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Description and performance of track and primary-vertex reconstruction with the CMS tracker

  • The CMS collaboration
  • A. Alikhanian Yerevan Institute of Physics
  • Austrian Academy of Sciences
  • TU Wien
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  • Belarusian State University
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  • Texas A&M University at Qatar
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  • National Institute of Chemical Physics and Biophysics, Tallinn
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Research output: Contribution to journalArticlepeer-review

Abstract

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For t events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of pT> 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of pT= 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in pT, and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10-12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung.

Original languageEnglish
Article numberP10009
JournalJournal of Instrumentation
Volume9
Issue number10
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Large detectorsystems performance
  • Pattern recognition, cluster finding, calibration and fitting methods
  • Performance of High Energy Physics Detectors

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