An Efficient and Optimal Filter for Identifying Point Sources in
  Millimeter/Sub-Millimeter Wavelength Sky Maps
  A new technique for reliably identifying point sources in
millimeter/sub-millimeter wavelength maps is presented. This method accounts
for the frequency dependence of noise in the Fourier domain as well as
non-uniformities in the coverage of a field. This optimal filter is an
improvement over commonly-used matched filters that ignore coverage gradients.
Treating noise variations in the Fourier domain as well as map space is
traditionally viewed as a computationally intensive problem. We show that the
penalty incurred in terms of computing time is quite small due to casting many
of the calculations in terms of FFTs and exploiting the absence of sharp
features in the noise spectra of observations. Practical aspects of
implementing the optimal filter are presented in the context of data from the
AzTEC bolometer camera. The advantages of using the new filter over the
standard matched filter are also addressed in terms of a typical AzTEC map.
