Abstract
Modified gravity theories are a popular research field in the hope that they could explain some of the unanswered questions in cosmology, for example how the universe starts, evolves and ends. One way to test proposed modified gravity models is by analyzing how the model affects the evolution of large scale structures in the universe. In the non-linear regime the only way of doing this is by performing N-body simulations, which simulates how a dynamical system of particles behave and evolve under the influence of physical forces. After performing such a simulation we wish to compare the data from the simulation with the observed universe. This cannot be done directly from the output from N-body simulations. To extract the necessary statistics a halo finding process should be performed, which determine how galaxies are grouped into halos and calculates the properties of these halos. As of yet, no one has taken into account the differences between standard general relativity and modified gravity in their halo finders, so the validity of other halo finders in the regime of modified gravity is therefore unknown.
This is what has been the focus of this thesis. Here, we introduce MORPH, the first halo finder that is completely independent of the gravity model used in the Nbody simulations. MORPH can analyze any dataset from a modified gravity N-body simulation. This is performed without the need for code modifications to accommodate for the modified gravity theory. As a part of this work we have examined various unbinding algorithms and their dependence on the gravity model. The main question this thesis set out to answer was whether there is a justified need for a modified gravity adjusted halo finder. The conclusion is that modified gravity must be taken into consideration when we intend to analyze halos in modified gravity datasets. However, only if the halo finders have a high unbinding percentage, making the errors from the unbinding routine larger than the current 10% error bars for halo finding.
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Veileder: David F. Mota/Nicolaas Groeneboom
Intern sensor: Luc Rouppe van der Voort
Ekstern sensor: Sigurd K. Næss, University of Oxford, England