Optimization-based Bayesian sensitivity on neutrino mass and constraints on cosmology with the KATRIN experiment

The Karlsruhe Tritium Neutrino (KATRIN) experiment has pushed the direct bound of the neutrino mass down to sub-eV level in their first two scientific campaigns. The upcoming data release using a frequentist approach which includes the most recent three measurement campaigns is currently in preparation.

A comprehensive Bayesian analysis provides an alternative interpretation for the prior information and the neutrino mass results. Performing Bayesian sampling is computationally intensive and challenging when including all the systematic uncertainties, e.g. for the shifted analyzing plane configuration of the main spectrometer. New methods to optimize the model calculation will be presented, together with the Bayesian sensitivity for KATRIN's first five measurement campaigns. Constraints on cosmological models with the released data will also be presented within the Bayesian framework.