Surveying the complex three Higgs doublet model with Machine Learning

Fuente: arXiv
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Autores principales: Boto, Rafael, Matos, João A. C., Romão, Jorge C., Silva, João P.
Formato: Preprint
Publicado: 2025
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author Boto, Rafael
Matos, João A. C.
Romão, Jorge C.
Silva, João P.
author_facet Boto, Rafael
Matos, João A. C.
Romão, Jorge C.
Silva, João P.
contents The couplings of the 125 GeV Higgs are being measured with higher precision as the Run 3 stage of LHC continues. Models with multiple Higgs doublets allow potential deviations from the SM predictions. For more than two doublets, there are five possible types of models that avoid flavor changing neutral couplings at tree level by the addition of a symmetry. We consider a softly broken Z2xZ2 three-Higgs doublet model with explicit CP violation in the scalar sector, exploring all five possible types of coupling choices and all five mass orderings of the neutral scalar bosons. The phenomenological study is performed using a Machine Learning black box optimization algorithm that efficiently searches for the possibility of large pseudoscalar Yukawa couplings. We identify the model choices that allow a purely pseudoscalar coupling in light of all recent experimental limits, including direct searches for CP-violation, thus motivating increased effort into improving the experimental precision.
format Preprint
id arxiv_https___arxiv_org_abs_2510_02445
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Surveying the complex three Higgs doublet model with Machine Learning
Boto, Rafael
Matos, João A. C.
Romão, Jorge C.
Silva, João P.
High Energy Physics - Phenomenology
The couplings of the 125 GeV Higgs are being measured with higher precision as the Run 3 stage of LHC continues. Models with multiple Higgs doublets allow potential deviations from the SM predictions. For more than two doublets, there are five possible types of models that avoid flavor changing neutral couplings at tree level by the addition of a symmetry. We consider a softly broken Z2xZ2 three-Higgs doublet model with explicit CP violation in the scalar sector, exploring all five possible types of coupling choices and all five mass orderings of the neutral scalar bosons. The phenomenological study is performed using a Machine Learning black box optimization algorithm that efficiently searches for the possibility of large pseudoscalar Yukawa couplings. We identify the model choices that allow a purely pseudoscalar coupling in light of all recent experimental limits, including direct searches for CP-violation, thus motivating increased effort into improving the experimental precision.
title Surveying the complex three Higgs doublet model with Machine Learning
topic High Energy Physics - Phenomenology
url https://arxiv.org/abs/2510.02445