On the accuracy of weak-lensing cluster mass reconstructions

TLDR: In this article, the bias and scatter in mass measurements of galaxy clusters resulting from fitting a spherically symmetric Navarro, Frenk, & White model to the reduced tangential shear profile measured in weak-lensing (WL) observations are studied.

Abstract: We study the bias and scatter in mass measurements of galaxy clusters resulting from fitting a spherically symmetric Navarro, Frenk, & White model to the reduced tangential shear profile measured in weak-lensing (WL) observations. The reduced shear profiles are generated for 104 cluster-sized halos formed in a ?CDM cosmological N-body simulation of a 1?h ?1 Gpc box. In agreement with previous studies, we find that the scatter in the WL masses derived using this fitting method has irreducible contributions from the triaxial shapes of cluster-sized halos and uncorrelated large-scale matter projections along the line of sight. Additionally, we find that correlated large-scale structure within several virial radii of clusters contributes a smaller, but nevertheless significant, amount to the scatter. The intrinsic scatter due to these physical sources is 20% for massive clusters and can be as high as 30% for group-sized systems. For current, ground-based observations, however, the total scatter should be dominated by shape noise from the background galaxies used to measure the shear. Importantly, we find that WL mass measurements can have a small, 5%-10%, but non-negligible amount of bias. Given that WL measurements of cluster masses are a powerful way to calibrate cluster mass-observable relations for precision cosmological constraints, we strongly emphasize that a robust calibration of the bias requires detailed simulations that include more observational effects than we consider here. Such a calibration exercise needs to be carried out for each specific WL mass estimation method, as the details of the method determine in part the expected scatter and bias. We present an iterative method for estimating mass M 500c that can eliminate the bias for analyses of ground-based data.