IIIT Hyderabad Publications |
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Cosmic acceleration sourced by slowly rolling scalar field and by the interaction between known components of matter in the UniverseAuthor: abhineet agarwal Date: 2019-01-07 Report no: IIIT/TH/2019/2 Advisor:Subhadip Mitra AbstractAbstract In this thesis, we investigate the possibility of sourcing late-time cosmic acceleration by a slowly rolling scalar field and by the large-scale modification of gravity without extra degrees of freedom. As for the slowly rolling scalar field, we consider a model based on a simple potential. We use geometric diagnostics to differentiate the underlying model from the cosmological constant one. With regard to the large-scale modification of gravity, we investigate a scenario in which the late-time cosmic acceleration might arise due to the coupling between dark matter and baryonic matter without resorting to the dark energy or large scale modification of gravity associated with extra degrees of freedom. The scenario can give rise to the late time acceleration in the Jordan frame and no acceleration in the Einstein frame - generic modification of gravity caused by the disformal coupling. In the Einstein frame, we have only matter and thereby no new degree of freedom. Dynamics gets complicated or modified in the Jordan frame with the appearance of an arbitrary coupling function. The altered dynamics gives rise to the acceleration. In this picture, there is no extra degree of freedom as there is none in the Einstein frame where the Lagrangian is diagonalized. Using a simple parametrisation for the coupling function, we constrain the model parameters by using the age constraints due to the globular cluster data. We also obtain the observational constraints on the parameters using H ( z ) + SNIa + BAO data sets. In this case, we distinguish between the phantom and the non-phantom acceleration and show that the model can give rise to the phantom behaviour in a narrow region of the parameter space. Full thesis: pdf Centre for Computational Natural Sciences and Bioinformatics |
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