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Basic Information on mosmem
Purpose: Maximum Entropy deconvolution for a mosaiced image
MOSMEM is a MIRIAD task that performs a maximum entropy
deconvolution of a mosaiced image. Optionally it can also
perform a joint deconvolution of a mosaic and single dish image.
MOSMEM will also work correctly on a single-pointing observation
interferometric observation. In this case, it will be less
efficient than MAXEN, but it could be used when combining single
dish data with a single pointing.
MOSMEM spits out some information as it goes:
RMSFAC is the ratio (actual rms)/(theoretical rms). It measures
the residuals (i.e. the difference between the dirty image and
the model modified by the point spread function). RMSFAC should
converge to 1.
NormGrd is normalised gradient in the maximisation process.
Convergence requires this to be less than 0.05
Flux is the sum of all the pixel values in the model.
One or perhaps two input dirty images (or cubes). These should
have units of Jy/beam. The first should be produced by INVERTs
mosaic mode. The optional second dirty map can be a single-dish
image. It must be on exactly the same pixel grid as the first
image. If necessary, use REGRID to make this so. If two inputs
are given, then a joint deconvolution of the two is performed.
One or perhaps two input dirty beams. The first, corresponding
to the first input dirty map, will be produced by INVERTs mosaic
mode. There is no default. The second dirty beam (which must
be given if there are two dirty map inputs) gives the point-
spread function of the single dish dirty map. This second dirty
beam need not be the same image size as the input dirty maps,
and may be appreciably smaller. This single-dish beam is
assumed to be position-independent, but it need not be
An initial estimate of the deconvolved image. For point
sources, giving a good initial model may help convergence. In
principle, this only helps convergence, but should not affect
the final solution. The model could be the output from a
previous run of MOSMEM or any other deconvolution task. It must
have flux units of Jy/pixel. The default is a flat estimate,
with the correct flux.
The default image. This is the image that the final solution
will tend towards. The final result will be influenced by this
default if the constrains that the data put on the solution are
weak. The default is a flat estimate, with the correct flux.
The name of the output map. The units of the output will be
Jy/pixel. It can be input to RESTOR to produce a restored
image, or alternatively to MOSMEM, as a model, to continue the
The maximum number of iterations. The default is 30.
This specifies the region to be deconvolved. See the User's
Manual for instructions on how to specify this. The default is
the entire image.
The entropy measure to be used, either "gull" (-p*log(p/e)) or
"cornwell" (-log(cosh(p)) -- also called the maximum emptiness
criteria). Using the maximum emptiness criteria is not
Tolerance of solution. There is no need to change this from the
default of 0.01.
One or two values (corresponding to the mosaic and single dish
observations). These give estimates of the number of points per
beam. MOSMEM can usually come up with a good, image-dependent
MOSMEM must be able to the theoretical rms noise of the input
dirty map(s), and will, by default, attempt to reduce the
residuals to have the same rms as this. If the true rms noise
is different from the theoretical, you may give the factor to
multiply by to convert from theoretical to true rms noise.
The theoretical rms will usually be an optimistic estimate of
the true noise level. The true noise will be increased by
calibration errors, confusion, poorly understood distant
sidelobes, etc. The rmsfac factor gives some "fudge factor"
(usually greater than 1) to scale the theoretical noise estimate
by. Either one or two values can be given, with the second
value corresponding to the single dish input.
For a mosaic, the theoretical rms is position dependent, and is
determined from information save by INVERT (the mostable table).
For a single dish image, the rms is assumed to be constant
across the field, and given by the "rms" item in the image. If
the single dish input does not contain this item, then this must
be added before using MOSMEM. This is easily done: for image
puthd in=xxxx/rms value=????
where "????" is the rms noise in Jy/beam.
The flux calibration factor. This is only relevant when doing a
joint deconvolution of a mosaic and a single-dish image. It
gives the factor which the single-dish data should be multiplied
by to convert it to the same flux units as the mosaic. The
default is 1. If the "dofactor" options is used (see below),
MOSMEM solves for this parameter.
An estimate of the integrated flux of the source. This
parameter is generally not useful if there is an input single
dish image. Giving MOSMEM a good value for the integrated flux
will help it find a good solution. On the other hand, giving a
poor value may do harm. Normally MOSMEM will NOT constrain the
integrated flux to be this value, but see the "doflux" option
below. The default is image-dependent for measure=gull, and
zero for measure=cornwell. A value can be given for each plane
Task enrichment parameters. Several can be given, separated by
commas. Minimum match is used. Possible values are:
doflux Constrain the solution to have the correct
integrated flux (normally the integrated flux is
not constrained). The integrated flux is
determined from the "flux" parameter or (if no flux
parameter is given) from the default image. This
option cannot be used if a single dish input map is
dofactor Solve for the flux calibration factor.
verbose Give lots of messages during the iterations. The
default is to give a one line message at each
Revision: 1.8, 2016/07/14 02:15:13 UTC
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