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 with the MIR 3.6 μm-4.5 μm cluster detection method developed by Papovich. As with the cluster red-sequence method, the SBS identifies candidate overdensities within 3.6 μm-4.5 μm color slices, which are the equivalent of a rest-frame 1.6 μm stellar bump "red-sequence." In addition to employing the MIR colors of galaxies, the SBS algorithm incorporates an optical/MIR (z′-3.6 μm) color cut. This cut effectively eliminates foreground 0.2 <z < 0.4 galaxies which have 3.6 μm-4.5 μm colors that are similarly red as z > 1.0 galaxies and add noise when searching for high-redshift galaxy overdensities. We demonstrate using the z ∼ 1 GCLASS cluster sample that similar to the red sequence, the stellar bump sequence appears to be a ubiquitous feature of high-redshift clusters, and that within that sample the color of the stellar bump sequence increases monotonically with redshift and provides photometric redshifts accurate to Δz = 0.05. We apply the SBS method in the XMM-LSS SWIRE field and show that it robustly recovers the majority of confirmed optical, MIR, and X-ray-selected clusters at z > 1.0 in that field. Lastly, we present confirmation of SpARCS J022427-032354 at z = 1.63, a new cluster detected with the method and confirmed with 12 high-confidence spectroscopic redshifts obtained using FORS2 on the Very Large Telescope. We conclude with a discussion of future prospects for using the algorithm.
Áreas temáticas de ASJC Scopus
- Astronomía y astrofísica
- Ciencias planetarias y espacial