TY  - JOUR
AU  - ATLAS Collaboration (Aad, G. et al
AU  - Amos, K. R.
AU  - Aparisi Pozo, J. A.
AU  - Bailey, A. J.
AU  - Bouchhar, N.
AU  - Cabrera Urban, S.
AU  - Cantero, J.
AU  - Cardillo, F.
AU  - Castillo Gimenez, V.
AU  - Costa, M. J.
AU  - Didenko
AU  - Escobar, C.
AU  - Fiorini, L.
AU  - Fullana Torregrosa, E.
AU  - Fuster, J.
AU  - Garcia, C.
AU  - Garcia Navarro, J. E.
AU  - Gomez Delegido, A. J.
AU  - Gonzalez de la Hoz, S.
AU  - Gonzalvo Rodriguez, G. R.
AU  - Guerrero Rojas, J. G. R.
AU  - Higon-Rodriguez, E.
AU  - Lacasta, C.
AU  - Lozano Bahilo, J. J.
AU  - Marti-Garcia, S.
AU  - Martinez Agullo, P.
AU  - Miralles Lopez, M.
AU  - Mitsou, V. A.
AU  - Monsonis Romero, L.
AU  - Moreno Llacer, M.
AU  - Munoz Perez, D.
AU  - Navarro-Gonzalez, J.
AU  - Poveda, J.
AU  - Prades Ibañez, A.
AU  - Rubio Jimenez, A.
AU  - Ruiz-Martinez, A.
AU  - Sabatini, P.
AU  - Salt, J.
AU  - Sanchez Sebastian, V.
AU  - Sayago Galvan, I.
AU  - Senthilkumar, V.
AU  - Soldevila, U.
AU  - Sanchez, J.
AU  - Torro Pastor, E.
AU  - Valero, A.
AU  - Valls Ferrer, J. A.
AU  - Varriale, L.
AU  - Villaplana Perez, M.
AU  - Vos, M.
PY  - 2023
DA  - 2023//
TI  - Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC
T2  - J. Instrum.
JO  - Journal of Instrumentation
SP  - T11004 - 61pp
VL  - 18
IS  - 11
PB  - IOP Publishing Ltd
KW  - Analysis and statistical methods
KW  - Particle identification methods
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.
SN  - 1748-0221
UR  - https://arxiv.org/abs/2211.16178
UR  - https://doi.org/10.1088/1748-0221/18/11/T11004
DO  - 10.1088/1748-0221/18/11/T11004
LA  - English
N1  - WOS:001116977400001
ID  - ATLASCollaborationAad_etal2023
ER  -