Abstract
We study the predictions for $CP$ phases and absolute neutrino mass scale for broad classes of models with a U(2)-like flavor symmetry. For this purpose we consider the same special textures in neutrino and charged lepton mass matrices that are successful in the quark sector. While in the neutrino sector the U(2) structure enforces two texture zeros, the contribution of the charged lepton sector to the Pontecorvo-Maki--Nakagawa--Sakata (PMNS) matrix can be parametrized by two rotation angles. Restricting to the cases where at least one of these angles is small, we obtain three representative scenarios. In all scenarios we obtain a narrow prediction for the sum of neutrino masses in the range of 60--75 meV, possibly in the reach of upcoming galaxy survey experiments. All scenarios can be excluded if near-future experimental date provide evidence for either neutrinoless double-beta decay or inverted neutrino mass ordering.
Highlights
Neutrino oscillation experiments have firmly established that neutrinos have tiny masses and large mixings
We study the predictions for CP phases and absolute neutrino mass scale for broad classes of models with a U(2)-like flavor symmetry
We have studied the predictions of a U(2) flavor symmetry for neutrino observables
Summary
Neutrino oscillation experiments have firmly established that neutrinos have tiny masses and large mixings. The U(2) structure typically leads to a characteristic pattern of fermion mass matrices mij, with m11 1⁄4 m13 1⁄4 m31 1⁄4 0 and m21 1⁄4 −m12, which makes this framework predictive despite the presence of the additional Oð1Þ parameters This feature allows us to study the consequences for neutrino observables in a broad class of U(2) models, without the need of specifying explicit flavor quantum numbers or Lagrangians. In the limit when there is no contribution from mixing in the charged lepton sector, this structure leads to a phenomenologically viable PMNS matrix with predictions for Dirac and Majorana phases and the overall mass scale, which are only limited by the uncertainty of the input parameters. These models lead to one-parameter deviations from the viable A2 texture, and are still predictive
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