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Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$

We present a measurement of the charged particle reconstruction inefficiency inside of jet cores, using data collected by the ATLAS experiment in 2015 of pp collisions produced at the LHC, at a center-of-mass energy of 13 TeV . The determination of this inefficiency is important for jet energy scale...

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Autor principal: Mansour, Jason Dhia
Lenguaje:eng
Publicado: 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1748-0221/11/12/C12041
http://cds.cern.ch/record/2226563
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author Mansour, Jason Dhia
author_facet Mansour, Jason Dhia
author_sort Mansour, Jason Dhia
collection CERN
description We present a measurement of the charged particle reconstruction inefficiency inside of jet cores, using data collected by the ATLAS experiment in 2015 of pp collisions produced at the LHC, at a center-of-mass energy of 13 TeV . The determination of this inefficiency is important for jet energy scale and mass calibration, as well as multiple other performance studies and analyses. A data driven method is used, where the fraction of lost particle tracks is determined from energy deposition dE/dx in the pixel detector. The fraction of lost tracks is found to be less than 5%, which is an improvement since the previous study, and agrees well within systematic uncertainties with a Monte Carlo simulation.
id cern-2226563
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
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spelling cern-22265632019-09-30T06:29:59Zdoi:10.1088/1748-0221/11/12/C12041http://cds.cern.ch/record/2226563engMansour, Jason DhiaTracking in dense environments and its inefficiency measurement using pixel $dE/dx$Particle Physics - Experimenthep-exWe present a measurement of the charged particle reconstruction inefficiency inside of jet cores, using data collected by the ATLAS experiment in 2015 of pp collisions produced at the LHC, at a center-of-mass energy of 13 TeV . The determination of this inefficiency is important for jet energy scale and mass calibration, as well as multiple other performance studies and analyses. A data driven method is used, where the fraction of lost particle tracks is determined from energy deposition dE/dx in the pixel detector. The fraction of lost tracks is found to be less than 5%, which is an improvement since the previous study, and agrees well within systematic uncertainties with a Monte Carlo simulation.We present a measurement of the charged particle reconstruction inefficiency inside of jet cores, using data collected by the ATLAS experiment in 2015 of $pp$ collisions produced at the LHC, at a center-of-mass energy of 13 TeV. The determination of this inefficiency is important for jet energy scale and mass calibration, as well as multiple other performance studies and analyses. A data driven method is used, where the fraction of lost particle tracks is determined from energy deposition $dE/dx$ in the pixel detector. The fraction of lost tracks is found to be less than 5%, which is an improvement since the previous study, and agrees well within systematic uncertainties with a Monte Carlo simulation.ATL-INDET-PROC-2016-006arXiv:1610.08709oai:cds.cern.ch:22265632016-10-21
spellingShingle Particle Physics - Experiment
hep-ex
Mansour, Jason Dhia
Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title_full Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title_fullStr Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title_full_unstemmed Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title_short Tracking in dense environments and its inefficiency measurement using pixel $dE/dx$
title_sort tracking in dense environments and its inefficiency measurement using pixel $de/dx$
topic Particle Physics - Experiment
hep-ex
url https://dx.doi.org/10.1088/1748-0221/11/12/C12041
http://cds.cern.ch/record/2226563
work_keys_str_mv AT mansourjasondhia trackingindenseenvironmentsanditsinefficiencymeasurementusingpixeldedx