加载中…
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 and an effective Majorana phase parameter , we construct such a prior using two different approaches and compare them with the standard flat and logarithmic priors in .

生成讲解博客的中文版本

生成AI智能校验的中文版本