Constraining the Mass-Richness Relationship of redMaPPer Clusters with Angular Clustering

Abstract

The potential of using cluster clustering for calibrating the mass-observable 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% statistical precision. However, the error budget is systematics dominated, reaching an 18% total error that is dominated by theoretical uncertainty in the bias-mass relation for dark matter halos. We perform a detailed treatment of the effects of assembly bias on our analysis, finding that the contribution of such effects to our parameter uncertainties is somewhat greater than that of measurement noise. We confirm the results from Miyatake et al. (2015) that the clustering amplitude of redMaPPer clusters depends on galaxy concentration, and provide additional evidence in support of this effect being due to some form of assembly bias. The results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.