Statistical uncertainties and systematic errors in weak lensing mass estimates of galaxy clusters

TL;DR

This paper analyzes statistical and systematic uncertainties in weak lensing mass estimates of galaxy clusters, emphasizing the importance of addressing biases like miscentring and member galaxy contamination for upcoming large surveys.

Contribution

It provides a detailed assessment of systematic errors affecting weak lensing mass estimates and discusses mitigation strategies for future large-area surveys.

Findings

Member galaxy contamination significantly biases mass estimates in stacked analyses.

Miscentring can be a major source of bias but can be mitigated with priors from future missions.

Large surveys will reduce statistical noise, highlighting the importance of controlling systematics.

Abstract

Upcoming and ongoing large area weak lensing surveys will also discover large samples of galaxy clusters. Accurate and precise masses of galaxy clusters are of major importance for cosmology, for example, in establishing well calibrated observational halo mass functions for comparison with cosmological predictions. We investigate the level of statistical uncertainties and sources of systematic errors expected for weak lensing mass estimates. Future surveys that will cover large areas on the sky, such as Euclid or LSST and to lesser extent DES, will provide the largest weak lensing cluster samples with the lowest level of statistical noise regarding ensembles of galaxy clusters. However, the expected low level of statistical uncertainties requires us to scrutinize various sources of systematic errors. In particular, we investigate the bias due to cluster member galaxies which are erroneously treated as background source galaxies due to wrongly assigned photometric redshifts. We find that this effect is significant when referring to stacks of galaxy clusters. Finally, we study the bias due to miscentring, i.e., the displacement between any observationally defined cluster centre and the true minimum of its gravitational potential. The impact of this bias might be significant with respect to the statistical uncertainties. However, complementary future missions such as eROSITA will allow us to define stringent priors on miscentring parameters which will mitigate this bias significantly.