Improvement of muon identification algorithms and perspectives on the D0 → μ+μ− search

After the second long shutdown of the Large Hadron Collider, scheduled for 2020, LHCb will start a data taking period with increased instantaneous luminosity and collision energy to perform very high precision measurements. The present muon system has been designed to ensure high momentum resolution and high efficiency of the muon detectors to the current data taking luminosities and energies. This could be no more the optimum choice at upgrade luminosities, since the high particle fluxes will lead to a muon identification performance degradation and to a decrease of the muon detection efficiencies. In particular, the optimisation of muon identification and an improved rejection of misidentified particles are crucial for the analyses of rare B and D decays, key channels sensitive to New Physics, which require high-purity signal. As a consequence it becomes mandatory to develop new algorithms that allow to maintain or even improve the current muon identification capabilities when operating at higher detector occupancies. My thesis concentrates on my studies for the development of a novel algorithm for the muon identification at LHCb. The test on a Monte Carlo sample produced in upgrade conditions and the first applications on data are here presented. Finally, the use of the new method on the D0 → μ+μ− analysis to obtain an expected upper limit for the branching fraction of this decay channel is introduced.After the second long shutdown of the Large Hadron Collider, scheduled for 2020, LHCb will start a data taking period with increased instantaneous luminosity and collision energy to perform very high precision measurements. The present muon system has been designed to ensure high momentum resolution and high efficiency of the muon detectors to the current data taking luminosities and energies. This could be no more the optimum choice at upgrade luminosities, since the high particle fluxes will lead to a muon identification performance degradation and to a decrease of the muon detection efficiencies. In particular, the optimisation of muon identification and an improved rejection of misidentified particles are crucial for the analyses of rare B and D decays, key channels sensitive to New Physics, which require high-purity signal. As a consequence it becomes mandatory to develop new algorithms that allow to maintain or even improve the current muon identification capabilities when operating at higher detector occupancies. My thesis concentrates on my studies for the development of a novel algorithm for the muon identification at LHCb. The test on a Monte Carlo sample produced in upgrade conditions and the first applications on data are here presented. Finally, the use of the new method on the D0 → μ+μ− analysis to obtain an expected upper limit for the branching fraction of this decay channel is introduced