Statistical Modeling and Markov Chain Monte Carlo Inference of the MAJORANA DEMONSTRATOR Background Data

Abstract

Observation of neutrinoless double-beta decay (0νββ) would establish lepton number violation, constrain the absolute neutrino mass scale, and imply the Majorana nature of neutrinos. Germanium-based 0νββ experiments are entering the tonne-scale era with discovery potential for half lives approaching 10^28 years, covering the region of effective Majorana neutrino masses indicative of the inverted ordering scenario for the three neutrino mass eigenstates. Sensitivity to such protracted decay rates requires < 0.1 background counts in the signal region per tonne-year of an experiment’s exposure, an order of magnitude improvement from current experiments observing tens of kilograms of 76Ge. Toward this goal, this work describes the simulation and analysis of 26.0 kilogram-years of background data from the MAJORANA DEMONSTRATOR, a 0νββ experiment operating an array of high-purity germanium detectors in a low-background environment at the Sanford Underground Research Facility. A latest analysis of this data yields a half life sensitivity of 4.8 × 10^25 years. Detailed simulation of the DEMONSTRATOR design and constraints on the radiopurity of its components facilitate Bayesian statistical modeling of the background data and Markov chain Monte Carlo sampling for inference of background sources, essential inputs for the next-generation tonne-scale experiment LEGEND.Doctor of Philosoph