Galaxy Cluster Mass Reconstruction Project - IV. Understanding the effects of imperfect membership on cluster mass estimation

TL;DR

This study investigates how contamination and incompleteness in galaxy membership identification affect galaxy cluster mass estimates, revealing biases, scatter, and implications for cosmological measurements.

Contribution

It provides an empirical model quantifying the effects of imperfect membership on mass estimation and discusses how these effects depend on cluster mass and method used.

Findings

All methods are biased by contamination and incompleteness.

Applying corrections reduces scatter to shot noise levels.

Imperfect membership causes a flattening of the mass relation.

Abstract

The primary difficulty in measuring dynamical masses of galaxy clusters from galaxy data lies in the separation between true cluster members from interloping galaxies along the line of sight. We study the impact of membership contamination and incompleteness on cluster mass estimates obtained with 25 commonly used techniques applied to nearly 1000 mock clusters. We show that all methods overestimate or underestimate cluster masses when applied to contaminated or incomplete galaxy samples respectively. This appears to be the main source of the intrinsic scatter in the mass scaling relation. Applying corrections based on a prior knowledge of contamination and incompleteness can reduce the scatter to the level of shot noise expected for poorly sampled clusters. We establish an empirical model quantifying the effect of imperfect membership on cluster mass estimation and discuss its universal and method-dependent features. We find that both imperfect membership and the response of the mass estimators depend on cluster mass, effectively causing a flattening of the estimated - true mass relation. Imperfect membership thus alters cluster counts determined from spectroscopic surveys, hence the cosmological parameters that depend on such counts.