The parametrisation of cross sections for Dark Matter particle processes
Abstract: Experiments at particle colliders provide experimental verifications of theories in particle physics, and allow to search for new particles. Computer programs are used to simulate particle collisions. Those so-called event generators can be used to prove theories and compare their results to actual collisions from the colliders. Even though those programs run on powerful computer systems, the event generation takes long and is also cost-intensive. Therefore, the aim of this thesis is to reduce this computation time in the aid of searches for new particles. One of the goals of modern particle physics experiments, such as the ATLAS and CMS detectors at the Large Hadron Collider, is to shed light on the problem of Dark Matter. The presence of matter in our universe, beyond known matter, is motivated by gravitational interaction. In this project, I simulated particle collisions producing particles that exist in theories of Dark Matter. I then parametrised the cross sections of these processes, a measure for the probability of this process occurring, depending on parameters of the Dark Matter theory studied, the mediator mass and Dark Matter mass. This parametrisation was initially studied using a simulation of many Dark Matter signal points with different mediator mass and Dark Matter mass, and then applied to a grid with fewer simulated points. Altogether, the parametrisation derived from the grid with fewer points shows cross-sections that are consistent with those of the full grid of points. This allows the generation of fewer signal points and to parametrise them instead, which then results in a much shorter computation time. These results are used for a publication on the constraints of Dark Matter searches performed at ATLAS, a particle detector, which uses data from the Large Hadron Collider (LHC).
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