Applying the Background-Source Separation Algorithm to Chandra Deep Field South Data

A probabilistic two-component mixture model allows one to separate the diffuse background from the celestial sources within a one-step algorithm without data censoring. The background is modelled with a thin-plate spline combined with the satellite’s exposure time. Source probability maps are created in a multi-resolution analysis for revealing faint and extended sources. All detected sources are automatically parametrized to produce a list of source positions, fluxes and morphological parameters. The present analysis is applied to the Chandra Deep Field South 2 Ms public released data. Within its 1.884 ks of exposure time and its angular resolution (0.984 arcsec), the Chandra Deep Field South data are particularly suited for testing the Background-Source separation algorithm.