Models in Neutrino Physics : Numerical and Statistical Studies

Abstract: The standard model of particle physics can excellently describe the vast majorityof data of particle physics experiments. However, in its simplest form, it cannot account for the fact that the neutrinos are massive particles and lepton flavorsmixed, as required by the observation of neutrino oscillations. Hence, the standardmodel must be extended in order to account for these observations, opening up thepossibility to explore new and interesting physical phenomena.There are numerous models proposed to accommodate massive neutrinos. Thesimplest of these are able to describe the observations using only a small numberof effective parameters. Furthermore, neutrinos are the only known existing particleswhich have the potential of being their own antiparticles, a possibility that isactively being investigated through experiments on neutrinoless double beta decay.In this thesis, we analyse these simple models using Bayesian inference and constraintsfrom neutrino-related experiments, and we also investigate the potential offuture experiments on neutrinoless double beta decay to probe other kinds of newphysics.In addition, more elaborate theoretical models of neutrino masses have beenproposed, with the seesaw models being a particularly popular group of models inwhich new heavy particles generate neutrino masses. We study low-scale seesawmodels, in particular the resulting energy-scale dependence of the neutrino parameters,which incorporate new particles with masses within the reach of current andfuture experiments, such as the LHC.