Precise clustering and density evolution of redMaPPer galaxy clusters versus MXXL simulation
We construct a large, redshift-complete sample of distant galaxy clusters by correlating Sloan Digital Sky Survey Data Release 12 redshifts with clusters identified with the red-sequence Matched-filter Probabilistic Percolation (redMaPPer) algorithm. Our spectroscopic completeness is > 97 per cent for ≃ 7000 clusters within the redMaPPer selection limit, z=0.325, so that our cluster correlation functions aremuch more precise than earlierwork and not suppressed by uncertain photometric redshifts.We derive an accurate power-law mass-richness relation from the observed abundance with respect to the mass function from Millennium XXL (MXXL) simulations, adjusted to the Planck-weighted cosmology. The number density of clusters is found to decline by 20 per cent over the range 0.1 < z < 0.3, in good agreement with the evolution predicted by MXXL. Our projected 3D correlation function scales with richness, λ, rising from r = 14 h Mpc at λ ≃25 to r = 22 h Mpc at λ ≃ 60, with a gradient that matches MXXL when applying our mass-richness relation, whereas the observed amplitude of the correlation function at 〈z〉 = 0.24 exceeds the MXXL prediction by 20 per cent at the ≃2.5σ level. This tension cannot be blamed on spurious, randomly located clusters as this would reduce the correlation amplitude. Full consistency between the correlation function and the abundances is achievable for the pre-Planck values of σ = 0.9, Ω = 0.25 and h = 0.73, matching the improved distance ladder estimate of the Hubble constant. ; TJB is supported by IKERBASQUE, the Basque Foundation for Science. RL is supported by the Spanish Ministry of Economy and Competitiveness through research projects FIS2010-15492 and Consolider EPI CSD2010-00064, and the University of the Basque Country UPV/EHU under program UFI 11/55. PJ acknowledges financial support from the Basque Government grant BFI-2012-349. TJB, RL and PJ are also supported by the Basque Government grant for the GIC IT956-16 research group. REA acknowledges support from AYA2015-66211-C2-2. JMD acknowledges support of the projects AYA2015-64508-P (MINECO/FEDER, UE), AYA2012-39475-C02-01 and the consolider project CSD2010-00064 funded by the Ministerio de Economia y Competitividad. KU acknowledges partial support from the Ministry of Science and Technology of Taiwan (grants MOST 103-2112-M-001-030-MY3 and MOST 103-2112-M-001-003-MY3). Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation and the US Department of Energy Office of Science. ; Peer Reviewed