[Paper Review] Global fits of simplified models for dark matter with GAMBIT I. Scalar and fermionic models with s-channel vector mediators

Christopher J. Chang, Pat Scott+4 more|arXiv (Cornell University)|Sep 27, 2022

Particle physics theoretical and experimental studies4 citations

TL;DR

This paper performs global Bayesian fits of simplified dark matter models using the GAMBIT framework, focusing on scalar and fermionic dark matter candidates that interact with quarks via an s-channel vector mediator. It finds that large regions of parameter space survive for all models, with resonant regions (where DM mass ≈ half mediator mass) favored by LHC monojet excesses and relic density constraints, particularly for Dirac and Majorana fermion DM.

ABSTRACT

Simplified models provide a useful way to study the impacts of a small number of new particles on experimental observables and the interplay of those observables, without the need to construct an underlying theory. In this study, we perform global fits of simplified dark matter models with GAMBIT using an up-to-date set of likelihoods for indirect detection, direct detection and collider searches. We investigate models in which a scalar or fermionic dark matter candidate couples to quarks via an s-channel vector mediator. Large parts of parameter space survive for each model. In the case of Dirac or Majorana fermion dark matter, excesses in LHC monojet searches and relic density limits tend to prefer the resonance region, where the dark matter has approximately half the mass of the mediator. A combination of vector and axial-vector couplings to the Dirac candidate also leads to competing constraints from direct detection and unitarity violation.

Motivation & Objective

• To perform comprehensive global fits of simplified dark matter models using the GAMBIT software framework.
• To assess the viability of scalar and fermionic dark matter candidates coupled to quarks via an s-channel vector mediator against current experimental constraints.
• To identify surviving parameter space regions after applying constraints from direct detection, indirect detection, collider searches, and relic abundance measurements.
• To project the sensitivity of future experiments like CTA and DARWIN on the remaining viable parameter space.
• To explore the impact of LHC monojet excesses on model viability and the role of unitarity constraints in shaping the allowed parameter space.

Proposed method

• Utilizes the GAMBIT (Global Beyond-particle physics, Model-building, and Bayesian Inference Tool) framework for full Bayesian global fitting of simplified dark matter models.
• Applies a comprehensive set of likelihoods from direct detection (e.g., XENON1T, LUX), indirect detection (e.g., Fermi-LAT, HAWC), and collider searches (monojet and dijet final states) for LHC Run 2.
• Incorporates relic abundance constraints via the micrOMEGAs module to calculate the dark matter relic density and compare with Planck 2018 measurements.
• Performs Markov Chain Monte Carlo (MCMC) sampling to explore the full parameter space of each model, including couplings and masses.
• Uses nuisance parameter likelihoods to account for systematic uncertainties in experimental data.
• Projects future sensitivities using CTA and DARWIN simulations to assess the reach of upcoming experiments.

Experimental results

Research questions

• RQ1 Which regions of the parameter space for scalar and fermionic dark matter with s-channel vector mediators survive current experimental constraints?
• RQ2 How do LHC monojet excesses influence the preferred parameter space for Dirac and Majorana fermion dark matter models?
• RQ3 To what extent do relic density constraints and direct detection limits compete in shaping the viable parameter space?
• RQ4 How will future experiments like CTA and DARWIN constrain the remaining viable regions of the parameter space?
• RQ5 What is the impact of unitarity violation on the allowed coupling strengths in these simplified models?

Key findings

• For scalar dark matter, large regions of parameter space survive, especially at high DM masses and low mediator masses, provided the model does not fully account for the relic abundance.
• The Dirac fermion DM model shows a preference for resonant production (m_DM ≈ 0.5 × m_Mediator), with preferred masses around 260 GeV for DM and 540 GeV for the mediator, driven by LHC monojet excesses.
• When requiring the model to saturate the observed relic abundance, the preferred region shifts to higher masses: m_DM ≈ 580 GeV and m_Mediator ≈ 1.3 TeV.
• Assuming the LHC monojet excesses are background fluctuations, the parameter space opens significantly, allowing non-resonant regions to survive.
• The Majorana fermion DM model also fits the monojet excesses while satisfying relic density constraints, with a preference for resonant regions.
• Future experiments like CTA will be most sensitive to the Dirac fermion model, while DARWIN is expected to constrain tens to over a hundred signal events across all models, particularly affecting high-mediator-mass regions for scalar and Dirac DM.