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Theses

Observation des photons directs dans les premières données et préparation à la recherche du boson de Higgs dans l'expérience CMS au LHC (CERN)

Abstract : The LHC (Large Hadron Collider) provides proton-proton collisions to CERN (European Organization for Nuclear Research) experiments at a 7 TeV center of mass energy since March 2010. The LHC has been designed in particular to allow the Higgs boson searches, particle predicted in the standard model but still not discovered until today, in the whole mass range where it is expected. This thesis is a contribution to the Higgs boson searches in CMS (Compact Muon Solenoid), one of the four big detectors at LHC. The thesis develops several tools which allow to measure the backgrounds and to improve the discovery potential. A new tool for recovery of photons emitted by leptons in the final state H --> ZZ(*) ->4$\ll (\ll= e\mu)$ has been developed in this thesis. This method recovers a variable number of photons per event, performs better than the method previously used in CMS and improves Z^0 and Higgs bosons mass resolution. A 5% gain on the significance to observe a Higgs boson in this channel is reached. The second part of this thesis deals with studies of the backgrounds and the searches for a light Higgs boson (110 < mH < 140 GeV) in the channel H --> $\gamma\gamma$. A new tool for $\gamma/\pi^i0$ discrimination with a neural network has been developed to reject photons coming from $\pi^0$ decays, copiously produced in QCD jets. The neural network performance is examined in details. The neural network is then used as "template" variable to measure $\gamma$+X process in data with 10 nb−1 of integrated luminosity. The measurement of $\gamma\gamma$+X process is also prepared with simulation in the luminosity hypothesis of 10 pb−1. Taking into account higher order kinematic effects is necessary to perform the best prediction of H -> $\gamma\gamma$ signal and backgrounds. In the thesis this is carried out with a reweighting method, at NNLO for gg -> H $\gamma\gamma$ process and for the first time at NLO for $\gamma\gamma$ +X process, in both cases with doubly differential distributions. Reweighting procedure and $\gamma/\pi^i0$ neural network are then integrated in the H -> $\gamma\gamma$ analysis to improve CMS sensitivity in the standard model and beyond, thanks to an effective parameterization developed by phenomenologists we were working with.
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Submitted on : Wednesday, June 8, 2011 - 9:37:30 AM
Last modification on : Monday, November 15, 2021 - 3:44:02 PM

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Nicolas Chanon. Observation des photons directs dans les premières données et préparation à la recherche du boson de Higgs dans l'expérience CMS au LHC (CERN). Physique [physics]. Université Claude Bernard - Lyon I, 2010. Français. ⟨tel-00598989⟩

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