Identification of b-quark jets with the CMS experiment

S. Chatrchyan, V. Khachatryan, A. M. Sirunyan, A. Tumasyan, W. Adam, E. Aguilo, T. Bergauer, M. Dragicevic, J. Erö, C. Fabjan, M. Friedl, R. Frühwirth, V. M. Ghete, J. Hammer, N. Hörmann, J. Hrubec, M. Jeitler, W. Kiesenhofer, V. Knünz, M. KrammerI. Krätschmer, D. Liko, I. Mikulec, M. Pernicka, B. Rahbaran, C. Rohringer, H. Rohringer, R. Schöfbeck, J. Strauss, A. Taurok, W. Waltenberger, G. Walzel, E. Widl, C. E. Wulz, V. Mossolov, N. Shumeiko, J. Suarez Gonzalez, M. Bansal, S. Bansal, T. Cornelis, E. A. De Wolf, X. Janssen, S. Luyckx, L. Mucibello, S. Ochesanu, B. Roland, S. Nourbakhsh, Y. Kubota, J. Mans, R. Rusack, CMS collaboration

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338 Scopus citations

Abstract

At the Large Hadron Collider, the identification of jets originating from b quarks is important for searches for new physics and for measurements of standard model processes. A variety of algorithms has been developed by CMS to select b-quark jets based on variables such as the impact parameters of charged-particle tracks, the properties of reconstructed decay vertices, and the presence or absence of a lepton, or combinations thereof. The performance of these algorithms has been measured using data from proton-proton collisions at the LHC and compared with expectations based on simulation. The data used in this study were recorded in 2011 at s = 7 TeV for a total integrated luminosity of 5.0 fb-1. The efficiency for tagging b-quark jets has been measured in events from multijet and t-quark pair production. CMS has achieved a b-jet tagging efficiency of 85% for a light-parton misidentification probability of 10% in multijet events. For analyses requiring higher purity, a misidentification probability of only 1.5% has been achieved, for a 70% b-jet tagging efficiency.

Original languageEnglish (US)
Article numberP04013
JournalJournal of Instrumentation
Volume8
Issue number4
DOIs
StatePublished - Apr 1 2013

Bibliographical note

Publisher Copyright:
© 2013 IOP Publishing Ltd and Sissa Medialab srl.

Keywords

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

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