SIMBAD references

2013A&A...549A..19W - Astronomy and Astrophysics, volume 549A, 19-19 (2013/1-1)

Studying the properties of galaxy cluster morphology estimators.

WEISSMANN A., BOEHRINGER H., SUHADA R. and AMEGLIO S.

Abstract (from CDS):

X-ray observations of galaxy clusters reveal a large range of morphologies with various degrees of disturbance, showing that the assumptions of hydrostatic equilibrium and spherical shape, which are used to determine the cluster mass from X-ray data are not always satisfied. It is therefore important for the understanding of cluster properties as well as for cosmological applications to detect and quantify substructure in X-ray images of galaxy clusters. Two promising methods to do so are power ratios and center shifts. Since these estimators can be heavily affected by Poisson noise and X-ray background, we performed an extensive analysis of their statistical properties using a large sample of simulated X-ray observations of clusters from hydrodynamical simulations. We quantify the measurement bias and error in detail and give ranges where morphological analysis is feasible. A new, computationally fast method to correct for the Poisson bias and the X-ray background contribution in power ratio and center shift measurements is presented and tested for typical XMM-Newton observational data sets. We studied the morphology of 121 simulated cluster images and established structure boundaries to divide samples into relaxed, mildly disturbed and disturbed clusters. In addition, we present a new morphology estimator - the peak of the 0.3-1 r500P3/P0 profile to better identify merging clusters. The analysis methods were applied to a sample of 80 galaxy clusters observed with XMM-Newton. We give structure parameters (P3/P0in r500, w and P3/P0max) for all 80 observed clusters. Using our definition of the P3/P0(w) substructure boundary, we find 41% (47%) of our observed clusters to be disturbed.

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Journal keyword(s): X-rays: galaxies: clusters - galaxies: clusters: intracluster medium

Simbad objects: 81

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