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We present the clustering of galaxy clusters as a useful addition to thecommon set of cosmological observables. The clustering of clusters probes thelarge-scale structure of the Universe, extending galaxy clustering analysis tothe high-peak, high-bias regime. Clustering of galaxy clusters complements thetraditional cluster number counts and observable-mass relation analyses,significantly improving their constraining power by breaking existingcalibration degeneracies. We use the maxBCG galaxy clusters catalogue toconstrain cosmological parameters and cross-calibrate the mass-observablerelation, using cluster abundances in richness bins and weak-lensing massestimates. We then add the redshift-space power spectrum of the sample,including an effective modelling of the weakly non-linear contribution andallowing for an arbitrary photometric redshift smoothing. The inclusion of thepower spectrum data allows for an improved self-calibration of the scalingrelation. 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 thismethod to constrain models of the early universe through the amount ofprimordial non-Gaussianity of the local type, using both the variation in thehalo mass function and the variation in the cluster bias. We find a constrainton the amount of skewness $f_{\mathrm{NL}} = 12 \pm 157 $ ($1\sigma$) from thecluster data alone.

Combining clustering and abundances of galaxy clusters to test cosmology and primordial non-Gaussianity