Mixture Modeling for Background and Sources Separation in x-ray Astronomical Images

Details Mixture Modeling for Background and Sources Separation in x-ray Astronomical Images Mixture Modeling for Background and Sources Separation in x-ray Astronomical Images

Nov 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004aipc..735..111g&link_type=abstract

BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 24th International Workshop on Bayesian Inference and

Mathematics

Probability

1

Probability Theory, Inference Methods, Background Radiations, X-Ray Sources, X-Ray Bursts

Scientific paper

A probabilistic technique for the joint estimation of background and sources in high-energy astrophysics is described. Bayesian probability theory is applied to gain insight into the coexistence of background and sources through a probabilistic two-component mixture model, which provides consistent uncertainties of background and sources. The present analysis is applied to ROSAT PSPC data (0.1-2.4 keV) in Survey Mode. A background map is modelled using a Thin-Plate spline. Source probability maps are obtained for each pixel (45 arcsec) independently and for larger correlation lengths, revealing faint and extended sources. We will demonstrate that the described probabilistic method allows for detection improvement of faint extended celestial sources compared to the Standard Analysis Software System (SASS) used for the production of the ROSAT All-Sky Survey (RASS) catalogues.

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