Analysis of simulated data for the KArlsruhe TRItium Neutrino experiment using Bayesian inference

The KATRIN (Karlsruhe Tritium Neutrino) experiment will analyze the tritium β spectrum to determine the mass of the neutrino with a sensitivity of 0.2 eV (90% C.L.). This approach to a measurement of the absolute value of the neutrino mass relies only on the principle of energy conservation and can in some sense be called model-independent as compared to cosmology and neutrinoless double β decay. However, by model independent we only mean in case of the minimal extension of the standard model. One should therefore also analyze the data for nonstandard couplings to, e.g., right-handed or sterile neutrinos. As an alternative to the frequentist minimization methods used in the analysis of the earlier experiments in Mainz and Troitsk we have been investigating Markov chain Monte Carlo (MCMC) methods which are very well suited for probing multiparameter spaces. We found that implementing the KATRIN χ2 function in the cosmomc package - an MCMC code using Bayesian parameter inference - solved the task at hand very nicely.