A New Approach to Multi-wavelength Associations of Astronomical Sources
  One of the biggest problems faced by current and next-generation astronomical
surveys is trying to produce large numbers of accurate cross identifications
across a range of wavelength regimes with varying data quality and positional
uncertainty. Until recently simple spatial "nearest neighbour" associations
have been sufficient for most applications. However as advances in
instrumentation allow more sensitive images to be made the rapid increase in
the source density has meant that source confusion across multiple wavelengths
is a serious problem. The field of far-IR and sub-mm astronomy has been
particularly hampered by such problems. The poor angular resolution of current
sub-mm and far-IR instruments is such that in a lot of cases there are multiple
plausible counterparts for each source at other wavelengths. Here we present a
new automated method of producing associations between sources at different
wavelengths using a combination of spatial and SED information set in the
Bayesian framework presented by Budavari & Szalay (2008). Testing of the
technique is performed on both simulated catalogues of sources from GaLICS and
real data from multi-wavelength observations of the SXDF. It is found that a
single figure of merit, the Bayes factor, can be effectively used to describe
the confidence in the match. Further applications of this technique to future
Herschel datasets are discussed.
