F. Marulli, A. Veropalumbo, M. Sereno, L. Moscardini, F. Pacaud, M. Pierre, M. Plionis, A. Cappi, C. Adami, S. Alis, B. Altieri, M. Birkinshaw, S. Ettori, L. Faccioli, F. Gastaldello, E. Koulouridis, C. Lidman, J.-P. Le Fèvre, S. Maurogordato, B. Poggianti, E. Pompei, T. Sadibekova, and I. Valtchanov
A&A Volume 620, December 2018 The XXL Survey: second series
Publication year: 2018


Context. Galaxy clusters trace the highest density peaks in the large-scale structure of the Universe. Their clustering provides a powerful probe that can be exploited in combination with cluster mass measurements to strengthen the cosmological constraints provided by cluster number counts.

Aims. We investigate the spatial properties of a homogeneous sample of X-ray selected galaxy clusters from the XXL survey, the largest programme carried out by the XMM-Newton satellite. The measurements are compared to Λ-cold dark matter predictions, and used in combination with self-calibrated mass scaling relations to constrain the effective bias of the sample, beff, and the matter density contrast, ΩM.

Methods. We measured the angle-averaged two-point correlation function of the XXL cluster sample. The analysed catalogue consists of 182 X-ray selected clusters from the XXL second data release, with median redshift ⟨z⟩ = 0.317 and median mass ⟨M500⟩≃ 1.3 × 1014M. A Markov chain Monte Carlo analysis is performed to extract cosmological constraints using a likelihood function constructed to be independent of the cluster selection function.

Results. Modelling the redshift-space clustering in the scale range 10 < r [h−1 Mpc] < 40, we obtain ΩM = 0.27−0.04+0.06 and beff = 2.73−0.20+0.18.

This is the first time the two-point correlation function of an X-ray selected cluster catalogue at such relatively high redshifts and low masses has been measured. The XXL cluster clustering appears fully consistent with standard cosmological predictions. The analysis presented in this work demonstrates the feasibility of a cosmological exploitation of the XXL cluster clustering, paving the way for a combined analysis of XXL cluster number counts and clustering.