Clusters morphology by Zernike polynomials

The study of the morphology of multiwavelength images of galaxy clusters is largely used to infer their dynamical state. We presented a novel approach of morphological analysis based on modelling clusters images with Zernike polynomials (ZPs). We used mock maps of the thermal component of the Sunyaev-Zel'dovich (tSZ) effect generated for synthetic clusters in THE THREE HUNDRED project, in the redshift range 0 ≤ z ≤ 1.03. Each tSZ map was modelled with several ZPs, in order to recover morphological features that could be related to different dynamical states. We concluded that morphological differences can be quantified by defining an indicator that includes the contribution of the different ZPs to the fit of the tSZ maps. The feasibility of this new method is prone to the angular resolution of the maps. Our results were also correlated with common morphological parameters and dynamical state indicators applied on the same clusters sample.