The Zen of Neutrino: Neutrinoless Double Beta Decay and Deep Learning
This event is part of the Departmental Seminars.
Neutrinoless Double Beta Decay (0νββ) is a hypothetical lepton-number-violating process and it's existence is one of the most important questions in particle physics. The discovery of 0νββ would answer persistent questions related to the intrinsic nature of neutrino mass and provide a window into physics beyond the Standard Model. KamLAND-Zen is one of the world-leading efforts in the search of 0νββ. Data was recently collected with 735 kg of Xe-136 and analyzed using a frequentist likelihood analysis to set a limit on the 0νββ half-life. In addition to the well-established frequentist approach, I conduct a Bayesian analysis with a Markov Chain Monte Carlo (MCMC). The Bayesian approach allows the use modern statistical tools and serves as an important cross check of the frequentist analysis. Furthermore, I developed a new machine learning event classification algorithm to increase sensitivity to the 0νββ half-life. In this talk, I will present the Bayesian analysis framework and a new result for the 0νββ half-life, in addition to future improvements with machine learning.
Join Zoom Meeting https://bostonu.zoom.us/j/7748832895
Meeting ID: 774 883 2895