Charge-carrier collective motion in germanium detectors for ββ-decay searches

Abstract

The time analysis of the signal induced by the drift of charge carriers in high purity germanium detectors provides information on the event topology. Millions of charge carriers are produced in a typical event. Their initial distribution, stochastic diffusion and Coulomb self-repulsion affect the time structure of the signal. We present a comprehensive study of these effects and evaluate their impact on the event discrimination capabilities for the three geometries which will be used in the Legend experiment for neutrinoless double-beta decay.

References in corpus (10)

• CoGeNT: A Search for Low-Mass Dark Matter using p-type Point Contact Germanium Detectors
• The Large Enriched Germanium Experiment for Neutrinoless Double Beta Decay (LEGEND)
• \textsc{MaGe} - a {\sc Geant4}-based Monte Carlo Application Framework for Low-background Germanium Experiments
• Probing Majorana neutrinos with double-$\beta$ decay
• Pulse shape discrimination studies with a Broad-Energy Germanium detector for signal identification and background suppression in the GERDA double beta decay experiment
• A Search for Neutrinoless Double-Beta Decay in ${}^{76}$Ge with 26 kg-yr of Exposure from the MAJORANA DEMONSTRATOR
• New limits on Bosonic Dark Matter, Solar Axions, Pauli Exclusion Principle Violation, and Electron Decay from the Majorana Demonstrator
• Constraints on dark photons and axion-like particles from SuperCDMS Soudan
• Pulse shape discrimination performance of Inverted Coaxial Ge detectors
• Characterization of High Purity Germanium Point Contact Detectors with Low Net Impurity Concentration

Cited by in corpus (5)

• Pulse shape analysis in GERDA Phase II
• Identification of the anomalous fast bulk events in a p-type point contact germanium detector
• Characterization of inverted coaxial ${}^{76}$Ge detectors in GERDA for future double-$\beta$ decay experiments
• Topologies of ${}^{76}$Ge double-beta decay events and calibration procedure biases
• CycleGAN-Driven Transfer Learning for Electronics Response Emulation in High-Purity Germanium Detectors