On the Accuracy of Weak Lensing Cluster Mass Reconstructions

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 observations. The reduced shear profiles are generated for ~10^4 cluster-sized halos formed in a LCDM cosmological N-body simulation of a 1 Gpc/h box. In agreement with previous studies, we find that the scatter in the weak lensing 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 weak lensing mass measurements can have a small, ~5%-10%, but non-negligible amount of bias. Given that weak lensing 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 which include more observational effects than we consider here. Such a calibration exercise needs to be carried out for each specific weak lensing 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 M500c that can eliminate the bias for analyses of ground-based data.

• The paper quantifies that WL mass reconstructions exhibit up to 30% scatter due to halo triaxiality and projection effects.
• The study identifies a 5-10% bias in mass estimates, which can impact the precision of cosmological tests.
• The authors propose an iterative calibration method to refine mass estimates, emphasizing advanced corrections for observational errors.

Overview of Weak Lensing Cluster Mass Reconstructions

The study by Becker and Kravtsov examines the accuracy of estimating galaxy cluster masses using weak lensing (WL) techniques, specifically by fitting a Navarro-Frenk-White (NFW) model to the reduced tangential shear profiles of clusters. The research leverages large-scale cosmological simulations to quantify both the scatter and bias inherent in WL mass estimates of cluster-sized halos.

The paper confirms that scatter in WL mass measurements is influenced by multiple factors, primarily the triaxial nature of halos and projections of uncorrelated large-scale structures (LSS) along the line of sight. The study further reveals that correlated structures within a few virial radii also contribute significantly to the scatter, albeit to a lesser extent. The intrinsic scatter can be as high as 30% for group-sized systems, indicating that statistical noise is substantial for current observations, which primarily rely on ground-based measurements utilizing background galaxy shapes.

Importantly, the authors detect a small but non-negligible bias, typically 5-10%, in WL mass estimates. They suggest that this bias, if left uncorrected, can undermine the precision required for cosmological testing, where accurate mass-observable relations are fundamental. Through their simulations, Becker and Kravtsov propose an iterative method aimed at mitigating bias by refining mass estimates, particularly beneficial for analyses of ground-based data.

Key Findings and Implications

• Bias and Scatter: The study delineates that the scatter in WL cluster masses is significantly influenced by halo triaxiality and LSS projections. Bias induced by these factors necessitates robust calibration in mass estimates, emphasizing the importance of including additional observational effects in simulations.
• Methodology Calibration: By adopting a widely used NFW fitting procedure, the research demonstrates that statistical noise is often dominated by galaxy shape errors, highlighting the importance of developing more sophisticated, nuanced methods for each specific estimation approach.
• Iterative Improvement: The proposed iterative method shows promise for reducing biases in mass estimates obtained from WL data, although the need for further refinement is acknowledged, particularly for cosmologically relevant precision levels.
• Simulation-Based Approach: Utilizing a statistical sample of halos from a $\Lambda$CDM simulation framework enables the authors to address various systematic effects collectively, offering a comprehensive understanding of WL errors.

Future Directions

The authors call for more exhaustive simulation studies to reach optimal accuracy in future WL mass estimates, suggesting pathways to include realistic observational errors and considering baryonic physics, which was not accounted for in their dark matter-only simulations. Additionally, they urge examining the effects of alternative halo models and fitting methods, including strong lensing features, to evaluate their efficacy in enhancing mass estimation precision.

Given the increasing reliance on WL measurements for precision cosmology—particularly in probing dark energy and modified gravity models—the implications of this work extend deeply into planning and conducting future cosmological surveys, informing both observational strategies and theoretical frameworks.