Combining clustering and abundances of galaxy clusters to test cosmology
  and primordial non-Gaussianity
  We present the clustering of galaxy clusters as a useful addition to the
common set of cosmological observables. The clustering of clusters probes the
large-scale structure of the Universe, extending galaxy clustering analysis to
the high-peak, high-bias regime. Clustering of galaxy clusters complements the
traditional cluster number counts and observable-mass relation analyses,
significantly improving their constraining power by breaking existing
calibration degeneracies. We use the maxBCG galaxy clusters catalogue to
constrain cosmological parameters and cross-calibrate the mass-observable
relation, using cluster abundances in richness bins and weak-lensing mass
estimates. We then add the redshift-space power spectrum of the sample,
including an effective modelling of the weakly non-linear contribution and
allowing for an arbitrary photometric redshift smoothing. The inclusion of the
power spectrum data allows for an improved self-calibration of the scaling
relation. We find that the inclusion of the power spectrum typically brings a
$\sim 50$ per cent improvement in the errors on the fluctuation amplitude
$\sigma_8$ and the matter density $\Omega_{\mathrm{m}}$. Finally, we apply this
method to constrain models of the early universe through the amount of
primordial non-Gaussianity of the local type, using both the variation in the
halo mass function and the variation in the cluster bias. We find a constraint
on the amount of skewness $f_{\mathrm{NL}} = 12 \pm 157 $ ($1\sigma$) from the
cluster data alone.
