Morphology parameters: Substructure identification in X-ray galaxy clusters

Viral Parekh, Kurt Van Der Heyden, Chiara Ferrari, Garry Angus, Benne Holwerda

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

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, M20, concentration, asymmetry, smoothness, ellipticity, and Gini of the second-order moment, GM) 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, M20, 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 M20 (<-2.0) values are associated with relaxed clusters, while low Gini (<0.4), low concentration (<1.0), and high M20 (>-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.

Original languageEnglish
Article numberA127
JournalAstronomy and Astrophysics
Volume575
DOIs
Publication statusPublished - Mar 1 2015

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substructures
galaxies
x rays
merger
radio
asymmetry
parameter
wavelength
ellipticity
gas
proportion
astrophysics
moments
coefficients
method
estimates
gases
wavelengths

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

Parekh, Viral ; Van Der Heyden, Kurt ; Ferrari, Chiara ; Angus, Garry ; Holwerda, Benne. / Morphology parameters : Substructure identification in X-ray galaxy clusters. In: Astronomy and Astrophysics. 2015 ; Vol. 575.
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Morphology parameters : Substructure identification in X-ray galaxy clusters. / Parekh, Viral; Van Der Heyden, Kurt; Ferrari, Chiara; Angus, Garry; Holwerda, Benne.

In: Astronomy and Astrophysics, Vol. 575, A127, 01.03.2015.

Research output: Contribution to journalArticle

TY - JOUR

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T2 - Substructure identification in X-ray galaxy clusters

AU - Parekh, Viral

AU - Van Der Heyden, Kurt

AU - Ferrari, Chiara

AU - Angus, Garry

AU - Holwerda, Benne

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AB - 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, M20, concentration, asymmetry, smoothness, ellipticity, and Gini of the second-order moment, GM) 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, M20, 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 M20 (<-2.0) values are associated with relaxed clusters, while low Gini (<0.4), low concentration (<1.0), and high M20 (>-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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