Modeling of GERDA Phase II data

The GERmanium Detector Array (GERDA) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta ($0\nu\beta\ beta$) decayof $^{76}$Ge. The technological challenge of GERDA is to operate in a background-free regime in the region of interest (ROI) after analysis cuts for the full 100 kg$\cdot$y target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition in the ROI around \qbb\ for the \onbb\ search, to extract a precise measurement of the half-life of the double-beta decaymode with neutrinos ($2\nu\beta\beta$) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the backgroundand achieve even better sensitivities. In this article the backgrounddecomposition is presented within a Bayesian framework for GERDA Phase II. The backgroundmodel fit, which is conducted prior active backgroundsuppression techniques, yields a flat spectrum in the ROI with a backgroundindex (BI) of $16.04^{+0.78}_{-0.85}\cdot10^{-3}$ cts/(kg$\cdot$keV$\cdot$yr) for the enriched BEGe data set and $14.68^{+0.47}_{-0.52}\cdot 10^{-3}$ cts/(kg$\cdot$keV$\cdot$yr) for the enriched coaxial data set. This indicates that, despite major hardware changes and higher inactive mass close to the detectors after the upgrade works completed in 2015, the BI before applying active backgroundreduction remains unchanged for the enriched coaxial detectors and is improved by a factor of three for the enriched BEGe detectors.