Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/2493
Title: A new calibration method for charm jet identification validated with proton-proton collision events at root s=13 TeV
Authors: Tumasyan, A.
Adam, W.
Andrejkovic, J. W.
Bergauer, T.
Chatterjee, S.
Dragicevic, M.
Güler, Yalçın
The CMS Collaboration
Keywords: Large detector-systems performance
Pattern recognition
cluster finding
calibration and fitting methods
Fragmentation
Publisher: Iop Publishing Ltd
Abstract: Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb(-1) at root s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.
URI: https://doi.org/10.1088/1748-0221/17/03/P03014
https://hdl.handle.net/20.500.13091/2493
ISSN: 1748-0221
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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