X-ray morphological estimators for galaxy clusters

Rasia, Elena; Meneghetti, M.; Ettori, S.

doi:10.1080/21672857.2013.11519713

Cited by 57 publications

(68 citation statements)

References 88 publications

(158 reference statements)

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“…This was unexpected because these parameters trace the 2D structure and should be sensitive to a range of substructure types. In addition, Rasia et al (2013) found that the smoothness & asymmetry were promising as probes for substructure. Rasia et al (2013), however, tested their parameters on simulated cluster data, and all the simulations had a uniform exposure time.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, Rasia et al (2013) found that the smoothness & asymmetry were promising as probes for substructure. Rasia et al (2013), however, tested their parameters on simulated cluster data, and all the simulations had a uniform exposure time. We found that the value of these two parameters largely depends on cluster exposure time or S/N.…”

Section: Discussionmentioning

confidence: 99%

“…The advantage of using the Gini coefficient is that it is independent of the precise location of a galaxy cluster's centre. The asymmetry parameter is correlated with Gini of the second-order moment and smoothness parameters Zhang et al 2010;Rasia et al 2013). We did not observe any correlation between the other six parameters and ellipticity.…”

Section: Parameter Vs Parameter Planesmentioning

confidence: 99%

“…Weißmann et al (2013) proposed to use the maximum of the third-order power ratios calculated in annuli of fixed width and constantly increasing radius to measure the degree of substructure. Rasia et al (2013) have used six different morphology parametersasymmetry, fluctuation of the X-ray brightness (smoothness), hardness ratios, concentration, the centroid-shift method, and third-order power ratio -to characterise simulated clusters. They took hydrodynamical simulation of 60 clusters and passed it through a Chandra telescope simulator with uniform exposure time (100 ks) for all clusters.…”

Section: Introductionmentioning

confidence: 99%

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Morphology parameters: substructure identification in X-ray galaxy clusters

Parekh

Heyden

Ferrari

et al. 2015

A&A

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Context. In recent years multi-wavelength observations have shown the presence of substructures related to merging events in a large proportion of galaxy clusters. Clusters can be roughly grouped into two categories -relaxed and non-relaxed -and a proper characterisation of the dynamical state of these systems is crucial for both astrophysical and cosmological studies. Aims. In this paper we investigate the use of a number of morphological parameters (Gini, M 20 , concentration, asymmetry, smoothness, ellipticity, and Gini of the second-order moment, G M ) introduced to automatically classify clusters as relaxed or dynamically disturbed systems. Methods. We apply our method to a sample of clusters at different redshifts extracted from the Chandra archive and investigate possible correlations between morphological parameters and other X-ray gas properties. Results. We conclude that a combination of the adopted parameters is a very useful tool for properly characterising the X-ray cluster morphology. According to our results, three parameters -Gini, M 20 , and concentration -are very promising for identifying cluster mergers. The Gini coefficient is a particularly powerful tool, especially at high redshift, because it is independent of the choice of the position of the cluster centre. We find that high Gini (>0.65), high concentration (>1.55), and low M 20 (<-2.0) values are associated with relaxed clusters, while low Gini (<0.4), low concentration (<1.0), and high M 20 (>-1.4) characterise dynamically perturbed systems. We also estimate the X-ray cluster morphological parameters in the case of radio loud clusters. Since they are in excellent agreement with previous analyses we confirm that diffuse intracluster radio sources are associated with major mergers.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Parameter Vs Parameter Planesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Morphology parameters: substructure identification in X-ray galaxy clusters

Parekh

Heyden

Ferrari

et al. 2015

A&A

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“…Böhringer et al 2010;Mahdavi et al 2013;Rasia et al 2013) to determine the degree of substructure quantitatively and compare the results from simulations with and without AGN feedback to X-ray observations. For the X-ray observations we consider the REXCESS clusters.…”

Section: Introductionmentioning

confidence: 99%

The effect of AGN feedback on the X-ray morphologies of clusters: Simulations vs. observations

Chon

Puchwein

Böhringer

2016

A&A

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Clusters of galaxies probe the large-scale distribution of matter and are a useful tool to test the cosmological models by constraining cosmic structure growth and the expansion of the Universe. It is the scaling relations between mass observables and the true mass of a cluster through which we obtain the cosmological constraints by comparing to theoretical cluster mass functions. These scaling relations are, however, heavily influenced by cluster morphology. The presence of the slight tension in recent cosmological constraints on Ω m and σ 8 based on the CMB and clusters has boosted the interests in looking for possible sources for the discrepancy. Therefore we study here the effect of active galactic nucleus (AGN) feedback as one of the major mechanisms modifying the cluster morphology influencing scaling relations. It is known that AGN feedback injects energies up to 10 62 erg into the intracluster medium, controls the heating and cooling of a cluster, and re-distributes cold gas from the centre to outer radii. We have also learned that cluster simulations with AGN feedback can reproduce observed cluster properties, for example, the X-ray luminosity, temperature, and cooling rate at the centre better than without the AGN feedback. In this paper using cosmological hydrodynamical simulations we investigate how the AGN feedback changes the X-ray morphology of the simulated systems, and compare this to the observed Representative XMM-Newton Cluster Structure Survey (REXCESS) clusters. We apply two substructure measures, centre shifts (w) and power ratios (e.g. P 3 /P 0 ), to characterise the cluster morphology, and find that our simulated clusters are more substructured than the observed clusters based on the values of w and P 3 /P 0 . We also show that the degree of this discrepancy is affected by the inclusion of AGN feedback. While the clusters simulated with the AGN feedback are in much better agreement with the REXCESS L X −T relation, they are also more substructured, which increases the tension with observations. When classified as non-relaxed or relaxed according to their w and P 3 /P 0 values, we find that there are no relaxed clusters in the simulations with the AGN feedback. This suggests that not only global cluster properties, like L X and T, and radial profiles should be used to compare and to calibrate simulations with observations, but also substructure measures like centre shifts and power ratios. Finally, we discuss what changes in the simulations might ease the tension with observational constraints on these quantities.

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A web portal for hydrodynamical, cosmological simulations

Ragagnin

Dolag

Biffi

et al. 2017

Astronomy and Computing

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This article describes a data center hosting a web portal for accessing and sharing the output of large, cosmological, hydro-dynamical simulations with a broad scientific community. It also allows users to receive related scientific data products by directly processing the raw simulation data on a remote computing cluster.The data center has a multi-layer structure: a web portal, a job control layer, a computing cluster and a HPC storage system. The outer layer enables users to choose an object from the simulations. Objects can be selected by visually inspecting 2D maps of the simulation data, by performing highly compounded and elaborated queries or graphically by plotting arbitrary combinations of properties. The user can run analysis tools on a chosen object. These services allow users to run analysis tools on the raw simulation data. The job control layer is responsible for handling and performing the analysis jobs, which are executed on a computing cluster. The innermost layer is formed by a HPC storage system which hosts the large, raw simulation data.The following services are available for the users: (I) ClusterInspect visualizes properties of member galaxies of a selected galaxy cluster; (II) SimCut returns the raw data of a sub-volume around a selected object from a simulation, containing all the original, hydro-dynamical quantities; (III) Smac creates idealised 2D maps of various, physical quantities and observables of a selected object; (IV) Phox generates virtual X-ray observations with specifications of various current and upcoming instruments.

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X-ray morphological estimators for galaxy clusters

Cited by 57 publications

References 88 publications

Morphology parameters: substructure identification in X-ray galaxy clusters

Morphology parameters: substructure identification in X-ray galaxy clusters

The effect of AGN feedback on the X-ray morphologies of clusters: Simulations vs. observations

A web portal for hydrodynamical, cosmological simulations

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