Morphological analysis of SZ and X-ray maps of galaxy clusters with Zernike polynomials

TL;DR

This paper introduces a novel morphological analysis method for galaxy clusters using Zernike polynomials, validated on simulations and applied to observational data, providing a new parameter correlated with cluster dynamical states.

Contribution

The paper presents a new analytical approach using Zernike polynomials for galaxy cluster morphology classification, validated on simulations and applied to real observational data.

Findings

The Zernike-based parameter correlates with traditional morphological indicators.

The method successfully classifies simulated cluster morphologies.

Preliminary results show applicability to real X-ray and Compton maps.

Abstract

Several methods are used to evaluate, from observational data, the dynamical state of galaxy clusters. Among them, the morphological analysis of cluster images is well suited for this purpose. We report a new approach to the morphology, which consists in analytically modelling the images with a set of orthogonal functions, the Zernike polynomials (ZPs). We validated the method on mock high-resolution Compton parameter maps of synthetic galaxy clusters from THE THREE HUNDRED project. To classify the maps for their morphology we defined a single parameter, $\mathcal{C}$, by combining the contribution of some ZPs in the modelling. We verify that $\mathcal{C}$ is linearly correlated with a combination of common morphological parameters and also with a proper 3D dynamical-state indicator available for the synthetic clusters we used. We also show the early results of the Zernike modelling applied on Compton parameter maps of local clusters ($z < 0.1$) observed by the $\textit{Planck}$ satellite. At last, we report the preliminary results of this kind of morphological analysis on mock X-ray maps of THE THREE HUNDRED clusters.