arXiv subjects

S. Fraker

Publications and source records attributed to S. Fraker.

2 recordsLinked to original sources

arXiv2021

The nylon balloon for xenon loaded liquid scintillator in KamLAND-Zen 800 neutrinoless double-beta decay search experiment

The KamLAND-Zen 800 experiment is searching for the neutrinoless double-beta decay of $^{136}$Xe by using $^{136}$Xe-loaded liquid scintillator. The liquid scintillator is enclosed inside a balloon made of thin, transparent, low-radioactivity film that we call Inner Balloon (IB). The IB, apart from guaranteeing the liquid containment, also allows to minimize the background from cosmogenic muon-spallation products and $^{8}$B solar neutrinos. Indeed these events could contribute to the total counts in the region of interest around the Q-value of the double-beta decay of $^{136}$Xe. In this paper, we present an overview of the IB and describe the various steps of its commissioning minimizing the radioactive contaminations, from the material selection, to the fabrication of the balloon and its installation inside the KamLAND detector. Finally, we show the impact of the IB on the KamLAND background as measured by the KamLAND detector itself.

physics.ins-det↗

arXiv2018

Suppression of Cosmic Muon Spallation Backgrounds in Liquid Scintillator Detectors Using Convolutional Neural Networks

Cosmic muon spallation backgrounds are ubiquitous in low-background experiments. For liquid scintillator-based experiments searching for neutrinoless double-beta decay, the spallation product $^{10}$C is an important background in the region of interest between 2-3 MeV and determines the depth requirement for the experiment. We have developed an algorithm based on a convolutional neural network that uses the temporal and spatial correlations in light emissions to identify $^{10}$C background events. With a typical kiloton-scale detector configuration like the KamLAND detector, we find that the algorithm is capable of identifying 61.6% of the $^{10}$C at 90% signal acceptance. A detector with perfect light collection could identify 98.2% at 90% signal acceptance. The algorithm is independent of vertex and energy reconstruction, so it is complementary to current methods and can be expanded to other background sources.

physics.ins-det↗