Applications for edge detection techniques using Chandra and XMM-Newton data: galaxy clusters and beyond
S. A. Walker, J. S. Sanders, A. C. Fabian

TL;DR
This paper demonstrates the effectiveness of Gaussian Gradient Magnitude filtering in enhancing X-ray surface brightness features in galaxy clusters and other astrophysical objects, revealing new structures and dynamics.
Contribution
It introduces and applies GGM filtering to Chandra and XMM-Newton data, uncovering previously unseen features and substructures in various astrophysical sources.
Findings
Revealed substructure behind cold fronts in galaxy clusters.
Identified a new edge in the Perseus cluster possibly indicating a bow shock.
Detected a moving feature in the Crab nebula's torus at ~0.1c speed.
Abstract
The unrivalled spatial resolution of the Chandra X-ray observatory has allowed many breakthroughs to be made in high energy astrophysics. Here we explore applications of Gaussian Gradient Magnitude (GGM) filtering to X-ray data, which dramatically improves the clarity of surface brightness edges in X-ray observations, and maps gradients in X-ray surface brightness over a range of spatial scales. In galaxy clusters, we find that this method is able to reveal remarkable substructure behind the cold fronts in Abell 2142 and Abell 496, possibly the result of Kelvin Helmholtz instabilities. In Abell 2319 and Abell 3667, we demonstrate that the GGM filter can provide a straightforward way of mapping variations in the widths and jump ratios along the lengths of cold fronts. We present results from our ongoing programme of analysing the Chandra and XMM-Newton archives with the GGM filter. In…
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