Weak lensing reconstructions in 2D & 3D: implications for cluster studies

TL;DR

This study compares 2D and 3D weak lensing mass mapping techniques, showing 3D methods are more effective at detecting galaxy clusters, especially at higher redshifts, and provide unbiased estimates of cluster properties.

Contribution

It demonstrates that 3D weak lensing reconstructions outperform 2D methods in cluster detection efficiency and accuracy, particularly at higher redshifts.

Findings

3D reconstructions detect clusters up to 10 times more effectively at high redshift.

Both methods are effective at low redshift, with comparable quality.

3D methods provide unbiased mass and redshift estimates of clusters.

Abstract

We compare the efficiency with which 2D and 3D weak lensing mass mapping techniques are able to detect clusters of galaxies using two state-of-the-art mass reconstruction techniques: MRLens in 2D and GLIMPSE in 3D. We simulate otherwise-empty cluster fields for 96 different virial mass-redshift combinations spanning the ranges $3\times10^{13}h^{-1}M_\odot \le M_{vir}\le 10^{15}h^{-1}M_\odot$ and $0.05 \le z_{\rm cl} \le 0.75$, and for each generate 1000 realisations of noisy shear data in 2D and 3D. For each field, we then compute the cluster (false) detection rate as the mean number of cluster (false) detections per reconstruction over the sample of 1000 reconstructions. We show that both MRLens and GLIMPSE are effective tools for the detection of clusters from weak lensing measurements, and provide comparable quality reconstructions at low redshift. At high redshift, GLIMPSE reconstructions offer increased sensitivity in the detection of clusters, yielding cluster detection rates up to a factor of $\sim 10\times$ that seen in 2D reconstructions using MRLens. We conclude that 3D mass mapping techniques are more efficient for the detection of clusters of galaxies in weak lensing surveys than 2D methods, particularly since 3D reconstructions yield unbiased estimators of both the mass and redshift of the detected clusters directly.