Neutrino mixing and mass hierarchy in Gaussian landscapes

TL;DR

This paper explores how Gaussian landscape models in extra dimensions can naturally produce the observed flavor structure, including quark and lepton mixing patterns and neutrino mass hierarchies, through statistical distributions of wavefunction overlaps.

Contribution

It introduces Gaussian landscapes as a framework for deriving flavor observables from random wavefunction overlaps, explaining both quark and lepton mixing and neutrino mass hierarchy.

Findings

Gaussian landscapes reproduce observed flavor features.

Large lepton mixing results from broad wavefunctions.

Neutrino mass hierarchy depends on the number of right-handed neutrinos.

Abstract

The flavor structure of the Standard Model may arise from random selection on a landscape. In a class of simple models, called "Gaussian landscapes," Yukawa couplings derive from overlap integrals of Gaussian zero-mode wavefunctions on an extra-dimensional space. Statistics of vacua are generated by scanning the peak positions of these wavefunctions, giving probability distributions for all flavor observables. Gaussian landscapes can account for all of the major features of flavor, including both the small electroweak mixing in the quark sector and the large mixing observed in the lepton sector. We find that large lepton mixing stems directly from lepton doublets having broad wavefunctions on the internal manifold. Assuming the seesaw mechanism, we find the mass hierarchy among neutrinos is sensitive to the number of right-handed neutrinos, and can provide a good fit to neutrino oscillation measurements.