Bayesian oscillation analysis of the NOvA data – Pierre Lasorak (Imperial College London)
48/2-224 - Madrone
SLAC
The NOvA (NuMI Off-axis Electron neutrino Appearance experiment) is a long baseline neutrino oscillation experiment based at Fermilab (IL) and Ash River (MN). It comprises an accelerator capable of providing an 850 kW proton beam that produces an intense flux of neutrinos, and two plastic scintillator detectors of 300 and 14,000 tonnes, placed off-axis at 1 and 810 km, respectively. Over the past ten years, NOvA has collected neutrino and anti-neutrino beam data and made leading measurements in electron neutrino appearance and neutrino mass ordering. In this talk, I will discuss NOvA’s latest neutrino long baseline oscillation results, which were presented at the Neutrino 2022 conference in Seoul. This analysis uses the 2020 dataset and employs two different Bayesian Markov Chain Monte Carlo techniques to make inferences on parameters from the PMNS matrix, the neutrino mass ordering and the Jarlskog invariant. I will first present the NOvA experiment and go through some details of its sensitivity. I will then describe the data sets and systematic uncertainties that were used and explain the Markov Chain Monte Carlo fitting techniques. Finally, I will present the data results.
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/98973156241?pwd=cEU5RFdlVXoyc0JTeTlDMkozKzQ5UT09
David Charles Goldfinger, Zhi Zheng
(dgoldfinger@stanford.edu, zzheng@slac)