Cosmology and Astrophysics from Relaxed Galaxy Clusters I: Sample Selection

TL;DR

This paper introduces an automated, morphology-based method for identifying relaxed galaxy clusters using X-ray data, enabling consistent analysis across various data qualities and redshifts, and applies it to a large cluster sample.

Contribution

It presents a new morphological classification method for relaxed clusters, tailored for robustness and comparability, and applies it to extensive X-ray cluster data from Chandra and ROSAT.

Findings

16% of clusters are classified as relaxed using the SPA criterion

The method is robust against data gaps and varying data quality

Relaxed fraction trends with redshift and temperature are discussed

Abstract

This is the first in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here we present a new, automated method for identifying relaxed clusters based on their morphologies in X-ray imaging data. While broadly similar to others in the literature, the morphological quantities that we measure are specifically designed to provide a fair basis for comparison across a range of data quality and cluster redshifts, to be robust against missing data due to point-source masks and gaps between detectors, and to avoid strong assumptions about the cosmological background and cluster masses. Based on three morphological indicators - Symmetry, Peakiness and Alignment - we develop the SPA criterion for relaxation. This analysis was applied to a large sample of cluster observations from the Chandra and ROSAT archives. Of the 361 clusters which received the SPA treatment, 57 (16 per cent) were subsequently found to be relaxed according to our criterion. We compare our measurements to similar estimators in the literature, as well as projected ellipticity and other image measures, and comment on trends in the relaxed cluster fraction with redshift, temperature, and survey selection method. Code implementing our morphological analysis will be made available on the web.