Inference of the morphology and dynamical state of nearby <i>Planck</i>-SZ galaxy clusters with Zernike polynomials

Aims. We analyse maps of the Sunyaev–Zel’dovich (SZ) signal of local galaxy clusters ( z &lt;0.1) observed by the Planck satellite to classify their dynamical state via morphological features. Methods. We applied a novel method, which was recently employed on mock SZ images generated from hydrodynamical simulated galaxy clusters in T HE T HREE H UNDRED (T HE 300) project to study the morphology of the cluster maps. In this paper, we report our results following its first application on real data. The method consists of modelling the images with a set of orthogonal functions defined on circular apertures, namely, the Zernike polynomials. From the fit we computed a single parameter, 𝒞, that quantifies the morphological features present in each image. The link between the morphology of 2D images and the dynamical state of the galaxy clusters is well known, even if it is not obvious. We used mock Planck -like Compton parameter maps generated for T HE 300 clusters to validate our morphological analysis. These clusters are, in fact, properly classified for their dynamical state with the relaxation parameter, χ , by exploiting 3D information from the simulations. Results. We find a mild linear correlation of ∼38% between 𝒞 and χ for T HE 300 clusters, mainly affected by the noise present in the maps. To obtain a proper dynamical-state classification for the Planck clusters, we exploited the conversion from the 𝒞 parameter derived in each Planck map in χ . A fraction of the order of 63% of relaxed clusters has been estimated in the selected Planck sample. Our classification was then compared with those of previous works that have attempted to evaluate, with different indicators and/or other wavelengths, the dynamical state of the same Planck objects. We find an agreement with these other works to be greater than 58%.