Constraints on non-unitary neutrino mixing in light of atmospheric and reactor neutrino data
Tetiana Kozynets, Philipp Eller, Alan Zander, Manuel Ettengruber, D. Jason Koskinen

TL;DR
This paper performs a Bayesian analysis of non-unitary neutrino mixing using atmospheric and reactor neutrino data, providing new detailed systematic uncertainty treatment and constraints on mixing matrix deviations from unitarity.
Contribution
It introduces a novel detailed systematic uncertainty treatment in Bayesian analysis of non-unitary neutrino mixing using atmospheric data.
Findings
Current data is compatible with both unitary and non-unitary models.
Bayesian analysis yields constraints on mixing matrix deviations from unitarity.
Future detectors will improve these constraints significantly.
Abstract
While the origin of neutrino masses remains unknown, several key neutrino mass generation models result in a non-unitary three-neutrino mixing matrix. To put such models to test, the deviations of the mixing matrix from unitarity can be measured directly through neutrino oscillation experiments. In this study, we perform a Bayesian analysis of the non-unitary mixing model using the recent public data from atmospheric and reactor neutrino experiments - namely IceCube-DeepCore, Daya Bay, and KamLAND. The novelty of our approach compared to the preceding global fits for non-unitarity is in the detailed treatment of the atmospheric neutrino data, which for the first time includes the relevant flux and detector systematic uncertainties. From the Bayesian posteriors on the individual mixing matrix elements, we derive the non-unitarity constraints in the form of normalisations and closures of…
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Taxonomy
TopicsNeutrino Physics Research · Astrophysics and Cosmic Phenomena · Particle physics theoretical and experimental studies
