Physics measurements at the LHC rely on the imulation of the proton-proton interaction to estimate detector performance and physics ackgrounds. Therefore, a good understanding of ll the processes involved is crucial to the final precision of any measurement. Monte Carlo event generators try to provide a realistic description of the proton-proton collision by combining the theoretical models describing different stages of the interaction process. Within this framework, the baryon number transport and the hadronisation mechanism are currently described by phenomenological models that need input from experimental data. This thesis investigates these subjects in the unique kinematic region covered by the LHCb detector. The production cross section ratios of identified hadrons (protons, kaons and pions) have been measured as a function of pseudorapidity and transverse momentum both at $sqrt{s} = 0.9$ TeV and $sqrt{s} = 7$ TeV collisions using 320 $mub^{-1}$ and 1.8 $nb^{-1}$ of data respectively. The measurements are then compared to the predictions from several tunings of the PYTHIA Monte Carlo generator. In general, current models do not give a satisfactory description of the hadronisation and tend to underestimate the transport of the baryon number into the final state. Critical to this analysis is the particle identification provided by the LHCb Ring Imaging Cherenkov (RICH) system. To ensure high performance, a proper calibration of the RICH photon detectors response is necessary. A system for the calibration of the magnetic distortion induced by the LHCb dipole magnet onto the photon detectors is described. The system currently provides calibration parameters used in the LHCb event reconstruction software and introduces a critical improvement to the overall particle identification performance.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:581027 |
| Date | January 2012 |
| Creators | Contu, Andrea |
| Contributors | Harnew, Neville |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:842ec7be-36e9-4abc-a810-2325074aa5f7 |
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