Prospects for Determining the Mass Distributions of Galaxy Clusters on Large Scales Using Weak Gravitational Lensing

TL;DR

This paper evaluates the effectiveness of the Diemer & Kravstov (DK) density profile in describing galaxy cluster mass distributions from simulations, especially beyond the virial radius, comparing it to the traditional NFW model.

Contribution

It demonstrates that the DK profile better fits stacked weak lensing data, particularly for future surveys like LSST, and explores its dependence on cluster accretion history.

Findings

DK profile outperforms NFW in fitting cluster outskirts.

Future LSST data will benefit from DK profile modeling.

Cluster accretion history influences DK profile characteristics.

Abstract

For more than two decades, the Navarro, Frenk, and White (NFW) model has stood the test of time; it has been used to describe the distribution of mass in galaxy clusters out to their outskirts. Stacked weak lensing measurements of clusters are now revealing the distribution of mass out to and beyond their virial radii, where the NFW model is no longer applicable. In this study we assess how well the parameterised Diemer & Kravstov (DK) density profile describes the characteristic mass distribution of galaxy clusters extracted from cosmological simulations. This is determined from stacked synthetic lensing measurements of the 50 most massive clusters extracted from the Cosmo-OWLS simulations, using the Dark Matter Only run and also the run that most closely matches observations. The characteristics of the data reflect the Weighing the Giants survey and data from the future Large Synoptic Survey Telescope (LSST). In comparison with the NFW model, the DK model favored by the stacked data, in particular for the future LSST data, where the number density of background galaxies is higher. The DK profile depends on the accretion history of clusters which is specified in the current study. Eventually however subsamples of galaxy clusters with qualities indicative of disparate accretion histories could be studied.