The importance of interloper removal in galaxy clusters: saving more objects for the Jeans analysis

• Published in: Monthly notices of the Royal Astronomical Society Vol. 377; no. 2; pp. 843 - 854
• Main Authors: Wojtak, Radosław, Łokas, Ewa L.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 11.05.2007; Blackwell Science; Oxford University Press
• Subjects: Astronomy; Dark matter; Earth, ocean, space; Estimating techniques; Exact sciences and technology; galaxies: clusters: general; galaxies: clusters: individual: A576; galaxies: kinematics and dynamics; Kinematics; Stars & galaxies; galaxies: clusters: individual: A576; galaxies: clusters: general; galaxies: kinematics and dynamics; dark matter; Galaxies; Statistical moment; Estimator; Mass distribution; Velocity dispersion; Galaxy clusters; Dark matter; Anisotropy; Dynamics; Kinematics; Virial mass; Models; Performance
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1111/j.1365-2966.2007.11653.x

We study the effect of contamination by interlopers in kinematic samples of galaxy clusters. We demonstrate that without the proper removal of interlopers the inferred parameters of the mass distribution in the cluster are strongly biased towards higher mass and lower concentration. The interlopers are removed using two procedures previously shown to work most efficiently on simulated data. One is based on using the virial mass estimator and calculating the maximum velocity available to cluster members and the other relies on the ratio of the virial and projected mass estimators. We illustrate the performance of the methods in detail using the example of A576, a cluster with a strong uniform background contamination, and compare the case of A576 to 15 other clusters with different degree of contamination. We model the velocity dispersion and kurtosis profiles obtained for the cleaned data samples of these clusters solving the Jeans equations to estimate the mass, concentration and anisotropy parameter. We present the mass–concentration relation for the total sample of 22 clusters.