Subhalo Abundance Matching in f(R) Gravity.

Using the liminality N-body simulations of Shi et al., we present the first predictions for galaxy clustering in f(R) gravity using subhalo abundance matching. We find that, for a given galaxy density, even for an f(R) model with f_{R0}=-10^{-6}, for which the cold dark matter clustering is very similar to the cold dark matter model with a cosmological constant (ΛCDM), the predicted clustering of galaxies in the f(R) model is very different from ΛCDM. The deviation can be as large as 40% for samples with mean densities close to that of L_{*} galaxies. This large deviation is testable given the accuracy that future large-scale galaxy surveys aim to achieve. Our result demonstrates that galaxy surveys can provide a stringent test of general relativity on cosmological scales, which is comparable to the tests from local astrophysical observations.

Creating synthetic universes in a computer.

Cosmologists regularly generate synthetic universes of galaxies using computer simulations. Such catalogues have an essential role to play in the analysis and exploitation of current and forthcoming galaxy surveys. I review the different ways in which synthetic or 'mock' catalogues are produced and discuss the different physical processes that the models attempt to follow, explaining why it is important to be as realistic as possible when trying to forge the Universe.