Galaxy cluster profiles: A Gaussian mixture model approach to halo miscentering

TL;DR

This paper introduces a Gaussian mixture model approach to better estimate and correct for miscentering bias in galaxy cluster profile measurements, improving accuracy for cosmological analyses.

Contribution

It proposes an alternative method using individual cluster profiles with Gaussian mixture models, enhancing miscentering parameter estimation over traditional stacked profile models.

Findings

Significantly improved miscentering parameter estimates.

Effective application to both 3D and 2D profiles.

Potential for better bias correction in upcoming surveys.

Abstract

Measurements of the galaxy density and weak-lensing profiles of galaxy clusters typically rely on an assumed cluster center, which is taken to be the brightest cluster galaxy or other proxies for the true halo center. Departure of the assumed cluster center from the true halo center bias the resultant profile measurements, an effect known as miscentering bias. Currently, miscentering is typically modeled in stacked profiles of clusters with a two parameter model. We use an alternate approach in which the profiles of individual clusters are used with the corresponding likelihood computed using a Gaussian mixture model. We test the approach using halos and the corresponding subhalo profiles from the IllustrisTNG hydrodynamic simulations. We obtain significantly improved estimates of the miscentering parameters for both 3D and projected 2D profiles relevant for imaging surveys. We discuss applications to upcoming cosmological surveys.