The redMaPPer Galaxy Cluster Catalog From DES Science Verification Data

TL;DR

This paper updates the redMaPPer algorithm for galaxy cluster detection, applying it to DES and SDSS data, resulting in extensive catalogs with high photometric redshift accuracy and consistent mass estimates, demonstrating its effectiveness for large surveys.

Contribution

The paper introduces improvements to the redMaPPer algorithm and applies it to new DES SV and SDSS data, producing large, accurate galaxy cluster catalogs with validated mass and redshift estimates.

Findings

DES SV catalog contains 786 clusters with high richness and redshift accuracy.

Photometric redshift uncertainties are controlled at ~0.01 for z<0.7.

Mass--richness scatter and centering performance are consistent with prior expectations.

Abstract

We describe updates to the \redmapper{} algorithm, a photometric red-sequence cluster finder specifically designed for large photometric surveys. The updated algorithm is applied to $150\,\mathrm{deg}^2$ of Science Verification (SV) data from the Dark Energy Survey (DES), and to the Sloan Digital Sky Survey (SDSS) DR8 photometric data set. The DES SV catalog is locally volume limited, and contains 786 clusters with richness $\lambda>20$ (roughly equivalent to $M_{\rm{500c}}\gtrsim10^{14}\,h_{70}^{-1}\,M_{\odot}$) and $0.2<z<0.9$. The DR8 catalog consists of 26311 clusters with $0.08<z<0.6$, with a sharply increasing richness threshold as a function of redshift for $z\gtrsim 0.35$. The photometric redshift performance of both catalogs is shown to be excellent, with photometric redshift uncertainties controlled at the $\sigma_z/(1+z)\sim 0.01$ level for $z\lesssim0.7$, rising to $\sim0.02$ at $z\sim0.9$ in DES SV. We make use of \emph{Chandra} and \emph{XMM} X-ray and South Pole Telescope Sunyaev-Zeldovich data to show that the centering performance and mass--richness scatter are consistent with expectations based on prior runs of \redmapper{} on SDSS data. We also show how the \redmapper{} \photoz{} and richness estimates are relatively insensitive to imperfect star/galaxy separation and small-scale star masks.