Results from a search for neutrinoless double-beta decay (0νββ) of ^{136}Xe are presented using the first year of data taken with the upgraded EXO-200 detector. Relative to previous searches by EXO-200, the energy resolution of the detector has been improved to σ/E=1.23%, the electric field in the drift region has been raised by 50%, and a system to suppress radon in the volume between the cryostat and lead shielding has been implemented. In addition, analysis techniques that improve topological discrimination between 0νββ and background events have been developed. Incorporating these hardware and analysis improvements, the median 90% confidence level 0νββ half-life sensitivity after combining with the full data set acquired before the upgrade has increased twofold to 3.7×10^{25}  yr. No statistically significant evidence for 0νββ is observed, leading to a lower limit on the 0νββ half-life of 1.8×10^{25}  yr at the 90% confidence level.

We report on an improved measurement of the 2νββ half-life of 136 Xe performed by EXO-200. The use of a large and homogeneous time projection chamber allows for the precise estimate of the fiducial mass used for the measurement, resulting in a small systematic uncertainty. We also discuss in detail the data analysis methods used for double-beta decay searches with EXO-200, while emphasizing those directly related to the present measurement. The 136 Xe 2νββ half-life is found to be T 2νββ 1/2 = 2.165 ± 0.016(stat) ± 0.059(sys) · 10 21 years. This is the most precisely measured half-life of any 2νββ decay to date.

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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 Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by SCOAP 3 .

The Institute for Genome Sciences (IGS) has developed a prokaryotic annotation pipeline that is used for coding gene/RNA prediction and functional annotation of Bacteria and Archaea. The fully automated pipeline accepts one or many genomic sequences as input and produces output in a variety of standard formats. Functional annotation is primarily based on similarity searches and motif finding combined with a hierarchical rule based annotation system. The output annotations can also be loaded into a relational database and accessed through visualization tools.