Weak lensing measurement of galaxy clusters in the CFHTLS-Wide survey

TL;DR

This paper presents the first weak lensing analysis of the CFHTLS-Wide survey, producing a large mass map and identifying galaxy clusters consistent with cosmological models, demonstrating the method's potential for future surveys.

Contribution

It introduces a comprehensive weak lensing analysis of the CFHTLS-Wide survey, including a large convergence map and cluster identification, validated against optical and X-ray data.

Findings

Largest weak lensing convergence map to date

Identified 301 peaks with high signal-to-noise ratio

Confirmed 85 galaxy groups/clusters with optical and X-ray counterparts

Abstract

We present the first weak gravitational lensing analysis of the completed Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). We study the 64 square degrees W1 field, the largest of the CFHTLS-Wide survey fields, and present the largest contiguous weak lensing convergence "mass map" yet made. 2.66 million galaxy shapes are measured, using a KSB pipeline verified against high-resolution Hubble Space Telescope imaging that covers part of the CFHTLS. Our i'-band measurements are also consistent with an analysis of independent r'-band imaging. The reconstructed lensing convergence map contains 301 peaks with signal-to-noise ratio {\nu}>3.5, consistent with predictions of a {\Lambda}CDM model. Of these peaks, 126 lie within 3.0' of a BCG identified from multicolor optical imaging in an independent, red sequence survey. We also identify 7 counterparts for massive clusters previously seen in X-ray emission within 6 square degrees XMM-LSS survey. With photometric redshift estimates for the source galaxies, we use a tomographic lensing method to fit the redshift and mass of each convergence peak. Matching these to the optical observations, we confirm 85 groups/clusters with \chi^2 reduced < 3.0, at a mean redshift <z_c> = 0.36 and velocity dispersion <\sigma_c> = 658.8 km/s. Future surveys, such as DES, LSST, KDUST and EUCLID, will be able to apply these same techniques to map clusters in much larger volumes and thus tightly constrain cosmological models.