Measurements of top-quark pair spin correlations in the eµ channel at √s = 13 TeV using pp collisions in the ATLAS detector

0537144 - FZÚ 2021 RIV US eng J - Journal Article
Aaboud, M. - Aad, G. - Abbott, B. - Chudoba, Jiří - Hejbal, Jiří - Hladík, Ondřej - Jačka, Petr - Jakoubek, Tomáš - Kepka, Oldřich - Kroll, Jiří - Kupčo, Alexander - Lokajíček, Miloš - Lysák, Roman - Marčišovský, Michal - Mikeštíková, Marcela - Němeček, Stanislav - Penc, Ondřej - Šícho, Petr - Staroba, Pavel - Svatoš, Michal - Taševský, Marek … Total 2911 authors
Measurements of top-quark pair spin correlations in the eµ channel at √s = 13 TeV using pp collisions in the ATLAS detector.
European Physical Journal C. Roč. 80, č. 8 (2020), s. 1-43, č. článku 754. ISSN 1434-6044. E-ISSN 1434-6052
R&D Projects: GA MŠMT(CZ) LTT17018
Research Infrastructure: CERN-CZ II - 90104
Institutional support: RVO:68378271
Keywords : ATLAS * CERN * LHC * rapidity dependence * angular dependence
OECD category: Particles and field physics
Impact factor: 4.590, year: 2020
Method of publishing: Open access

A measurement of observables sensitive to spin correlations in ttˉt ar{t}ttˉ production is presented, using 36.1 hbox {fb}^{-1} of pp collision data at s=13sqrt{s} = 13s ​=13 TeV recorded with the ATLAS detector at the Large Hadron Collider. Differential cross-sections are measured in events with exactly one electron and one muon with opposite-sign electric charge as a function of the azimuthal opening angle and the absolute difference in pseudorapidity between the electron and muon candidates in the laboratory frame. The azimuthal opening angle is also measured as a function of the invariant mass of the ttˉt ar{t}ttˉ system. The measured differential cross-sections are compared to predictions by several NLO Monte Carlo generators and fixed-order calculations. The observed degree of spin correlation is somewhat higher than predicted by the generators used. The data are consistent with the prediction of one of the fixed-order calculations at NLO, but agree less well with higher-order predictions.

Permanent Link: http://hdl.handle.net/11104/0314895