Discovery of a Rich Cluster at z = 1.63 using the Rest-Frame 1.6um "Stellar Bump Sequence" Method
Adam Muzzin, Gillian Wilson, Ricardo Demarco, Chris Lidman, Julie, Nantais, Henk Hoekstra, H. K. C. Yee, Alessandro Rettura

TL;DR
The paper introduces the Stellar Bump Sequence (SBS) method, a new two-color algorithm for identifying high-redshift galaxy clusters using optical and mid-infrared data, successfully discovering a cluster at z=1.63.
Contribution
The paper presents the SBS algorithm, combining optical and MIR colors to robustly detect high-redshift clusters and demonstrates its effectiveness with new cluster discovery and validation.
Findings
SBS effectively identifies high-redshift clusters in wide-field data.
The stellar bump sequence color correlates with redshift, enabling accurate photometric redshifts.
Discovery of a new cluster at z=1.63 confirmed with spectroscopic redshifts.
Abstract
We present a new two-color algorithm, the "Stellar Bump Sequence" (SBS), that is optimized for robustly identifying candidate high-redshift galaxy clusters in combined wide-field optical and mid-infrared (MIR) data. The SBS algorithm is a fusion of the well-tested cluster red-sequence method of Gladders & Yee (2000) with the MIR 3.6um - 4.5um cluster detection method developed by Papovich (2008). As with the cluster red-sequence method, the SBS identifies candidate overdensities within 3.6um - 4.5um color slices, which are the equivalent of a rest-frame 1.6um stellar bump "red-sequence". In addition to employing the MIR colors of galaxies, the SBS algorithm incorporates an optical/MIR (z' - 3.6um) color cut. This cut effectively eliminates foreground 0.2 < z < 0.4 galaxies which have 3.6um - 4.5um colors that are similarly red as z > 1.0 galaxies and add noise when searching for…
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