Neutrino Mass Matrix Textures: A Data-driven Approach

TL;DR

This paper employs a data-driven, probabilistic approach to analyze neutrino mass matrix textures, considering both standard and sterile neutrino scenarios, to inform model building and future research directions.

Contribution

It introduces a novel probabilistic analysis of neutrino mass matrices using latest oscillation data, including sterile neutrinos, to explore correlations and constraints.

Findings

Probabilistic distributions of mass matrix elements derived from current data

Identification of correlations between matrix entries in different scenarios

Insights into future experimental constraints on neutrino mass textures

Abstract

We analyze the neutrino mass matrix entries and their correlations in a probabilistic fashion, constructing probability distribution functions using the latest results from neutrino oscillation fits. Two cases are considered: the standard three neutrino scenario as well as the inclusion of a new sterile neutrino that potentially explains the reactor and gallium anomalies. We discuss the current limits and future perspectives on the mass matrix elements that can be useful for model building.