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arxiv: 1202.0396 · v1 · pith:V3CG66BLnew · submitted 2012-02-02 · 🌌 astro-ph.IM · astro-ph.CO

Applying the Background-Source separation algorithm to Chandra Deep Field South data

classification 🌌 astro-ph.IM astro-ph.CO
keywords dataalgorithmchandradeepfieldsourcessouthanalysis
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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 modeled 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.

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