Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3

The Run 3 of the Large Hadron Collider (LHC) will be characterised by an enhanced level of noise in the CMS electromagnetic calorimeter (ECAL), caused by the ageing of the photosensors and the loss of crystal transparency due to radiation damage. To face these new conditions, some parameters of the...

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Detalles Bibliográficos
Autor principal: Lyon, Anne-Mazarine
Lenguaje:eng
Publicado: 2022
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/2374/1/012015
http://cds.cern.ch/record/2861222
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author Lyon, Anne-Mazarine
author_facet Lyon, Anne-Mazarine
author_sort Lyon, Anne-Mazarine
collection CERN
description The Run 3 of the Large Hadron Collider (LHC) will be characterised by an enhanced level of noise in the CMS electromagnetic calorimeter (ECAL), caused by the ageing of the photosensors and the loss of crystal transparency due to radiation damage. To face these new conditions, some parameters of the clustering algorithms of the ECAL, namely the Particle-Flow Clustering and SuperClustering algorithms, are tuned to offer optimal performance in terms of signal preservation and noise and pile-up rejection. The methods used for the tuning as well as its performance are presented.
id cern-2861222
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2022
record_format invenio
spelling cern-28612222023-06-16T09:49:31Zdoi:10.1088/1742-6596/2374/1/012015http://cds.cern.ch/record/2861222engLyon, Anne-MazarineOptimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3Detectors and Experimental TechniquesThe Run 3 of the Large Hadron Collider (LHC) will be characterised by an enhanced level of noise in the CMS electromagnetic calorimeter (ECAL), caused by the ageing of the photosensors and the loss of crystal transparency due to radiation damage. To face these new conditions, some parameters of the clustering algorithms of the ECAL, namely the Particle-Flow Clustering and SuperClustering algorithms, are tuned to offer optimal performance in terms of signal preservation and noise and pile-up rejection. The methods used for the tuning as well as its performance are presented.oai:cds.cern.ch:28612222022
spellingShingle Detectors and Experimental Techniques
Lyon, Anne-Mazarine
Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title_full Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title_fullStr Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title_full_unstemmed Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title_short Optimisation of the CMS ECAL clustering algorithms in view of LHC-Run 3
title_sort optimisation of the cms ecal clustering algorithms in view of lhc-run 3
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1088/1742-6596/2374/1/012015
http://cds.cern.ch/record/2861222
work_keys_str_mv AT lyonannemazarine optimisationofthecmsecalclusteringalgorithmsinviewoflhcrun3

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