CPU usage of the trigger algorithms, the set of triggers (so called trigger menu) running online has undergone only minor modifications thanks to the robustness and redundancy of the trigger system, and the use of a levelling luminosity scheme in agreement with LHC and other experiments. This presentation gives a brief yet comprehensive review of the real-time performance of the ATLAS trigger system in 2017. Considerations will be presented on the most relevant parameters of the trigger (efficiency to collect signal and output data rate) as well as details on some aspects of the algorithms which are run real-time on the High Level Trigger CPU farm.arXiv:1806.08475ATL-DAQ-PROC-2018-005oai:cds.cern.ch:26245832018-06-18
spellingShingle Particle Physics - Experiment
Detectors and Experimental Techniques
Beauchemin, Pierre-Hugues
Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title_full Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title_fullStr Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title_full_unstemmed Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title_short Real time data analysis with the ATLAS Trigger at the LHC in Run-2
title_sort real time data analysis with the atlas trigger at the lhc in run-2
topic Particle Physics - Experiment
Detectors and Experimental Techniques
url https://dx.doi.org/10.1109/TNS.2020.2967761
http://cds.cern.ch/record/2624583
work_keys_str_mv AT beaucheminpierrehugues realtimedataanalysiswiththeatlastriggeratthelhcinrun2