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Abstract

The Germanium Detector Array (Gerda) experiment, located underground at the INFN Laboratori Nazionali del Gran Sasso (LNGS) in Italy, deploys high-purity germanium detectors to search for the neutrinoless double β-decay (0vββ) of ⁷⁶Ge. An observation of this lepton number violating process, which is expected by many extensions of the Standard Model, would not only generate a fundamental shift in our understanding of particle physics, but also unambiguously prove the neutrino to have a non-vanishing Majorana mass component. A ifrst phase of data recording lasted from November 2011 to May 2013 - resulting in a total exposure (defined as the product of detector mass and measurement time) of 21.6 kg ^. yr. Within this thesis a thorough study of this data with special emphasis on the development and scrutiny of an active background suppression technique by means of a signal shape analysis has been performed. Among several investigated multivariate approaches, particularly a selection algorithm based on an artificial neural network is found to yield the best performance; i.a. the background index close to the Q-value of the 0vββ - decay could be suppressed by 45% to 1^. 10² cts=(keV^. kg^.yr), while still retaining a considerably high signal survival fraction of (83 ± 3)% leading to a significant improvement of the experimental sensitivity. The efficiency is derived by a simulation and further validated by substantiated consistency checks availing themselves of measurements taken with different calibration sources and physics data. No signal is observed and a new lower limit of T^0v_½ (90% C.L.) > 2.2^. 10²⁵ yr for the half-life of neutrinoless double β-decay of ⁷⁶Ge is established.