Speaker
Description
Neutrino oscillation is so far the only experimental observation beyond the standard model. Many experiments have been set-up to measure the parameters governing the oscillation probabilities. Feldman-Cousins method is a unified approach to create frequentist confidence intervals near physical limits or with low statistics. It is broadly used in neutrino oscillation parameter extraction. However, the Feldman-Cousins method is very computationally expensive, on the order of tens of millions of CPU hours. In this work, we propose an iterative method using Gaussian Process to efficiently estimate a frequentist confidence contour for the neutrino oscillation parameters and show that it produces the same results at a small fraction of the computation cost of the standard Feldman-Cousins method.
