Speaker
Christopher Chang
(University of Queensland)
Description
GUM is a recent addition to the GAMBIT framework that auto-generates the necessary code to run global scans of BSM models. By reducing the time to setup global scans, GUM removes one of the barriers to studying many models simultaneously. In this work I demonstrate an application of this to multiple simplified dark matter models at once. I will discuss scans that include a range of observables from dark matter and collider searches to form a combined likelihood. This work has the potential to produce the most up-to-date constraints on some of the less studied models.
