Off-line data processing and analysis for the GERDA experiment

Abstract

GERDA is an experiment designed to look for the neutrinoless double beta decay of Ge-76. The experiment uses an array of high-purity germanium detectors, enriched in Ge-76, directly immersed in liquid argon. GERDA is presently operating eight enriched coaxial detectors (approximately 15 kg of Ge-76) and about 30 new custom-made enriched BEGe detectors will be deployed in the next phase (additional 20 kg of Ge-76). The paper describes the GERDA off-line analysis of the high-purity germanium detector data. Firstly we present the signal processing flow, focusing on the digital filters and on the algorithms used. Secondly we discuss the rejection of non-physical events and the data quality monitoring. The analysis is performed completely with the GERDA software framework (GELATIO), designed to support a multi-channel processing and to perform a modular analysis of digital signals.

7 pages, 7 figures, ACAT 2011 proceeding

References in corpus (3)

• Pulse shape discrimination studies with a Broad-Energy Germanium detector for signal identification and background suppression in the GERDA double beta decay experiment
• Signal modeling of high-purity Ge detectors with a small read-out electrode and application to neutrinoless double beta decay search in Ge-76
• GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

Cited by in corpus (14)

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• The GERDA experiment for the search of 0νββ decay in ^{76}Ge
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• Results on $\beta \beta$ decay with emission of two neutrinos or Majorons in ${}^{76}$Ge from GERDA Phase I
• The background in the neutrinoless double beta decay experiment GERDA
• Pulse shape discrimination for GERDA Phase I data
• Production, characterization and operation of ${}^{76}$Ge enriched BEGe detectors in GERDA
• Measurement of the half-life of the two-neutrino double beta decay of Ge-76 with the Gerda experiment
• Pulse shape analysis in GERDA Phase II
• Results on neutrinoless double beta decay from GERDA Phase I
• A feasibility study of multi-electrode high-purity germanium detector for Ge-76 neutrinoless double beta decay searching
• Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines