Fitting NOvA physics model parameters with Markov Chain Monte Carlo

The NuMI Off-Axis ν_e Appearance (NOvA) experiment is an 810 km base-line neutrino oscillation experiment measuring the fundamental properties of neutrinos and antineutrinos, using the high statistics data from the Near Detector (ND) at Fermilab to produce predictions for the Far Detector in Minnesota. This talk demonstrates the use of Markov Chain Monte Carlo (MCMC) -- a Bayesian inference tool -- to identify best-fit values for NOvA's physics model parameters. By utilizing NOvA ND-only fake data along with NOvA's ND simulation of neutrino interactions and its corresponding parameters as input, MCMC obtains probable values for each parameter to best agree with the ND fake data. MCMC provides a meaningful technique to obtain the best fit for NOvA's physics model parameters and to learn how they can be constrained with NOvA data. This work marks progress towards achieving a simultaneous two-detector MCMC fit of NOvA's physics model parameters to measure the neutrino oscillation parameters, sin²(θ₂₃), Δm²₃₂, and δ_CP with its data.