Please use this identifier to cite or link to this item:
https://hdl.handle.net/11147/8692
Title: | Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV | Authors: | Karapınar, Güler CMS Collaboration |
Keywords: | Particle identification methods Pattern recognition, cluster finding, calibration and fitting methods Performance of High Energy Physics Detectors |
Publisher: | IOP Publishing Ltd. | Abstract: | Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated t (t) over bar events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV). | URI: | https://doi.org/10.1088/1748-0221/13/05/P05011 https://hdl.handle.net/11147/8692 |
ISSN: | 1748-0221 |
Appears in Collections: | Rectorate / Rektörlük WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Show full item record
CORE Recommender
SCOPUSTM
Citations
436
checked on Nov 15, 2024
WEB OF SCIENCETM
Citations
162
checked on Nov 9, 2024
Page view(s)
196
checked on Nov 18, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.