Final published version
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC
AU - The ATLAS collaboration
AU - Barton, A.E.
AU - Bertram, I.A.
AU - Borissov, G.
AU - Bouhova-Thacker, E.V.
AU - Ferguson, R.A.M.
AU - Fox, H.
AU - Henderson, R.C.W.
AU - Jones, R.W.L.
AU - Kartvelishvili, V.
AU - Love, P.A.
AU - Marshall, E.J.
AU - Meng, L.
AU - Muenstermann, D.
AU - Ribaric, N.
AU - Rybacki, K.
AU - Smizanska, M.
AU - Spinali, S.
AU - Wharton, A.M.
AU - Yexley, Melissa
PY - 2023/11/30
Y1 - 2023/11/30
N2 - Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.
AB - Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.
KW - Analysis and statistical methods
KW - Particle identification methods
U2 - 10.1088/1748-0221/18/11/t11004
DO - 10.1088/1748-0221/18/11/t11004
M3 - Journal article
VL - 18
JO - Journal of Instrumentation
JF - Journal of Instrumentation
SN - 1748-0221
IS - 11
M1 - T11004
ER -