Global fits of scalar singlet dark matter with GAMBIT

TL;DR

This paper introduces GAMBIT, a versatile framework for global fits of BSM theories, demonstrated through preliminary analysis of scalar singlet dark matter using diverse experimental data.

Contribution

The paper presents GAMBIT, a new flexible tool for comprehensive global fits of BSM models, integrating multiple experimental constraints.

Findings

Preliminary scalar singlet dark matter parameter space constraints.

GAMBIT effectively combines diverse experimental data.

Initial results demonstrate the framework's capabilities.

Abstract

The wide range of probes of physics beyond the standard model leads to the need for tools that combine experimental results to make the most robust possible statements about the validity of theories and the preferred regions of their parameter space. Here we introduce a new code for such analyses: GAMBIT, the Global and Modular BSM Inference Tool. GAMBIT is a flexible and extensible framework for global fits of essentially any BSM theory. The code currently incorporates direct and indirect searches for dark matter, limits on production of new particles from the LHC and LEP, complete flavor constraints from LHCb, LHC Higgs production and decay measurements, and various electroweak precision observables. Here we present an overview of the code's capabilities, followed by preliminary results from scans of the scalar singlet dark matter model.