BOURDIN , H.

We introduce a new multiscale restoration algorithm for images with few photons counts and its use for denoising XMM data. We use a thresholding of the wavelet space so as to remove the noise contribution at each scale while preserving the multiscale information of the signal. Contrary to other algorithms the signal restoration process is the...

International audience

We report results obtained from analysis of the XMM-Newton observation of the compact group of galaxies HCG 16. It is a peculiar system composed of 7 spirals, 6 of which are active, and its nature as a bound system has been much debated. The EPIC camera observations give new insights into the X-ray parameters describing the physical status of...

Advances in Space Research, 36, pp. 650-655, http://dx.doi.org./10.1016/j.asr..01.104

We present a combined X-ray and optical analysis of three bimodal galaxy clusters selected as merging candidates at z similar to 0.1. These targets are part of MUSIC (MUlti-Wavelength Sample of Interacting Clusters), which is a general project designed to study the physics of merging clusters by means of multi-wavelength observations....

International audience

International audience

Context: A 2163 is among the richest and most distant Abell clusters, presenting outstanding properties in different wavelength domains. X-ray observations have revealed a distorted gas morphology and strong features have been detected in the temperature map, suggesting that merging processes are important in this cluster. However, the merging...

We report the discovery of large-scale diffuse radio emission south-east of the galaxy cluster MACS J0520.7-1328, detected through high-sensitivity Giant Metrewave Radio Telescope 323 MHz observations. This emission is dominated by an elongated diffuse radio source and surrounded by other features of lower surface brightness. Patches of these...

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Temperature profiles of the hot galaxy cluster intracluster medium (ICM) have a complex non-linear structure that traditional parametric modelling may fail to fully approximate. For this study, we made use of neural networks, for the first time, to construct a data-driven non-parametric model of ICM temperature profiles. A new deconvolution...