Spectral imaging of galaxy clusters with Planck
H. Bourdin, P. Mazzotta, and E. Rasia

TL;DR
This paper presents a spectral imaging algorithm for analyzing Planck SZ data to detect gas density anisotropies, filaments, and shock fronts in galaxy clusters, enhancing understanding of cluster outskirts.
Contribution
The paper introduces a novel multiscale spectral imaging algorithm tailored for Planck SZ observations, improving detection of anisotropies and shock features in galaxy clusters.
Findings
Algorithm successfully detects filaments in cluster peripheries.
Effective identification of large-scale shocks in colliding clusters.
Planck data can reveal detailed gas structures in galaxy clusters.
Abstract
The Sunyaev-Zeldovich (SZ) effect is a promising tool for detecting the presence of hot gas out to the galaxy cluster peripheries. We developed a spectral imaging algorithm dedicated to the SZ observations of nearby galaxy clusters with Planck, with the aim of revealing gas density anisotropies related to the filamentary accretion of materials, or pressure discontinuities induced by the propagation of shock fronts. To optimize an unavoidable trade-off between angular resolution and precision of the SZ flux measurements, the algorithm performs a multiscale analysis of the SZ maps as well as of other extended components, such as the cosmic microwave background (CMB) anisotropies and the Galactic thermal dust. The demixing of the SZ signal is tackled through kernel weighted likelihood maximizations. The CMB anisotropies are further analyzed through a wavelet analysis, while the Galactic…
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