Dark energy and modified theories of gravity
View/ Open
Date
10/07/2017Author
Lima, Nelson Daniel de Aguiar
Metadata
Abstract
It is now a consolidated fact that our Universe is undergoing an accelerated
expansion. According to Einstein's General Relativity, if the main constituents
of our Universe were ordinary and cold dark matter, then we would expect it to
be contracting and collapsing due to matter's attractive nature. The simplest
explanation we have for this acceleration is in the form of a component with a
negative ratio of pressure to density equal to -1 known as cosmological constant,
Λ , presently dominating over baryonic and cold dark matter.
However, the Λ Cold Dark Matter (Λ CDM) model suffers from a well known fine tuning problem. This led to the formulation of dark energy and modified gravity
theories as alternatives to the problem of cosmic acceleration. These theories
either include additional degrees of freedom, higher-order equations of motion,
extra dimensionalities or imply non-locality.
In this thesis we focus on single field scalar tensor theories embedded within
Horndeski gravity. Even though there is currently doubt on their ability to explain
cosmic acceleration without having a bare cosmological constant on their action,
the degree of freedom they introduce mediates an additional fifth force. And
while this force has to suppressed on Solar system scales, it can have interesting
and observable effects on cosmological scales.
Over the next decade there is a surge of surveys that will improve the
understanding of our Universe on the largest scales. Hence, in this work, we take
several different modified gravity theories and study their impact on cosmological
observables. We will analyze the dynamics of linear perturbations on these
theories and clearly highlight how they deviate from Λ CDM, allowing to break
the degeneracy at the background level. We will also study the evolution of the
gravitational potentials on sub horizon scales and provide simplified expressions
at this regime and, for some models, obtain constraints using the latest data.