Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen 91058, Germany.
Physics Department, Carleton University, Ottawa, Ontario K1S 5B6, Canada.
Phys Rev Lett. 2019 Oct 18;123(16):161802. doi: 10.1103/PhysRevLett.123.161802.
A search for neutrinoless double-β decay (0νββ) in ^{136}Xe is performed with the full EXO-200 dataset using a deep neural network to discriminate between 0νββ and background events. Relative to previous analyses, the signal detection efficiency has been raised from 80.8% to 96.4±3.0%, and the energy resolution of the detector at the Q value of ^{136}Xe 0νββ has been improved from σ/E=1.23% to 1.15±0.02% with the upgraded detector. Accounting for the new data, the median 90% confidence level 0νββ half-life sensitivity for this analysis is 5.0×10^{25} yr with a total ^{136}Xe exposure of 234.1 kg yr. No statistically significant evidence for 0νββ is observed, leading to a lower limit on the 0νββ half-life of 3.5×10^{25} yr at the 90% confidence level.
使用深度神经网络在 EXO-200 全数据集上搜索 ^{136}Xe 中微子无中微子双β衰变 (0νββ)。与以前的分析相比，信号探测效率从 80.8%提高到 96.4±3.0%，并且在升级后的探测器中，探测器在 ^{136}Xe 0νββ Q 值处的能量分辨率从 σ/E=1.23%提高到 1.15±0.02%。考虑到新数据，此分析的 90%置信水平 0νββ 半衰期灵敏度的中位数为 5.0×10^{25} yr，总 ^{136}Xe 暴露量为 234.1 kg yr。未观察到 0νββ 的统计显著证据，因此在 90%置信水平下，0νββ 的半衰期下限为 3.5×10^{25} yr。
