Least-informative priors for 0νββ decay searches

Bayesian parameter inference techniques require a choice of prior distribution, which can strongly impact the statistical conclusions drawn. We discuss the construction of least-informative priors for neutrinoless double beta decay searches. Such priors attempt to be objective by maximizing the information gain from an experimental setup. In a parametrization using the lightest neutrino mass m(l) and an effective Majorana phase parameter Phi, we construct such a prior using two different approaches and compare them with the standard flat and logarithmic priors in m(l).

Automated summary

Bayesian parameter inference techniques in neutrinoless double beta decay searches require a choice of prior distribution, which can strongly impact statistical conclusions. Least-informative priors are discussed to maximize information gain from an experimental setup in the parametrization of the lightest neutrino mass and an effective Majorana phase parameter.