Search for Two-neutrino Double-Beta Decay of to the excited state of with the Complete EXO-200 Dataset
arXiv:2303.01103 · doi:10.1088/1674-1137/aceee3
Abstract
A new search for two-neutrino double-beta () decay of to the excited state of is performed with the full EXO-200 dataset. A deep learning-based convolutional neural network is used to discriminate signal from background events. Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two. With the addition of the Phase II dataset taken with an upgraded detector, the median 90 confidence level half-life sensitivity of decay to the state of is using a total exposure of . No statistically significant evidence for decay to the state is observed, leading to a lower limit of at 90 confidence level, improved by 70 relative to the current world's best constraint.
9 pages, 7 figures, 2 tables
References in corpus (8)
- Final Results of GERDA on the Search for Neutrinoless Double- Decay
- and nuclear matrix elements in the interacting boson model with isospin restoration
- NEXO: Neutrinoless double beta decay search beyond year half-life sensitivity
- Measurement of the Drift Velocity and Transverse Diffusion of Electrons in Liquid Xenon with the EXO-200 Detector
- New Results for Double-Beta Decay of Mo-100 to Excited Final States of Ru-100 Using the TUNL-ITEP Apparatus
- A Statistical Analysis for the Neutrinoless Double-Beta Decay Matrix element of 48Ca
- The Majorana Demonstrator's Search for Double-Beta Decay of Ge to Excited States of Se
- KamNet: An Integrated Spatiotemporal Deep Neural Network for Rare Event Search in KamLAND-Zen