Study of prompt and non prompt quarkonium production at forward rapidity with Standard and Machine Learning techniques

Charmonia, bound states of charm (c) and anticharm ($\overline{c}$), represent an important tool to understand quantum chromodynamics (QCD). In particular, the $J/\Psi$ meson production has been investigated by many LHC experiments. The ALICE experiment has been upgraded recently, aiming to improve spatial resolutions at mid and forward rapidity. As a part of the upgrade, the Muon Forward Tracker (MFT), a new detector at forward rapidity, was installed with the goal of improving the vertexing resolution of ALICE's muon spectrometer. As a consequence it is now possible to separate the production cross section into the prompt (produced at the primary vertex) and non-prompt (produced in the decay of B hadrons) components for this vector meson. The goal of this project is to determine the non-prompt $J/\Psi$ decay fraction using the standard template fit technique. In addition, an exploratory study of the possible Machine Learning (ML) appli-cation for this study will be discussed.