At the Large Hadron Collider (LHC) at Geneva, collisions of nuclei are used to create a thermodynamic system described by fluid dynamics under extreme conditions of temperature and energy density. The temperature of the short-lived system is sufficiently high in order to release the building blocks of matter at a subnucleonic scale, quarks and gluons. This state of matter is commonly called Quark Gluon Plasma (QGP). The space-time evolution of heavy-ion and light-ion collisions at the LHC is described by close-to-ideal hydrodynamics after a short pre-equilibrium lapse of time. However, key features of the early stages of these collisions are largely unknown. These characteristics are crucial to understand the applicability limits of hydrodynamics as well as the thermalization process of a strongly interacting system.
In recent publications, it was pointed out that the dilepton production in the intermediate mass scale between 1.5 and 5 GeV/c² is highly sensitive to the ´thermalization´ time scale towards the equilibrium QGP.
This thesis is dedicated to the development of an event generator based on state-of-the-art theoretical calculations for the production of charm quarks from the preequilibrium in hadronic collisions at the LHC. The generator will allow to generate simulations adapted for the usage in the LHC experiment and to simulate the preequilibrium signal within general purpose event generators. Machine learning methods will be used for the tool optimisation.