Source Classification in Deep Multi-Wavelengths Surveys

Details Source Classification in Deep Multi-Wavelengths Surveys Source Classification in Deep Multi-Wavelengths Surveys

Jan 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21321103p&link_type=abstract

American Astronomical Society, AAS Meeting #213, #211.03; Bulletin of the American Astronomical Society, Vol. 41, p.283

Astronomy and Astrophysics

Astronomy

Scientific paper

We will discuss a Bayesian probabilistic model approach to selecting sources from deep surveys, based on our analysis of X-ray-selected normal/starburst galaxies in the Chandra Deep Fields (which overlap the GOODS regions). This approach explicitly takes into account uncertainties in the parameters used for the classification. This is particularly relevant when X-ray data is employed since the most interesting sources tend to be close to the flux limit of the survey, and hence have low numbers of photons detected. We will also discuss the inclusion of the likelihoods for flux and redshift (particularly photometric redshifts which are tied to classification via some form of template fitting) when computing "derived" quantities such as luminosity functions and luminosity density.

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