Results from a search for neutrinoless double-beta decay (0νββ) of ^{136}Xe are presented using the first year of data taken with the upgraded EXO-200 detector. Relative to previous searches by EXO-200, the energy resolution of the detector has been improved to σ/E=1.23%, the electric field in the drift region has been raised by 50%, and a system to suppress radon in the volume between the cryostat and lead shielding has been implemented. In addition, analysis techniques that improve topological discrimination between 0νββ and background events have been developed. Incorporating these hardware and analysis improvements, the median 90% confidence level 0νββ half-life sensitivity after combining with the full data set acquired before the upgrade has increased twofold to 3.7×10^{25} yr. No statistically significant evidence for 0νββ is observed, leading to a lower limit on the 0νββ half-life of 1.8×10^{25} yr at the 90% confidence level.
We apply deep neural networks (DNN) to data from the EXO-200 experiment. In the studied cases, the DNN is able to reconstruct the relevant parameters—total energy and position—directly from raw digitized waveforms, with minimal exceptions. For the first time, the developed algorithms are evaluated on real detector calibration data. The accuracy of reconstruction either reaches or exceeds what was achieved by the conventional approaches developed by EXO-200 over the course of the experiment. Most existing DNN approaches to event reconstruction and classification in particle physics are trained on Monte Carlo simulated events. Such algorithms are inherently limited by the accuracy of the simulation. We describe a unique approach that, in an experiment such as EXO-200, allows to successfully perform certain reconstruction and analysis tasks by training the network on waveforms from experimental data, either reducing or eliminating the reliance on the Monte Carlo.
Searches for double beta decay of 134 Xe were performed with EXO-200, a single-phase liquid xenon detector designed to search for neutrinoless double beta decay of 136 Xe. Using an exposure of 29.6 kg · yr, the lower limits of T 2νββ 1=2 > 8.7 × 10 20 yr and T 0νββ 1=2 > 1.1 × 10 23 yr at 90% confidence level were derived, with corresponding half-life sensitivities of 1.2 × 10 21 yr and 1.9 × 10 23 yr. These limits exceed those in * Permanent address: King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia. † Present address: P. N. Lebedev Physical Institute of the Russian Academy of Sciences,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.