Performance of the H -> ZZ* -> 4 mu analysis with the CMS Phase-2 muon detector upgrade

Fontanesi, Elisa (2017) Performance of the H -> ZZ* -> 4 mu analysis with the CMS Phase-2 muon detector upgrade. [Laurea magistrale], Università di Bologna, Corso di Studio in Fisica [LM-DM270]
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A study of the performance of the Standard Model H(125 GeV) -> ZZ* -> 4 mu analysis with the upgraded CMS muon detector for the high luminosity operation (up to 7.5 x 10^{34} cm^{-2}s^{-1}) at the Large Hadron Collider (HL-LHC) has been carried out. The CMS Phase-2 muon detector upgrade, which will take place from 2024 to 2026, is crucial to efficiently exploit the data that will be collected at the HL-LHC, under very challenging experimental conditions, such as large number of overlapping collisions per event, up to 200 (referred to as pile-up). The H -> ZZ* -> 4 mu analysis essentially relies on the muon system to detect four muons in the final state; it therefore represents an important benchmark for the proposed muon detector upgrade, in particular the extension in pseudorapidity of the muon detector from |eta| < 2.4 to |eta| < 2.8 by introducing the ME0 (Muon Endcap 0) subdetector. The results presented here are obtained using simulated proton-proton collision events at sqrt{s} = 14 TeV with the full simulation of the upgraded CMS detector. The signal and background events are simulated with an average pile-up of 200. The analysis is performed assuming an integrated luminosity of 3000 fb^{-1} (expected in almost ten years of the HL-LHC operation) and follows the analysis of the 2016 data (Run-2). It is found that the signal selection efficiency remains immune to the high pile-up conditions and increases by 17% with the acceptance extension of the muon system.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Fontanesi, Elisa
Relatore della tesi
Correlatore della tesi
Corso di studio
Curriculum B: Fisica nucleare e subnucleare
Ordinamento Cds
Parole chiave
CMS upgrade Higgs muon
Data di discussione della Tesi
27 Ottobre 2017

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