Abstract
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 234.1kg 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.
Highlights
Background errors Spectral shape agreementBackground model Other [8] Total errorSignal detection efficiency Fiducial volume Partial 3D cut Light-to-charge ratio Denoising misreconstructed Other [13] Phase I (%)2.8 < 0.4 0.9 ÁÁÁ < 1.0 3.1 Phase II (%)2.6 < 0.4 0.9 1.0 < 1.0 3.1 resolution at the 0νββ decay energy of Qββ 1⁄4 2457.83 Æ 0.37 keV [24]
A search for neutrinoless double-β decay (0νββ) in 136Xe is performed with the full EXO-200 dataset using a deep neural network to discriminate between 0νββ and background events
In addition to the new data acquired between June 2017 and October 2018, this search introduces several analysis developments to optimize the detector sensitivity to 0νββ, including the incorporation of a deep neural network (DNN) to discriminate between background and signal events
Summary
A search for neutrinoless double-β decay (0νββ) in 136Xe is performed with the full EXO-200 dataset using a deep neural network to discriminate between 0νββ and background events. Accounting for the new data, the median 90% confidence level 0νββ half-life sensitivity for this analysis is 5.0 × 1025 yr with a total 136Xe exposure of 234.1 kg yr.
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