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Using the waveforms from a digital electronic system, an offline analysis technique on pulse shape discrimination (PSD) has been developed to improve the neutron-gamma separation in a bar-shaped NE-213 scintillator that couples to a photomultiplier tube (PMT) at each end. The new improved method, called the ``valued-assigned PSD (VPSD), assigns a normalized fitting residual to every waveform as the PSD value. This procedure then facilitates the incorporation of longitudinal position dependence of the scintillator, which further enhances the PSD capability of the detector system. In this paper, we use radiation emitted from an AmBe neutron source to demonstrate that the resulting neutron-gamma identification has been much improved when compared to the traditional technique that uses the geometric mean of light outputs from both PMTs. The new method has also been modified and applied to a recent experiment at the National Superconducting Cyclotron Laboratory (NSCL) that uses an analog electronic system.
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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.
We report on the characterization of two inverted coaxial Ge detectors in the context of being employed in future $^{76}$Ge neutrinoless double beta ($0 ubetabeta$) decay experiments. It is an advantage that such detectors can be produced with bigger Ge mass as compared to the planar Broad Energy Ge detectors (BEGe) that are currently used in the GERDA $0 ubetabeta$ decay experiment. This will result in lower background for the search of $0 ubetabeta$ decay due to a reduction of cables, electronics and holders. The measured resolution near the $^{76}$Ge Q-value at 2039 keV is 2.5 keV and their pulse-shape characteristics are similar to BEGe-detectors. It is concluded that this type of Ge-detector is suitable for usage in $^{76}$Ge $0 ubetabeta$ decay experiments.
We measured the decay time of the scintillation pulses produced by electron and nuclear recoils in CaF2(Eu) by a new fitting method. In the recoil energy region 5-30 keVee, we found differences of the decay time between electron and nuclear recoil events. In the recoil energy region above 20 keVee, we found that the decay time is independent of the recoil energy.
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.
A series of test experiments on three different Si-based neutron detectors, namely a 1-d 128 channel, 0.5 mm space resolution Si microstrip sensor coupled to natural Gd converter, a medium size ? 1 cm2 PIN diode coupled to nGd2O3 or 157Gd2O3 converters, and a SiPM photomultiplier coupled to neutron scintillators, are presented to show the performances of this class of devices for thermal neutron detection. A pulse shape analysis method, designed to improve the performance of these devices by an optimized discrimination of the neutron signals from noise and background radiation, is proposed, described and tested. This study is aimed to real time applications and single event storage of the neutron information in time of flight instrumentation.
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