Recent numerical simulations have shown that the variations of the gas temperature in clusters of galaxies are indicative of the dynamical state of these clusters. Maps of the temperature variation show complex structures with different shapes at different spatial scales, such as hot compression regions, filaments, cooling flows, or large-scale temperature profiles. A new multiscale spectro-imagery algorithm for restoring the spatial temperature variations within clusters of galaxies is presented here. It has been especially developed to work with the EPIC MOS1, MOS2 and PN spectro-imagers on board the XMM-Newton satellite. The temperature values are fitted to an emission model that includes the source, the cosmic X-ray background and cosmic-ray induced particle background. The spatial temperature variations are coded at different scales in the wavelet space using the Haar wavelet and denoised by thresholding the wavelet coefficients. Our local temperature estimator behaves asymptotically like an optimal mininum variance bound estimator. But it is highly sensitive to the instrumental and astrophysical backgrounds, so that a good knowledge of each component of the emission model is required. Our algorithm has been applied to a simulated 60 ks observation of a merging cluster at z = 0.1. The cluster at different stages of merging has been provided by 3-D hydrodynamical simulations of structure formation (AMR). The multiscale approach has enabled us to restore the faint structures within the core of the merging subgroups where the gas emissivity is high, but also the temperature decrease at large scale in their external regions.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science
- Galaxies: clusters: general
- Galaxies: interactions