Search for Neutrinoless Double-Beta Decay with the Complete EXO-200 Dataset

Abstract

A search for neutrinoless double-beta decay ($0\nu\beta\beta$) in $^{136}$Xe is performed with the full EXO-200 dataset using a deep neural network to discriminate between $0\nu\beta\beta$ and background events. Relative to previous analyses, the signal detection efficiency has been raised from 80.8% to 96.4$\pm$3.0% and the energy resolution of the detector at the Q-value of $^{136}$Xe $0\nu\beta\beta$ has been improved from $\sigma/E=1.23\%$ to $1.15\pm0.02\%$ with the upgraded detector. Accounting for the new data, the median 90% confidence level $0\nu\beta\beta$ half-life sensitivity for this analysis is $5.0 \cdot 10^{25}$ yr with a total $^{136}$Xe exposure of 234.1 kg$\cdot$yr. No statistically significant evidence for $0\nu\beta\beta$ is observed, leading to a lower limit on the $0\nu\beta\beta$ half-life of $3.5\cdot10^{25}$ yr at the 90% confidence level.