CERN Accelerating science

The ALICE detector is designed to study the Quark-Gluon Plasma (QGP), a state in which strongly interacting partonic matter is deconfined in a hot and dense medium. The measurement of quarkonium, an important probe of QGP, is possible with ALICE in two regions: at midrapidity, through their dielectron decays, and at forward rapidity, through their dimuon decays with the muon spectrometer. In order to expand the physics program at the forward rapidity region, the Muon Forward Tracker (MFT) was installed in ALICE during the long shutdown, a period in which upgrades take place to prepare for the next data taking period. The work of this thesis focuses first on software developments for MFT commissioning tool and the official detector control system. Then, algorithm development was done for the track matching between the muon spectrometer and the MFT based on machine learning. Once the matching is performed and global muon tracks are extracted, the calculation of the point of closest approach between the muon tracks was required for the separation of prompt and non-prompt J/$\psi$ contributions. Thus, the secondary vertexing algorithm was also developed. Finally, quality assessments for Run 3 simulations were done to prepare for the upcoming data taking.