Revisiting the universal texture zero of flavour: a Markov chain Monte Carlo analysis

We revisit the phenomenological predictions of the Universal Texture Zero (UTZ) model of flavour originally presented in [], and update them in light of both improved experimental constraints and numerical analysis techniques. In particular, we have developed an in-house Markov Chain Monte Carlo (MCMC) algorithm to exhaustively explore the UTZ's viable parameter space, considering both leading- and next-to-leading contributions in the model's effective operator product expansion. We also extract -- for the first time -- reliable UTZ predictions for the (poorly constrained) leptonic CP-violating phases, and ratio observables that characterize neutrino masses probed by (e.g.) oscillation, $\beta$-decay, and cosmological processes. We therefore dramatically improve on the proof-in-principle phenomenological analysis originally presented in [], and ultimately show that the UTZ remains a minimal, viable, and appealing theory of flavour. Our results also further demonstrate the potential of robustly examining multi-parameter flavour models with MCMC routines.