The imminent era of large galaxy surveys (Dark Energy Survey, Euclid and Dark Energy Spectroscopic Instrument, among others) will soon drive a step change in our understanding of the standard cosmological model. Analytic control has traditionally come from the use of perturbation theory, but its reach is limited in scale and excludes a significant fraction of the modes visible to the surveys. N-body simulations could provide an alternative, but their computational time is extremely long. These pressures have produced research to enhance the standard perturbation theory and to appropriately model the redshift-space distortion power spectra that real surveys produce.
The analysis performed in this thesis is based on the effective field theory of large-scale structure (EFT). This yields encouraging results for the dark matter power spectrum, at the cost of adjustable counterterms that we estimate from a suite of custom N-body simulations performed using the gevolution numerical relativity code. We extend our analysis to haloes –concept used to refer to a more general notion: tracers of large-scale structures. There exists a statistical relation between the distribution of dark matter and haloes given by a set of bias parameters. As part of this analysis, we utilise the WizCOLA simulations –created to obtain covariance matrices for the WiggleZ survey.
In summary, we are in broad agreement with other methods employed in the literature. We include for the first time the full time dependence of the one-loop matter power spectrum using EFT and we are capable of probing smaller scales, k ≲ 0.74h/Mpc. Moreover, we achieve, for k ≲ 0.4h/Mpc, a ∼ 2% level of accuracy in real space and ∼ 5% for the monopole in redshift space. We also quantify how more complex modelling improves the fit for the halo multipoles. For future work, we find it relevant to use real observational data, e.g. WiggleZ dataset
