An overview of DarkBit, the GAMBIT dark matter module

TL;DR

DarkBit is a module within GAMBIT that computes dark matter observables and likelihoods, integrating various experimental constraints to analyze the parameter space of models like the MSSM and assess future detection sensitivities.

Contribution

This paper provides a comprehensive overview of DarkBit's capabilities and demonstrates its application in scanning the MSSM parameter space with a focus on future dark matter search sensitivities.

Findings

DarkBit effectively incorporates multiple dark matter constraints.

GAMBIT scans identify key regions of MSSM parameter space.

Future dark matter searches could probe current best-fit regions.

Abstract

In this conference paper, I give an overview of the capabilities of DarkBit, a module of the GAMBIT global fitting code that calculates a range of dark matter observables and corresponding experimental likelihood functions. Included in the code are limits from the dark matter relic density, multiple direct detection experiments, and indirect searches in gamma-rays and neutrinos. I discuss the capabilities of the code, and then present recent results of GAMBIT scans of the parameter space of the minimal supersymmetric standard model, with a focus on sensitivities of future dark matter searches to the current best fit regions.