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Software digitizer for high granular gaseous detector
A sampling calorimeter using gaseous sensor layers with digital readout [1] is near perfect for ``Particle Flow Algorithm'' [2,3] approach, since it is homogeneous over large surfaces, robust, cost efficient, easily segmentable to any readout pad dimension and size and almost insensitive t...
Autores principales: | , , |
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Formato: | info:eu-repo/semantics/article |
Lenguaje: | eng |
Publicado: |
JINST
2014
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/9/11/C11016 http://cds.cern.ch/record/1999219 |
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author | Haddad, Y Ruan, M Boudry, V |
author_facet | Haddad, Y Ruan, M Boudry, V |
author_sort | Haddad, Y |
collection | CERN |
description | A sampling calorimeter using gaseous sensor layers with digital readout [1] is near perfect for ``Particle Flow Algorithm'' [2,3] approach, since it is homogeneous over large surfaces, robust, cost efficient, easily segmentable to any readout pad dimension and size and almost insensitive to neutrons. Monte-Carlo (MC) programs such as GEANT4 [4] simulate with high precision the energy deposited by particles. The sensor and electronic response associated to a pad are calculated in a separate ``digitization'' process. We develop a general method for simulating the pad response using the spatial information from a simulation done at high granularity. The digitization method proposed here has been applied to gaseous detectors including Glass Resistive Plate Chambers (GRPC) and MicroMegas, and validated on test beam data. Experimental observable such as pad multiplicity and mean number of hits at different thresholds have been reproduced with high precision. |
format | info:eu-repo/semantics/article |
id | cern-1999219 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2014 |
publisher | JINST |
record_format | invenio |
spelling | cern-19992192019-09-30T06:29:59Z doi:10.1088/1748-0221/9/11/C11016 http://cds.cern.ch/record/1999219 eng Haddad, Y Ruan, M Boudry, V Software digitizer for high granular gaseous detector Detectors and Experimental Techniques 9: Advanced infrastructures for detector R&D 9.5:Highly Granular Calorimetry A sampling calorimeter using gaseous sensor layers with digital readout [1] is near perfect for ``Particle Flow Algorithm'' [2,3] approach, since it is homogeneous over large surfaces, robust, cost efficient, easily segmentable to any readout pad dimension and size and almost insensitive to neutrons. Monte-Carlo (MC) programs such as GEANT4 [4] simulate with high precision the energy deposited by particles. The sensor and electronic response associated to a pad are calculated in a separate ``digitization'' process. We develop a general method for simulating the pad response using the spatial information from a simulation done at high granularity. The digitization method proposed here has been applied to gaseous detectors including Glass Resistive Plate Chambers (GRPC) and MicroMegas, and validated on test beam data. Experimental observable such as pad multiplicity and mean number of hits at different thresholds have been reproduced with high precision. info:eu-repo/grantAgreement/EC/FP7/262025 info:eu-repo/semantics/openAccess Education Level info:eu-repo/semantics/article http://cds.cern.ch/record/1999219 JINST JINST, 11 (2014) pp. C11016 2014-05-06 |
spellingShingle | Detectors and Experimental Techniques 9: Advanced infrastructures for detector R&D 9.5:Highly Granular Calorimetry Haddad, Y Ruan, M Boudry, V Software digitizer for high granular gaseous detector |
title | Software digitizer for high granular gaseous detector |
title_full | Software digitizer for high granular gaseous detector |
title_fullStr | Software digitizer for high granular gaseous detector |
title_full_unstemmed | Software digitizer for high granular gaseous detector |
title_short | Software digitizer for high granular gaseous detector |
title_sort | software digitizer for high granular gaseous detector |
topic | Detectors and Experimental Techniques 9: Advanced infrastructures for detector R&D 9.5:Highly Granular Calorimetry |
url | https://dx.doi.org/10.1088/1748-0221/9/11/C11016 http://cds.cern.ch/record/1999219 http://cds.cern.ch/record/1999219 |
work_keys_str_mv | AT haddady softwaredigitizerforhighgranulargaseousdetector AT ruanm softwaredigitizerforhighgranulargaseousdetector AT boudryv softwaredigitizerforhighgranulargaseousdetector |