Quark and lepton masses from Gaussian landscapes

The flavor structure of the standard model (SM) might arise from random selection on a landscape. We propose a class of simple models, Gaussian landscapes, where Yukawa couplings derive from overlap integrals of Gaussian wave functions on extra-dimensions. Statistics of vacua are generated by scanning the peak positions of these zero-modes, giving probability distributions for all flavor observables. Gaussian landscapes can account for all observed flavor patterns with few free parameters. Although they give broad probability distributions, the predictions are correlated and accounting for measured parameters sharpens the distributions of future neutrino measurements.