Application of a Bayesian Method to Absorption Spectral-Line Finding in
  Simulated ASKAP Data
  The large spectral bandwidth and wide field of view of the Australian SKA
Pathfinder radio telescope will open up a completely new parameter space for
large extragalactic HI surveys. Here we focus on identifying and parametrising
HI absorption lines which occur in the line of sight towards strong radio
continuum sources. We have developed a method for simultaneously finding and
fitting HI absorption lines in radio data by using multi-nested sampling, a
Bayesian Monte Carlo algorithm. The method is tested on a simulated ASKAP data
cube, and is shown to be reliable at detecting absorption lines in low
signal-to-noise data without the need to smooth or alter the data. Estimation
of the local Bayesian evidence statistic provides a quantitative criterion for
assigning significance to a detection and selecting between competing
analytical line-profile models.
