2019/06/30 by G. Anton, I. Badhrees, P. S. Barbeau +118 · 2 citations
Mathematics · Physics and Astronomy · #Algorithm #BETA (programming language) #Combinatorics #Computer science #Dark Matter and Cosmic Phenomena #Double beta decay #Energy (signal processing) #Mathematics #Neutrino #Neutrino Physics Research #Particle physics #Particle physics theoretical and experimental studies #Physics #Quantum mechanics #Statistics #hep-ex #nucl-ex
paper · pdf · doi:10.1103/physrevlett.123.161802
published as Phys. Rev. Lett. 123, 161802 (2019) · v1, 7 pages, 5 figures; v2, fix references; v3, update to accepted version
openalex created_date 2019/06/14 · arxiv created 2019/10/18 · openalex publication_date 2019/10/18 · arxiv updated 2019/10/21 · openalex updated_date 2026/08/05
A search for neutrinoless double-beta decay (0νββ) in 136Xe 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 136Xe 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 ⋅ 1025 yr with a total 136Xe 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⋅1025 yr at the 90% confidence level.