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Register a new userPulse-shape discrimination of surface events in CdZnTe detectors for the COBRA experiment
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Events near the cathode and anode surfaces of a coplanar grid CdZnTe detector are identifiable by means of the interaction depth information encoded in the signal amplitudes. However, the amplitudes cannot be used to identify events near the lateral surfaces. In this paper a method is described to identify lateral surface events by means of their pulse shapes. Such identification allows for discrimination of surface alpha particle interactions from more penetrating forms of radiation, which is particularly important for rare event searches. The effectiveness of the presented technique in suppressing backgrounds due to alpha contamination in the search for neutrinoless double beta decay with the COBRA experiment is demonstrated.
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The IGEX experiment has been operating enriched germanium detectors in the Canfranc Underground Laboratory (Spain) in a search for the neutrinoless double decay of 76Ge. The implementation of Pulse Shape Discrimination techniques to reduce the radioactive background is described in detail. This analysis has been applied to a fraction of the IGEX data, leading to a rejection of ~60 % of their background, in the region of interest (from 2 to 2.5 MeV), down to ~0.09 c/(keV kg y).
The COBRA collaboration searches for neutrinoless double beta-decay ($0 ubetabeta$-decay) using CdZnTe semiconductor detectors with a coplanar-grid readout and a surrounding guard-ring structure. The operation of the COBRA demonstrator at the Gran Sasso underground laboratory (LNGS) indicates that alpha-induced lateral surface events are the dominant source of background events. By instrumenting the guard-ring electrode it is possible to suppress this type of background. In laboratory measurements this method achieved a suppression factor of alpha-induced lateral surface events of $5300^{+2660}_{-1380}$, while retaining $85.3pm0.1%$ of gamma events occurring in the entire detector volume. This suppression is superior to the pulse-shape analysis methods used so far in COBRA by three orders of magnitude.
New charge and current-sensitive preamplifiers coupled to silicon detectors and devoted to studies in nuclear structure and dynamics have been developed and tested. For the first time shapes of current pulses from light charged particles and carbon ions are presented. Capabilities for pulse shape discrimination techniques are demonstrated.
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.
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.
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