The WaZP galaxy cluster sample of the Dark Energy Survey Year 1

TL;DR

This paper introduces WaZP, a new galaxy cluster finder for DES Year 1 data, demonstrating its effectiveness by matching known clusters and comparing favorably with existing methods like redMaPPer and SPT.

Contribution

The paper presents WaZP, a novel wavelet-based photometric redshift cluster finder, and develops a new matching algorithm for comparing optical cluster samples.

Findings

WaZP detects over 60,000 clusters in DES Y1 data.

WaZP recovers all SPT SZ clusters within the survey overlap.

High agreement (95%) with redMaPPer for rich clusters.

Abstract

We present a new (2+1)D galaxy cluster finder based on photometric redshifts called Wavelet Z Photometric (WaZP) applied to DES first year (Y1A1) data. The results are compared to clusters detected by the South Pole Telescope (SPT) survey and the redMaPPer cluster finder, the latter based on the same photometric data. WaZP searches for clusters in wavelet-based density maps of galaxies selected in photometric redshift space without any assumption on the cluster galaxy populations. The comparison to other cluster samples was performed with a matching algorithm based on angular proximity and redshift difference of the clusters. It led to the development of a new approach to match two optical cluster samples, following an iterative approach to minimize incorrect associations. The WaZP cluster finder applied to DES Y1A1 galaxy survey (1,511 deg2 up to i=23 mag) led to the detection of 60,547 galaxy clusters with redshifts 0.05<z<0.9 and richness Ngals>5. Considering the overlapping regions and redshift ranges between the DES Y1A1 and SPT cluster surveys, all SZ based SPT clusters are recovered by the WaZP sample.The comparison between WaZP and redMaPPer cluster samples showed an excellent overall agreement for clusters with richness Ngals ({\lambda} for redMaPPer) greater than 25 (20), with 95% recovery on both directions. Based on the cluster cross-match we explorethe relative fragmentation of the two cluster samples and investigate the possible signatures of unmatched clusters.