Constraining the mass–richness relationship of redMaPPer clusters with angular clustering

• Main Authors: Baxter, Eric J., Rozo, Eduardo, Jain, Bhuvnesh, Rykoff, Eli, Wechsler, Risa H.
• Other Authors: Univ Arizona, Dept Phys
• Language: en
• Published: OXFORD UNIV PRESS 2016
• Subjects: methods: analytical; cosmology: observations; large-scale structure of Universe
• Online Access: http://hdl.handle.net/10150/622071; http://arizona.openrepository.com/arizona/handle/10150/622071

The potential of using cluster clustering for calibrating the mass-richness relation of galaxy clusters has been recognized theoretically for over a decade. Here, we demonstrate the feasibility of this technique to achieve high-precision mass calibration using redMaPPer clusters in the Sloan Digital Sky Survey North Galactic Cap. By including cross-correlations between several richness bins in our analysis, we significantly improve the statistical precision of our mass constraints. The amplitude of the mass-richness relation is constrained to 7 per cent statistical precision by our analysis. However, the error budget is systematics dominated, reaching a 19 per cent total error that is dominated by theoretical uncertainty in the bias-mass relation for dark matter haloes. We confirm the result from Miyatake et al. that the clustering amplitude of redMaPPer clusters depends on galaxy concentration as defined therein, and we provide additional evidence that this dependence cannot be sourced by mass dependences: some other effect must account for the observed variation in clustering amplitude with galaxy concentration. Assuming that the observed dependence of redMaPPer clustering on galaxy concentration is a form of assembly bias, we find that such effects introduce a systematic error on the amplitude of the mass-richness relation that is comparable to the error bar from statistical noise. The results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.