Abstract
Spherical collapse is a crude, but useful toy model for structure formation in an expanding universe. Previous works have looked at this model in ΛCDM with massive neutrinos, where the primary findings were that massive neutrinos in general delay the formation of structure in the universe, but this is to some small extent counteracted by neutrinos clustering in the dark matter halo. One has also studied spherical collapse in DGP gravity, a form of modified gravity without a cosmological constant, where weakened gravity on large scales instead explain the accelerated expansion of the universe. This thesis aims to take the next step and look at combining the two approaches into one: Modelling spherical collapse with massive neutrinos and DGP gravity at the same time. Previous studies give us reason to expect certain degeneracies here - data might well be explained by both effects, making it difficult to pinpoint to what extent each influences observations. Investigating these degeneracies is therefore our goal. We design and implement an algorithm to investigate spherical collapse in Python 2, with initial conditions from a modified version of the CAMB code. We find that top-hat overdensities in DGP gravity with a similar background to ΛCDM in general collapse much later. In particular, for massless neutrino collapse in DGP to look like massive neutrino collapse in ΛCDM, the sum of neutrino masses needs to be at least 0.8 eV, well in excess of current cosmological upper bounds. In the absence of neutrino clustering, we observe the same difference of 0.8 eV with massive neutrinos in both cosmologies, but note a significant dependency on this number of the choice of h and r_c in DGP gravity. For an alternate parameter set, we need an even higher difference in total neutrino mass. This suggests that massive neutrinos with realistic masses may be unable to completely mask the effects of a modified theory of gravity, but we cannot rule out that there exists a combination of DGP parameters that cancels this effect.