Abstract. The observation of neutrinoless double-beta decay (0νββ) would show that lepton number is violated, reveal that neutrinos are Majorana particles, and provide information on neutrino mass. A discovery-capable experiment covering the inverted ordering region, with effective Majorana neutrino masses of 15 − 50 meV, will require a tonne-scale experiment with excellent energy resolution and extremely low backgrounds, at the level of ∼0.1 count /(FWHM·t·yr) in the region of the signal. The current generation 76 Ge experiments GERDA and the Majorana Demonstrator, utilizing high purity Germanium detectors with an intrinsic energy resolution of 0.12%, have achieved the lowest backgrounds by over an order of magnitude in the 0νββ signal region of all 0νββ experiments. Building on this success, the LEGEND collaboration has been formed to pursue a tonne-scale 76 Ge experiment. The collaboration aims to develop a phased 0νββ experimental program with discovery potential at a half-life approaching or at 10 28 years, using existing resources as appropriate to expedite physics results.

Experiments searching for rare processes like neutrinoless double beta decay heavily rely on the identification of background events to reduce their background level and increase their sensitivity. We present a novel machine learning based method to recognize one of the most abundant classes of background events in these experiments. By combining a neural network for feature extraction with a smaller classification network, our method can be trained with only a small number of labeled events. To validate our method, we use signals from a broad-energy germanium detector irradiated with a 228 Th gamma source. We find that it matches the performance of state-of-the-art algorithms commonly used for this detector type. However, it requires less tuning and calibration and shows potential to identify certain types of background events missed by other methods.

A four-fold segmented n-type point-contact "Broad Energy" high-purity germanium detector, SegBEGe, has been characterised at the Max-Planck-Institut für Physik in Munich. The main characteristics of the detector are described and first measurements concerning the detector properties are presented. The possibility to use mirror pulses to determine source positions is discussed as well as charge losses observed close to the core contact.

The open-source software package SolidStateDetectors.jl to calculate the fields and simulate the drifts of charge carriers in solid state detectors, especially in large volume high-purity germanium detectors, together with the corresponding pulses, is introduced. The package can perform all calculations in full 3D while it can also make use of detector symmetries. The effect of the surroundings of a detector can also be studied. The package is programmed in the user friendly and performance oriented language julia, such that 3D field calculations and drift simulations can be executed efficiently and in parallel. The package was developed for high-purity germanium detectors, but it can be adjusted by the user to other types of semiconductors. The verification of the package is shown for an n-type segmented point-contact germanium detector. Additional features of SolidStateDetectors.jl, which are under development are listed.

P-type point contact (PPC) germanium detectors are used in rare event and low-background searches, including neutrinoless double beta (0) decay, low-energy nuclear recoils, and coherent elastic neutrino-nucleus scattering. The detectors feature an excellent energy resolution, low detection thresholds down to the sub-keV range, and enhanced background rejection capabilities. However, due to their large passivated surface, separating the signal readout contact from the bias voltage electrode, PPC detectors are susceptible to surface effects such as charge build-up. A profound understanding of their response to surface events is essential. In this work, the response of a PPC detector to alpha and beta particles hitting the passivated surface was investigated in a multi-purpose scanning test stand. It is shown that the passivated surface can accumulate charges resulting in a radial-dependent degradation of the observed event energy. In addition, it is demonstrated that the pulse shapes of surface alpha events show characteristic features which can be used to discriminate against these events.