Several criteria may be used to stop the iterative search of this
“matching pursuit”:
- When the maximum of the absolute value of the residual map is lower
than a fraction of the noise. This stopping criterion is adapted to
noise limited situations, i.e. when empirical measures of the
noise in the cleaned image give a value similar to the noise value
estimated from the system temperatures.
- When the maximum of the absolute value of the residual map is lower
than a fraction of the maximum intensity of the original dirty map. This
stopping criterion is adapted to dynamic range limited situations, i.e.
when some part of the source is so intense that the associated side lobes
are larger than the thermal noise. In this case, any empirical measure of
the noise in the cleaned image will give a value larger than the noise
value estimated from the system temperatures.
- The total number of clean components. This is a sanity criterium in
case the other ones would be badly tuned.
- When the total flux remains stable.
Choosing the good stopping criterion is important because the
deconvolution must go deep enough to recover weak extended flux but
CLEAN algorithms start to diverge when the noise is cleaned too
deep. Criterium 4 is thus in general preferable, but may lead to
insufficient cleaning when the dirty beam is poor (by lack of uv
coverage and/or because of phase noise). If (# 4) fails, a good
compromise is to clean down to or slightly below (typically
\(0.8\sigma\)
) the noise level.
