# Constraining the inner density slope of massive galaxy clusters

## TL;DR

This study uses hydrodynamic simulations to assess how well the inner density slopes of massive galaxy clusters can be inferred from combined stellar kinematics and lensing data, revealing sensitivities and discrepancies with observational estimates.

## Contribution

It demonstrates that inner density slopes can be reasonably inferred from mock data and compares simulated cluster profiles with observational results, highlighting biases and differences.

## Key findings

- Inner density slopes can be inferred reasonably well from mock data.
- Simulated dark matter profiles are steeper than some observational estimates.
- Weak lensing constraints significantly influence slope estimates.

## Abstract

We determine the inner density profiles of massive galaxy clusters (M$_{200}$ > $5 \times 10^{14}$ M$_{\odot}$) in the Cluster-EAGLE (C-EAGLE) hydrodynamic simulations, and investigate whether the dark matter density profiles can be correctly estimated from a combination of mock stellar kinematical and gravitational lensing data. From fitting mock stellar kinematics and lensing data generated from the simulations, we find that the inner density slopes of both the total and the dark matter mass distributions can be inferred reasonably well. We compare the density slopes of C-EAGLE clusters with those derived by Newman et al. for 7 massive galaxy clusters in the local Universe. We find that the asymptotic best-fit inner slopes of "generalized" NFW (gNFW) profiles, ${\gamma}_{\rm gNFW}$, of the dark matter haloes of the C-EAGLE clusters are significantly steeper than those inferred by Newman et al. However, the mean mass-weighted dark matter density slopes of the simulated clusters are in good agreement with the Newman et al. estimates. We also find that the estimate of ${\gamma}_{\rm gNFW}$ is very sensitive to the constraints from weak lensing measurements in the outer parts of the cluster and a bias can lead to an underestimate of ${\gamma}_{\rm gNFW}$.