Modeling of the GERDA data after the upgrade

The GERDA experiment at the Gran Sasso underground laboratories is searching for neutrinoless double-beta decay in 76 Ge. In order to observe such a rare process this experiment will collect an exposure of 100 kg·y in background free condition. In 2018 many upgrades have been performed on the apparatus. In my thesis project I am studying and modeling the full-range energy spectrum acquired by the germanium detectors. All the analysis is done using bayesian statistics approach (parameter estimation, hypothesis testing, etc.). The spectrum is modeled by means of Monte Carlo simulations reproducing possible ra- dioactive isotopes, coming from U and T h chains or from cosmogenic activation, distributed in different components of the apparatus (cables, LAr, etc.) that can give significant contribution. The parameters of interest (isotopes activities, two neutrino beta decay’s half life) are then estimated from the data using Markov Chain Monte Carlo algorithms while direct screening measurements of the apparatus’ components (if available) are introduced as prior distributions in the analysis. For very high statistics gamma decay lines ( 40 K and 42 K) a detector by detector study of the number of registered counts is performed in order to get a more accurate and reliable assessment of the activities of the isotope generating these events; then they are inserted as prior distributions in the full-range fit. From this analysis it will be possible to understand the origin of the collected events, make a precise mea- surement of the half-life of the allowed two neutrino decay mode and could also give information about the purity of the materials for future experiments’ strategies. Moreover this study will help a lot the search for the neutrinoless double-beta decay in the region around Q ββ .