Neutrino mass eigenstates and their ordering: a Bayesian approach

TL;DR

This paper uses a Bayesian approach to combine various experimental data to robustly determine the neutrino mass ordering, a key unresolved question in neutrino physics.

Contribution

It introduces a Bayesian framework that integrates oscillation, double beta decay, and CMB data to constrain neutrino mass ordering.

Findings

Provides probabilistic constraints on neutrino mass hierarchy

Demonstrates the effectiveness of Bayesian methods in neutrino physics

Offers insights into the likelihood of normal vs. inverted ordering

Abstract

One of the not-yet determined properties of neutrinos is the ordering of their mass eigenstates. We combine the available data from neutrino oscillations, neutrinoless double beta decay and Cosmic Microwave Background observations to derive robust constraints on the mass ordering in a Bayesian context. Based on arxiv:1801.04946.