Projecten per jaar
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 √
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 machinelearning models. Thus, they are expected to increase the sensitivity of future physics analyses.
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 √
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 machinelearning models. Thus, they are expected to increase the sensitivity of future physics analyses.
| Datum van beschikbaarheid | 8 nov. 2021 |
|---|---|
| Uitgever | HEPData |
Format
- Format
-
EU674: Innoveren voor duurzame versnellende systemen
D'Hondt, J. (Administrative Promotor), Tytgat, M. (Administrative Promotor) & D'Hondt, J. (CoI (Co-Promotor))
1/03/24 → 29/02/28
Project: Fundamenteel
-
FWOAL1078: Studie van de Charm-Higgs Yukawa bij de LHC
Tytgat, M. (Administrative Promotor) & D'Hondt, J. (Administrative Promotor)
1/01/23 → 31/12/26
Project: Fundamenteel
-
iBOF/23/074: Ontsluiten van de charm-Higgs koppeling bij de LHC
Lowette, S. (Administrative Promotor), D'Hondt, J. (Administrative Promotor), D'Hondt, J. (PI (Promotor, Principal Investigator)), Lowette, S. (Co-Promoter), Van Mechelen, P. (Co-Promoter) & Dobur, D. (Co-Promoter)
1/01/23 → 31/12/26
Project: Fundamenteel
Onderzoekersoutput
- 1 Article
-
A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ = 13 TeV
CMS Collaboration, 17 mrt. 2022, In: JINST. 2022, 17, 65 blz., P03014.Onderzoeksoutput: Article › peer review
Open AccessBestand14 Citaten (Scopus)179 Downloads (Pure)