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A predictive and testable unified theory of fermion masses, mixing and leptogenesis

Fu, Bowen; King, Stephen F.; Marsili, Luca; Pascoli, Silvia; Turner, Jessica; Zhou, Ye-Ling

A predictive and testable unified theory of fermion masses, mixing and leptogenesis Thumbnail


Authors

Bowen Fu

Stephen F. King

Luca Marsili

Silvia Pascoli

Ye-Ling Zhou



Abstract

We consider a minimal non-supersymmetric SO(10) Grand Unified Theory (GUT) model that can reproduce the observed fermionic masses and mixing parameters of the Standard Model. We calculate the scales of spontaneous symmetry breaking from the GUT to the Standard Model gauge group using two-loop renormalisation group equations. This procedure determines the proton decay rate and the scale of U(1)B−L breaking, which generates cosmic strings and the right-handed neutrino mass scales. Consequently, the regions of parameter space where thermal leptogenesis is viable are identified and correlated with the fermion masses and mixing, the neutrinoless double beta decay rate, the proton decay rate, and the gravitational wave signal resulting from the network of cosmic strings. We demonstrate that this framework, which can explain the Standard Model fermion masses and mixing and the observed baryon asymmetry, will be highly constrained by the next generation of gravitational wave detectors and neutrino oscillation experiments which will also constrain the proton lifetime.

Citation

Fu, B., King, S. F., Marsili, L., Pascoli, S., Turner, J., & Zhou, Y. (2022). A predictive and testable unified theory of fermion masses, mixing and leptogenesis. Journal of High Energy Physics, 2022(11), Article 72. https://doi.org/10.1007/jhep11%282022%29072

Journal Article Type Article
Acceptance Date Oct 28, 2022
Online Publication Date Nov 14, 2022
Publication Date 2022
Deposit Date Jan 18, 2023
Publicly Available Date Jan 18, 2023
Journal Journal of High Energy Physics
Print ISSN 1126-6708
Publisher Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Peer Reviewed Peer Reviewed
Volume 2022
Issue 11
Article Number 72
DOI https://doi.org/10.1007/jhep11%282022%29072
Public URL https://durham-repository.worktribe.com/output/1185165

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.






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