arXiv · 2101.00428
Convergent Bayesian Global Fits of 4D Composite Higgs Models
Abstract
Models in which the Higgs boson is a composite pseudo-Nambu-Goldstone boson offer attractive solutions to the Higgs mass naturalness problem. We consider three such models based on the minimal $SO(5) \rightarrow SO(4)$ symmetry breaking pattern, and perform convergent global fits on the models under a Bayesian framework in order to find the regions of their parameter spaces that best fit a wide range of constraints, including recent Higgs measurements. We use a novel technique to analyse the fine-tuning of the models, quantifying the tuning as the Kullback-Leibler divergence from the prior to the posterior probability on the parameter space. Each model is found to be able to satisfy all constraints at the $3σ$ level simultaneously. As a by-product of the fits, we analyse the collider phenomenology of our models in these viable regions. In two of the three models, we find that the $g g \rightarrow H \rightarrow γγ$ cross section is less than ${\sim}90$% that predicted by the SM, which is already in slight tension with experiment and could potentially be ruled out in the future high-luminosity run of the LHC. In addition, the lightest fermions $F$ arising from the new strong dynamics in these models are seen in general to lie above ${\sim}1.1$ TeV, with the $F \rightarrow tW^{+}$ and $F \rightarrow \bar{b}W^{+}$ decays offering particularly promising channels for probing these models in future collider searches.
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Ethan Carragher, Will Handley, Daniel Murnane, Peter Stangl, Wei Su, Martin White, Anthony G. Williams. 2021-02-16. Convergent Bayesian Global Fits of 4D Composite Higgs Models. https://doi.org/10.1007/jhep05(2021)237
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