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Improvement of the Energy Resolution via an Optimized Digital Signal Processing in GERDA Phase I

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 Added by Peter Grabmayr
 Publication date 2015
  fields Physics
and research's language is English




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An optimized digital shaping filter has been developed for the GERDA experiment which searches for neutrinoless double beta decay in 76Ge. The GERDA Phase I energy calibration data have been reprocessed and an average improvement of 0.3 keV in energy resolution (FWHM) at the 76Ge Q value for 0 ubetabeta decay is obtained. This is possible thanks to the enhanced low-frequency noise rejection of this Zero Area Cusp (ZAC) signal shaping fillter.



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The GERDA experiment located at the LNGS searches for neutrinoless double beta (0 ubetabeta) decay of ^{76}Ge using germanium diodes as source and detector. In Phase I of the experiment eight semi-coaxial and five BEGe type detectors have been deployed. The latter type is used in this field of research for the first time. All detectors are made from material with enriched ^{76}Ge fraction. The experimental sensitivity can be improved by analyzing the pulse shape of the detector signals with the aim to reject background events. This paper documents the algorithms developed before the data of Phase I were unblinded. The double escape peak (DEP) and Compton edge events of 2.615 MeV gamma rays from ^{208}Tl decays as well as 2 ubetabeta decays of ^{76}Ge are used as proxies for 0 ubetabeta decay. For BEGe detectors the chosen selection is based on a single pulse shape parameter. It accepts 0.92$pm$0.02 of signal-like events while about 80% of the background events at Q_{betabeta}=2039 keV are rejected. For semi-coaxial detectors three analyses are developed. The one based on an artificial neural network is used for the search of 0 ubetabeta decay. It retains 90% of DEP events and rejects about half of the events around Q_{betabeta}. The 2 ubetabeta events have an efficiency of 0.85pm0.02 and the one for 0 ubetabeta decays is estimated to be 0.90^{+0.05}_{-0.09}. A second analysis uses a likelihood approach trained on Compton edge events. The third approach uses two pulse shape parameters. The latter two methods confirm the classification of the neural network since about 90% of the data events rejected by the neural network are also removed by both of them. In general, the selection efficiency extracted from DEP events agrees well with those determined from Compton edge events or from 2 ubetabeta decays.
Internal contaminations of $^{238}$U, $^{235}$U and $^{232}$Th in the bulk of high purity germanium detectors are potential backgrounds for experiments searching for neutrinoless double beta decay of $^{76}$Ge. The data from GERDA Phase~I have been analyzed for alpha events from the decay chain of these contaminations by looking for full decay chains and for time correlations between successive decays in the same detector. No candidate events for a full chain have been found. Upper limits on the activities in the range of a few nBq/kg for $^{226}$Ra, $^{227}$Ac and $^{228}$Th, the long-lived daughter nuclides of $^{238}$U, $^{235}$U and $^{232}$Th, respectively, have been derived. With these upper limits a background index in the energy region of interest from $^{226}$Ra and $^{228}$Th contamination is estimated which satisfies the prerequisites of a future ton scale germanium double beta decay experiment.
The GERDA collaboration is performing a sensitive search for neutrinoless double beta decay of $^{76}$Ge at the INFN Laboratori Nazionali del Gran Sasso, Italy. The upgrade of the GERDA experiment from Phase I to Phase II has been concluded in December 2015. The first Phase II data release shows that the goal to suppress the background by one order of magnitude compared to Phase I has been achieved. GERDA is thus the first experiment that will remain background-free up to its design exposure (100 kg yr). It will reach thereby a half-life sensitivity of more than 10$^{26}$ yr within 3 years of data collection. This paper describes in detail the modifications and improvements of the experimental setup for Phase II and discusses the performance of individual detector components.
The development of large-area homogeneous photo-detectors with sub-millimeter path lengths for direct Cherenkov light and for secondary-electrons opens the possibility of large time-of-flight systems for relativistic particles with resolutions in the pico-second range. Modern ASIC techniques allow fast multi-channel front-end electronics capable of sub-pico-second resolution directly integrated with the photo-detectors. However, achieving resolution in the pico-second range requires a precise knowledge of the signal generation process in order to understand the pulse waveform, the signal dynamics, and the noise induced by the detector itself, as well as the noise added by the processing electronics. Using the parameters measured for fast photo-detectors such as micro-channel plates photo-multipliers, we have simulated and compared the time-resolutions for four signal processing techniques: leading edge discriminators, constant fraction discriminators, multiple-threshold discriminators and pulse waveform sampling.
The GERmanium Detector Array (GERDA) collaboration searched for neutrinoless double-$beta$ decay in $^{76}$Ge with an array of about 40 high-purity isotopically-enriched germanium detectors. The experimental signature of the decay is a monoenergetic signal at Q$_{betabeta}$ = 2039.061(7)keV in the measured summed energy spectrum of the two emitted electrons. Both the energy reconstruction and resolution of the germanium detectors are crucial to separate a potential signal from various backgrounds, such as neutrino-accompanied double-$beta$ decays allowed by the Standard Model. The energy resolution and stability were determined and monitored as a function of time using data from regular $^{228}$Th calibrations. In this work, we describe the calibration process and associated data analysis of the full GERDA dataset, tailored to preserve the excellent resolution of the individual germanium detectors when combining data over several years.
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