Cargando…

Calorimetry with Extremely Fine Spatial Segmentation

Particle Flow Algorithms (PFAs) attempt to measure each particle in a hadronic jet individually, using the detector subsystem that provides the best energy/momentum resolution. Calorimeters that can exploit the power of PFAs emphasize spatial granularity over single particle energy resolution. In th...

Descripción completa

Detalles Bibliográficos
Autores principales: Bilki, B, Guler, Y, Onel, Y, Repond, J, Xia, L
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/2374/1/012022
http://cds.cern.ch/record/2861340
_version_ 1780977819912765440
author Bilki, B
Guler, Y
Onel, Y
Repond, J
Xia, L
author_facet Bilki, B
Guler, Y
Onel, Y
Repond, J
Xia, L
author_sort Bilki, B
collection CERN
description Particle Flow Algorithms (PFAs) attempt to measure each particle in a hadronic jet individually, using the detector subsystem that provides the best energy/momentum resolution. Calorimeters that can exploit the power of PFAs emphasize spatial granularity over single particle energy resolution. In this context, the CALICE Collaboration developed the Digital Hadron Calorimeter (DHCAL). The DHCAL uses Resistive Plate Chambers (RPCs) as active media and is read out with 1 × 1 cm$^{2}$ pads and digital (1-bit) resolution. In order to obtain a unique dataset of electromagnetic and hadronic interactions with unprecedented spatial resolution, the DHCAL went through a broad test beam program. In addition to conventional calorimetry, the DHCAL offers detailed measurements of event shapes, rigorous tests of simulation models and various analytical tools to improve calorimetric performance. Here we report on the results from the analysis of DHCAL data and comparisons with the Monte Carlo simulations.
id cern-2861340
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2022
record_format invenio
spelling cern-28613402023-06-16T10:00:23Zdoi:10.1088/1742-6596/2374/1/012022http://cds.cern.ch/record/2861340engBilki, BGuler, YOnel, YRepond, JXia, LCalorimetry with Extremely Fine Spatial SegmentationDetectors and Experimental TechniquesParticle Flow Algorithms (PFAs) attempt to measure each particle in a hadronic jet individually, using the detector subsystem that provides the best energy/momentum resolution. Calorimeters that can exploit the power of PFAs emphasize spatial granularity over single particle energy resolution. In this context, the CALICE Collaboration developed the Digital Hadron Calorimeter (DHCAL). The DHCAL uses Resistive Plate Chambers (RPCs) as active media and is read out with 1 × 1 cm$^{2}$ pads and digital (1-bit) resolution. In order to obtain a unique dataset of electromagnetic and hadronic interactions with unprecedented spatial resolution, the DHCAL went through a broad test beam program. In addition to conventional calorimetry, the DHCAL offers detailed measurements of event shapes, rigorous tests of simulation models and various analytical tools to improve calorimetric performance. Here we report on the results from the analysis of DHCAL data and comparisons with the Monte Carlo simulations.oai:cds.cern.ch:28613402022
spellingShingle Detectors and Experimental Techniques
Bilki, B
Guler, Y
Onel, Y
Repond, J
Xia, L
Calorimetry with Extremely Fine Spatial Segmentation
title Calorimetry with Extremely Fine Spatial Segmentation
title_full Calorimetry with Extremely Fine Spatial Segmentation
title_fullStr Calorimetry with Extremely Fine Spatial Segmentation
title_full_unstemmed Calorimetry with Extremely Fine Spatial Segmentation
title_short Calorimetry with Extremely Fine Spatial Segmentation
title_sort calorimetry with extremely fine spatial segmentation
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1088/1742-6596/2374/1/012022
http://cds.cern.ch/record/2861340
work_keys_str_mv AT bilkib calorimetrywithextremelyfinespatialsegmentation
AT gulery calorimetrywithextremelyfinespatialsegmentation
AT onely calorimetrywithextremelyfinespatialsegmentation
AT repondj calorimetrywithextremelyfinespatialsegmentation
AT xial calorimetrywithextremelyfinespatialsegmentation