Erlangen 2026 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 13: Higgs Physics II
T 13.7: Vortrag
Montag, 16. März 2026, 17:45–18:00, KH 02.013
Machine learning in the 2HDM2S model for dark matter — •Rafael Boto1, Tiago Rebelo2, Jorge Romão2, and João Silva2 — 1Institute for Theoretical Physics, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany — 2CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av Rovisco Pais, 1, P-1049-001 Lisboa, Portugal
In this work, we build a two real scalar singlet extension of the two Higgs doublet model to answer the dark matter problem. We study the vacuum structure, the bounded from below conditions, the restrictions from the oblique parameters S,T and U, as well as the unitarity constraints. We submit the model to collider and Dark Matter experimental constraints and explore its allowed parameter space. We compare randomly populated simulations, simulations starting near the alignment limit, and a Machine Learning based exploration to find viable solutions.
Keywords: Multi-Higgs Models; Dark Matter; Higgs model; Beyond the standard model; symmetry: Z2 x Z2