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Register a new userOn the Origin of Cool Core Galaxy Clusters: Comparing X-Ray Observations with Numerical Simulations
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Jason W. Henning
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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 non-cool core clusters, especially beyond the cluster cores. We produced X-ray images, surface brightness profiles, and hardness ratio maps of 30 nearby rich Abell clusters (17 cool cores and 13 non-cool cores). We show that the use of double beta-models with cool core surface brightness profiles and single beta-models for non-cool core profiles yield statistically significant differences in the slopes (i.e., beta 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 non-cool 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 AMR Enzo code. The simulated surface brightness profiles have steeper beta-model fits in the outer cluster regions for both cool cores and non-cool cores, suggesting additional ICM heating is required compared to observed cluster ICMs. Temperature and surface brightness profiles reveal that the simulated clusters are over-cooled in their cores. As in the observations, however, simulated hardness ratio and temperature profiles indicate that non-cool 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 Burns et al. 2008 suggesting that non-cool core clusters suffered early major mergers destroying nascent cool cores.
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We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non-cool-core systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and in observations. Furthermore, we also find that simulated cool-core clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic cool-core structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.
We examine deep XMM-Newton Reflection Grating Spectrometer (RGS) spectra from the cores of three X-ray bright cool core galaxy clusters, Abell 262, Abell 3581 and HCG 62. Each of the RGS spectra show Fe XVII emission lines indicating the presence of gas around 0.5 keV. There is no evidence for O VII emission which would imply gas at still cooler temperatures. The range in detected gas temperature in these objects is a factor of 3.7, 5.6 and 2 for Abell 262, Abell 3581 and HCG 62, respectively. The coolest detected gas only has a volume filling fraction of 6 and 3 per cent for Abell 262 and Abell 3581, but is likely to be volume filling in HCG 62. Chandra spatially resolved spectroscopy confirms the low volume filling fractions of the cool gas in Abell 262 and Abell 3581, indicating this cool gas exists as cold blobs. Any volume heating mechanism aiming to prevent cooling would overheat the surroundings of the cool gas by a factor of 4. If the gas is radiatively cooling below 0.5 keV, it is cooling at a rate at least an order of magnitude below that at higher temperatures in Abell 262 and Abell 3581 and two-orders of magnitude lower in HCG 62. The gas may be cooling non-radiatively through mixing in these cool blobs, where the energy released by cooling is emitted in the infrared. We find very good agreement between smooth particle inference modelling of the cluster and conventional spectral fitting. Comparing the temperature distribution from this analysis with that expected in a cooling flow, there appears to be a even larger break below 0.5 keV as compared with previous empirical descriptions of the deviations of cooling flow models.
The thermodynamic structure of hot gas in galaxy clusters is sensitive to astrophysical processes and typically difficult to model with galaxy formation simulations. We explore the fraction of cool-core (CC) clusters in a large sample of $370$ clusters from IllustrisTNG, examining six common CC definitions. IllustrisTNG produces continuous CC criteria distributions, the extremes of which are classified as CC and non-cool-core (NCC), and the criteria are increasingly correlated for more massive clusters. At $z=0$, the CC fractions for $2$ criteria are in reasonable agreement with the observed fractions but the other $4$ CC fractions are lower than observed. This result is partly driven by systematic differences between the simulated and observed gas fraction profiles. The simulated CC fractions with redshift show tentative agreement with the observed fractions, but linear fits demonstrate that the simulated evolution is steeper than observed. The conversion of CCs to NCCs appears to begin later and act more rapidly in the simulations. Examining the fraction of CCs and NCCs defined as relaxed we find no evidence that CCs are more relaxed, suggesting that mergers are not solely responsible for disrupting CCs. A comparison of the median thermodynamic profiles defined by different CC criteria shows that the extent to which they evolve in the cluster core is dependent on the CC criteria. We conclude that the thermodynamic structure of galaxy clusters in IllustrisTNG shares many similarities with observations, but achieving better agreement most likely requires modifications of the underlying galaxy formation model.
Cool-core clusters are characterized by strong surface brightness peaks in the X-ray emission from the Intra Cluster Medium (ICM). This phenomenon is associated with complex physics in the ICM and has been a subject of intense debate and investigation in recent years. In order to quantify the evolution in the cool-core cluster population, we robustly measure the cool-core strength in a local, representative cluster sample, and in the largest sample of high-redshift clusters available to date. We use high-resolution Chandra data of three representative cluster samples spanning different redshift ranges: (i) the local sample from the 400 SD survey with median z = 0.08, (ii) the high redshift sample from the 400 SD Survey with median z=0.59, and (iii) 15 clusters drawn from the RDCS and the WARPS, with median z = 0.83. Our analysis is based on the measurement of the surface brightness concentration, c_SB, which allows us to characterize the cool-core strength in low signal-to-noise data. We also obtain gas density profiles to derive cluster central cooling times and entropy. In addition to the X-ray analysis, we search for radio counterparts associated with the cluster cores. We find a statistically significant difference in the c_SB distributions of the two high-z samples, pointing towards a lack of concentrated clusters in the 400 SD high-z sample. Taking this into account, we confirm a negative evolution in the fraction of cool-core clusters with redshift, in particular for very strong cool-cores. This result is validated by the central entropy and central cooling time, which show strong anti-correlations with c_SB. However, the amount of evolution is significantly smaller than previously claimed, leaving room for a large population of well formed cool-cores at z~1.
In this work we propose a new diagnostic to segregate cool core (CC) clusters from non-cool core (NCC) clusters by studying the two-dimensional power spectra of the X-ray images observed with the Chandra X-ray observatory. Our sample contains 41 members ($z=0.01sim 0.54$), which are selected from the Chandra archive when a high photon count, an adequate angular resolution, a relatively complete detector coverage, and coincident CC-NCC classifications derived with three traditional diagnostics are simultaneously guaranteed. We find that in the log-log space the derived image power spectra can be well represented by a constant model component at large wavenumbers, while at small wavenumbers a power excess beyond the constant component appears in all clusters, with a clear tendency that the excess is stronger in CC clusters. By introducing a new CC diagnostic parameter, i.e., the power excess index (PEI), we classify the clusters in our sample and compare the results with those obtained with three traditional CC diagnostics. We find that the results agree with each other very well. By calculating the PEI values of the simulated clusters, we find that the new diagnostic works well at redshifts up to 0.5 for intermediately sized and massive clusters with a typical Chandra or XMM pointing observation. The new CC diagnostic has several advantages over its counterparts, e.g., it is free of the effects of the commonly seen centroid shift of the X-ray halo caused by merger event, and the corresponding calculation is straightforward, almost irrelevant to the complicated spectral analysis.
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