A Bayesian technique for the detection of point sources in CMB maps
  The detection and flux estimation of point sources in cosmic microwave
background (CMB) maps is a very important task in order to clean the maps and
also to obtain relevant astrophysical information. In this paper we propose a
maximum a posteriori (MAP) approach detection method in a Bayesian scheme which
incorporates prior information about the source flux distribution, the
locations and the number of sources. We apply this method to CMB simulations
with the characteristics of the Planck satellite channels at 30, 44, 70 and 100
GHz. With a similar level of spurious sources, our method yields more complete
catalogues than the matched filter with a 5 sigma threshold. Besides, the new
technique allows us to fix the number of detected sources in a non-arbitrary
way.
