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Published January 21, 2016 | Supplemental Material + Published
Journal Article Open

The RedGOLD cluster detection algorithm and its cluster candidate catalogue for the CFHT-LS W1


We present RedGOLD (Red-sequence Galaxy Overdensity cLuster Detector), a new optical/NIR galaxy cluster detection algorithm, and apply it to the CFHT-LS W1 field. RedGOLD searches for red-sequence galaxy overdensities while minimizing contamination from dusty star-forming galaxies. It imposes an Navarro–Frenk–White profile and calculates cluster detection significance and richness. We optimize these latter two parameters using both simulations and X-ray-detected cluster catalogues, and obtain a catalogue ∼80 per cent pure up to z ∼ 1, and ∼100 per cent (∼70 per cent) complete at z ≤ 0.6 (z ≲ 1) for galaxy clusters with M ≳ 10^(14) M_⊙ at the CFHT-LS Wide depth. In the CFHT-LS W1, we detect 11 cluster candidates per deg^2 out to z ∼ 1.1. When we optimize both completeness and purity, RedGOLD obtains a cluster catalogue with higher completeness and purity than other public catalogues, obtained using CFHT-LS W1 observations, for M ≳ 10^(14) M_⊙. We use X-ray-detected cluster samples to extend the study of the X-ray temperature–optical richness relation to a lower mass threshold, and find a mass scatter at fixed richness of σ_(lnM|λ) = 0.39 ± 0.07 and σ_(lnM|λ) = 0.30 ± 0.13 for the Gozaliasl et al. and Mehrtens et al. samples. When considering similar mass ranges as previous work, we recover a smaller scatter in mass at fixed richness. We recover 93 per cent of the redMaPPer detections, and find that its richness estimates is on average ∼40–50 per cent larger than ours at z > 0.3. RedGOLD recovers X-ray cluster spectroscopic redshifts at better than 5 per cent up to z ∼ 1, and the centres within a few tens of arcseconds.

Additional Information

© 2015 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2015 October 2. Received 2015 September 18. In original form 2015 May 9. First published online November 26, 2015. The Millennium Simulation data bases used in this paper and the web application providing online access to them were constructed as part of the activities of the German Astrophysical Virtual Observatory (GAVO). We warmly thank our referee for his/her constructive comments that improved this paper. We thank Eduardo Rozo for insightful discussions on the method and the comparison with the redmaPPer algorithm. We thank James G. Bartlett for the interesting discussions and for carefully editing the abstract and the conclusions. The French authors (RL, SM, and AR) acknowledge the support of the French Agence Nationale de la Recherche (ANR) under the reference ANR10- BLANC-0506-01-Projet VIRAGE (PI: S.Mei). SM acknowledges financial support from the Institut Universitaire de France (IUF), of which she is senior member. HH is supported by the DFG Emmy Noether grant Hi 1495/2-1. We thank the Observatory of Paris for hosting TE under its visitor programme.

Attached Files

Published - MNRAS-2016-Licitra-3020-41.pdf

Supplemental Material - Licitra2015_CFHTW1_MNRAS.zip


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August 20, 2023
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