Selecting background galaxies in weak-lensing analysis of galaxy clusters

TL;DR

This paper introduces a new method for selecting background galaxies in weak lensing studies of galaxy clusters, using shear signals and color data, validated through simulations and real data, achieving accurate mass estimates.

Contribution

The novel approach combines shear analysis and color selection to identify background galaxies, reducing reliance on spectral data and improving mass estimation accuracy.

Findings

Method achieves mass estimates with ~98% accuracy.

Performance comparable to photometric redshift selection.

Validated on both simulations and real cluster data.

Abstract

In this paper, we present a new method to select the faint, background galaxies used to derive the mass of galaxy clusters by weak lensing. The method is based on the simultaneous analysis of the shear signal, that should be consistent with zero for the foreground, unlensed galaxies, and of the colors of the galaxies: photometric data from the COSMic evOlution Survey are used to train the color selection. In order to validate this methodology, we test it against a set of state-of-the-art image simulations of mock galaxy clusters in different redshift [$0.23-0.45$] and mass [$0.5-1.55\times10^{15}M_\odot$] ranges, mimicking medium-deep multicolor imaging observations (e.g. SUBARU, LBT). The performance of our method in terms of contamination by unlensed sources is comparable to a selection based on photometric redshifts, which however requires a good spectral coverage and is thus much more observationally demanding. The application of our method to simulations gives an average ratio between estimated and true masses of $\sim 0.98 \pm 0.09$. As a further test, we finally apply our method to real data, and compare our results with other weak lensing mass estimates in the literature: for this purpose we choose the cluster Abell 2219 ($z=0.228$), for which multi-band (BVRi) data are publicly available.