Global analyses of Higgs portal singlet dark matter models using GAMBIT

TL;DR

This paper conducts comprehensive global analyses of Higgs portal singlet dark matter models, evaluating their parameter spaces and Bayesian plausibility using GAMBIT, with updated experimental data and uncertainties.

Contribution

It provides the first combined Bayesian and frequentist analysis of vector, Majorana, and Dirac fermion Higgs portal dark matter models with recent data.

Findings

Parameter regions can explain all dark matter and fit data well.

Vector dark matter is slightly disfavoured due to tuning.

Fermionic dark matter favors CP violation to evade detection constraints.

Abstract

We present global analyses of effective Higgs portal dark matter models in the frequentist and Bayesian statistical frameworks. Complementing earlier studies of the scalar Higgs portal, we use GAMBIT to determine the preferred mass and coupling ranges for models with vector, Majorana and Dirac fermion dark matter. We also assess the relative plausibility of all four models using Bayesian model comparison. Our analysis includes up-to-date likelihood functions for the dark matter relic density, invisible Higgs decays, and direct and indirect searches for weakly-interacting dark matter including the latest XENON1T data. We also account for important uncertainties arising from the local density and velocity distribution of dark matter, nuclear matrix elements relevant to direct detection, and Standard Model masses and couplings. In all Higgs portal models, we find parameter regions that can explain all of dark matter and give a good fit to all data. The case of vector dark matter requires the most tuning and is therefore slightly disfavoured from a Bayesian point of view. In the case of fermionic dark matter, we find a strong preference for including a CP-violating phase that allows suppression of constraints from direct detection experiments, with odds in favour of CP violation of the order of 100:1. Finally, we present DDCalc 2.0.0, a tool for calculating direct detection observables and likelihoods for arbitrary non-relativistic effective operators.