Galaxy clusters in the CFHTLS. First matched filter candidate catalogue of the Deep fields

TL;DR

This paper presents a matched-filter algorithm applied to CFHTLS data to detect galaxy clusters, resulting in a catalogue of 162 candidates with estimated redshifts around 0.6, and assesses the detection efficiency and noise.

Contribution

It introduces a new matched-filter detection method applied to CFHTLS Deep fields and provides the first catalogue of cluster candidates with estimated redshifts and noise analysis.

Findings

Catalogue contains 162 galaxy cluster candidates.

Detection completeness is high up to z~0.7 for R>1 clusters.

Estimated noise frequency is approximately 17 detections per square degree.

Abstract

We apply a matched-filter cluster detection algorithm to the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) i-band data for the Deep-1, Deep-2, Deep-3 and Deep-4 fields covering a total of 4square degrees. To test the implemented procedure we carry out simulations for assessing the frequency of noise peaks as well as estimate the recovery efficiency. We estimate that up to z~0.7 the catalogue is essentially complete for clusters of richness class R>~1. The recovered redshifts are in general overestimated by dz=0.1 with a scatter of sigma_dz~0.1, except at redshifts z>~1 where the estimated redshifts are systematically underestimated. The constructed cluster candidate catalogue contains 162 detections over an effective area of 3.112 square degrees corresponding to a density of ~52.1 per square degree. The median estimated redshift of the candidates is z=0.6. The estimated noise frequency is 16.9+-5.4 detections per square degree. From visual inspection we identify systems that show a clear concentration of galaxies with similar colour. These systems have a density of ~20 per square degree.