On the origin of cool core galaxy clusters: comparing X-ray observations with numerical simulations.
HENNING J.W., GANTNER B., BURNS J.O. and HALLMAN E.J.
Abstract (from CDS):
To better constrain models of cool core galaxy cluster formation, we have used X-ray observations taken from the Chandra and ROSAT archives to examine the properties of cool core and noncool core clusters, especially beyond the cluster cores. Using an optimized reduction process, we produced X-ray images, surface brightness profiles, and hardness ratio maps of 30 nearby rich Abell clusters (17 cool cores and 13 noncool cores). We show that the use of double β models with cool core surface brightness profiles and single β models for noncool core profiles yield statistically significant differences in the slopes (i.e., β values) of the outer surface brightness profiles, but similar cluster core radii, for the two types of clusters. Hardness ratio profiles as well as spectroscopically fit temperatures suggest that noncool core clusters are warmer than cool core clusters of comparable mass beyond the cluster cores. We compared the properties of these clusters with the results from analogously reduced simulations of 88 numerical clusters created by the adaptive mesh refinement Enzo code. The simulated surface brightness profiles have steeper β-model fits in the outer cluster regions for both cool cores and noncool cores, suggesting additional intracluster medium (ICM) heating is required compared to observed cluster ICMs. Temperature and surface brightness profiles reveal that the simulated clusters are overcooled in their cores. As in the observations, however, simulated hardness ratio and temperature profiles indicate that noncool core clusters are warmer than cool core clusters of comparable mass far beyond the cluster cores. The general similarities between observations and simulations support a model described in Paper I suggesting that noncool core clusters suffered early major mergers destroying nascent cool cores. Differences between simulations and observations will be used to motivate new approaches to feedback in subsequent numerical models.