Gaussian covariance matrices for anisotropic galaxy clustering
  measurements
  Measurements of the redshift-space galaxy clustering have been a prolific
source of cosmological information in recent years. Accurate covariance
estimates are an essential step for the validation of galaxy clustering models
of the redshift-space two-point statistics. Usually, only a limited set of
accurate N-body simulations is available. Thus, assessing the data covariance
is not possible or only leads to a noisy estimate. Further, relying on
simulated realisations of the survey data means that tests of the cosmology
dependence of the covariance are expensive. With these points in mind, this
work presents a simple theoretical model for the linear covariance of
anisotropic galaxy clustering observations with synthetic catalogues.
Considering the Legendre moments (`multipoles') of the two-point statistics and
projections into wide bins of the line-of-sight parameter (`clustering
wedges'), we describe the modelling of the covariance for these anisotropic
clustering measurements for galaxy samples with a trivial geometry in the case
of a Gaussian approximation of the clustering likelihood. As main result of
this paper, we give the explicit formulae for Fourier and configuration space
covariance matrices. To validate our model, we create synthetic HOD galaxy
catalogues by populating the haloes of an ensemble of large-volume N-body
simulations. Using linear and non-linear input power spectra, we find very good
agreement between the model predictions and the measurements on the synthetic
catalogues in the quasi-linear regime.
