Stacked Weak Lensing Mass Calibration: Estimators, Systematics, and Impact on Cosmological Parameter Constraints

TL;DR

This paper compares locally and globally normalized shear estimators in stacked weak lensing mass calibration, analyzing their systematics, biases, and impact on cosmological constraints in the DES.

Contribution

It evaluates the efficacy and systematics of both estimators in DES, highlighting their nearly identical precision and differences in contamination biases.

Findings

Both estimators have similar statistical precision after corrections.

Proper correction of higher order effects is essential to avoid biases.

Stacked weak lensing can calibrate cluster masses to about 2% precision.

Abstract

When extracting the weak lensing shear signal, one may employ either locally normalized or globally normalized shear estimators. The former is the standard approach when estimating cluster masses, while the latter is the more common method among peak finding efforts. While both approaches have identical signal-to-noise in the weak lensing limit, it is possible that higher order corrections or systematics considerations make one estimator preferable over the other. In this paper, we consider the efficacy of both estimators within the context of stacked weak lensing mass estimation in the Dark Energy Survey (DES). We find the two estimators have nearly identical statistical precision, even after including higher order corrections, but that these corrections must be incorporated into the analysis to avoid observationally relevant biases in the recovered masses. We also demonstrate that finite bin-width effects may be significant if not properly accounted for, and that the two estimators exhibit different systematics, particularly with respect to contamination of the source catalog by foreground galaxies. Thus, the two estimators may be employed as a systematics cross-check of each other. Stacked weak lensing in the DES should allow for the mean mass of galaxy clusters to be calibrated to about 2% precision (statistical only), which can improve the figure of merit of the DES cluster abundance experiment by a factor of ~3 relative to the self-calibration expectation. A companion paper (Schmidt & Rozo, 2010) investigates how the two types of estimators considered here impact weak lensing peak finding efforts.