The redshift evolution of massive galaxy clusters in the MACSIS simulations

TL;DR

This study uses the MACSIS simulations to analyze the evolution of massive galaxy clusters, revealing deviations from self-similar models and emphasizing the importance of selection effects in cluster property calibration.

Contribution

The paper introduces the MACSIS simulation suite, extending previous models to higher masses, and provides detailed predictions on the redshift evolution of cluster properties considering selection effects.

Findings

Scaling relations deviate from self-similar predictions.

Hot cluster samples align more closely with self-similar models.

Profiles of hot gas match observations at different redshifts.

Abstract

We present the MAssive ClusterS and Intercluster Structures (MACSIS) project, a suite of 390 clusters simulated with baryonic physics that yields realistic massive galaxy clusters capable of matching a wide range of observed properties. MACSIS extends the recent BAHAMAS simulation to higher masses, enabling robust predictions for the redshift evolution of cluster properties and an assessment of the effect of selecting only the hottest systems. We study the observable-mass scaling relations and the X-ray luminosity-temperature relation over the complete observed cluster mass range. As expected, we find the slope of these scaling relations and the evolution of their normalization with redshift departs significantly from the self-similar predictions. However, for a sample of hot clusters with core-excised temperatures $k_{\rm{B}}T\geq5\,\rm{keV}$ the normalization and slope of the observable-mass relations and their evolution are significantly closer to self-similar. The exception is the temperature-mass relation, for which the increased importance of non-thermal pressure support and biased X-ray temperatures leads to a greater departure from self-similarity in the hottest systems. As a consequence, these also affect the slope and evolution of the normalization in the luminosity-temperature relation. The median hot gas profiles show good agreement with observational data at $z=0$ and $z=1$, with their evolution again departing significantly from the self-similar prediction. However, selecting a hot sample of clusters yields profiles that evolve significantly closer to the self-similar prediction. In conclusion, our results show that understanding the selection function is vital for robust calibration of cluster properties with mass and redshift.