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Performance studies of tracking-based triggering using a fast emulation

Experiments at the High-Luminosity phase of the LHC will face an increased number of interactions per bunch crossing. Several strategies have been evaluated by the ATLAS experiment to improve its trigger strategy in this context. One of the limitations in recovering events with low energy particles...

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Autor principal: The ATLAS collaboration
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:http://cds.cern.ch/record/2848431
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author The ATLAS collaboration
author_facet The ATLAS collaboration
author_sort The ATLAS collaboration
collection CERN
description Experiments at the High-Luminosity phase of the LHC will face an increased number of interactions per bunch crossing. Several strategies have been evaluated by the ATLAS experiment to improve its trigger strategy in this context. One of the limitations in recovering events with low energy particles is the input rate of the Event Filter which necessitates high thresholds of Level-0 trigger items. As such, the potential use of tracking information prior to the Event Filter could particularly benefit to hadronic and di-lepton signatures. However, traditional track reconstruction techniques are known to be consumptive in terms of time and computational resources. A hardware fast-tracker solution, called L1Track, has been conceived to compute coarse-resolution tracks prior to the Event-Filter step. In this note we introduce a fast emulation of this system, allowing to explore various inputs to the tracking algorithm given the detector readout limits. The performance of simplified trigger algorithms on emulated L1Track tracks are investigated, highlighting the feedback that the emulation enables on the physics potential of a low latency hardware based track trigger.
id cern-2848431
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2023
record_format invenio
spelling cern-28484312023-02-13T14:39:12Zhttp://cds.cern.ch/record/2848431engThe ATLAS collaborationPerformance studies of tracking-based triggering using a fast emulationParticle Physics - ExperimentExperiments at the High-Luminosity phase of the LHC will face an increased number of interactions per bunch crossing. Several strategies have been evaluated by the ATLAS experiment to improve its trigger strategy in this context. One of the limitations in recovering events with low energy particles is the input rate of the Event Filter which necessitates high thresholds of Level-0 trigger items. As such, the potential use of tracking information prior to the Event Filter could particularly benefit to hadronic and di-lepton signatures. However, traditional track reconstruction techniques are known to be consumptive in terms of time and computational resources. A hardware fast-tracker solution, called L1Track, has been conceived to compute coarse-resolution tracks prior to the Event-Filter step. In this note we introduce a fast emulation of this system, allowing to explore various inputs to the tracking algorithm given the detector readout limits. The performance of simplified trigger algorithms on emulated L1Track tracks are investigated, highlighting the feedback that the emulation enables on the physics potential of a low latency hardware based track trigger.ATL-DAQ-PUB-2023-001oai:cds.cern.ch:28484312023-02-07
spellingShingle Particle Physics - Experiment
The ATLAS collaboration
Performance studies of tracking-based triggering using a fast emulation
title Performance studies of tracking-based triggering using a fast emulation
title_full Performance studies of tracking-based triggering using a fast emulation
title_fullStr Performance studies of tracking-based triggering using a fast emulation
title_full_unstemmed Performance studies of tracking-based triggering using a fast emulation
title_short Performance studies of tracking-based triggering using a fast emulation
title_sort performance studies of tracking-based triggering using a fast emulation
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2848431
work_keys_str_mv AT theatlascollaboration performancestudiesoftrackingbasedtriggeringusingafastemulation