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

    Fingerprint

    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

    T1 - Morphology parameters

    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

    PY - 2015/3/1

    Y1 - 2015/3/1

    N2 - 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.

    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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