NOvA 3-Flavor Neutrino Oscillation Analysis Using Bayesian Methods

NOvA is a long baseline neutrino oscillation experiment with a near and a far detector that uses Fermilab's NuMI beam. The far detector placed 810km from the target is used to measure neutrino oscillations through the ν_e appearance and ν_μ disappearance channels. New results featuring a 10-year dataset were recently presented under both a frequentist and Bayesian fitting framework. The Bayesian fits can be conducted comparatively quickly with high statistics without computationally-intensive Feldman-Cousins corrections necessary in the frequentist framework. Additionally, Bayesian sampling of the posterior makes it possible to measure oscillation parameters using only NOvA data and incorporate external constraints from reactor experiments later through a straightforward reweighting of the posterior. We perform fits with Bayesian Markov Chain Monte Carlo using two different algorithms: MR²T² and Hamiltonian Monte Carlo. An overview of the NOvA Bayesian fitting methods and their results for the 3-flavor oscillation analysis will be presented.