Computation

• As with CLEAN, you give VTESS a dirty image (inname etc.) and a dirty beam (in2name etc.). You also have the option to give it a default image (in3name etc.) which is an initial model of the source that the algorithm begins with. This might be the result from a previous run of VTESS\ so that you can deconvolve some more, or it might be, say, a low-resolution image of the source.
• VTESS produces two output images. One is the MEM image (outname etc.), which has units of Jy per pixel. This image has a resolution that is signal-to-noise ratio dependent. You can also produce a convolved image (out2name etc.) by specifying convolving Gaussian through bmaj, bmin, and bpa. If the beam is left at zero, VTESS will try to fit the dirty beam's main lobe and use the resulting elliptical Gaussian for the convolution. This is the same procedure as CLEAN uses for its final convolved image.
• VTESS can actually do a very sophisticated mosaicing deconvolution as well as a simple single image deconvolution. This is what nmaps is for. Leave this at one for the moment, as I am not going to discuss mosaicing.
• niter specifies the number of iterations to perform. Start off with 10 or so.
• A crucial parameter is noise. This determines how well the algorithm will try to fit the model to the data. It should be comparable to the r.m.s. value of a blank region of a CLEAN image. If noise is too large, the output image will be too smooth. If it's too small, convergence will be prevented. A useful trick is to underestimate noise and then stop after a few iterations, and reset noise to the level achieved up to that point. Do not leave noise at zero.
• flux specifies how the zero-spacing flux is to be estimated. There are three modes of use. First, you specify a known value which must be fitted to within 5%. Second, if you have no idea what the zero-spacing flux is then leave flux at zero. VTESS will attempt to estimate it. Third, if you have a rough idea (within a factor of 2 say) then set flux to the negative of your guess. For example, flux=-2. VTESS will then do a reasonable job of estimating the true value.

inname,inclass Dirty image inseq,indisk

in2name,in2class Dirty beam in2seq,in2disk

in3name,in3class Default image, leave

in3seq,in3disk blank if nothing better

outname,outclass MEM image. Units

outseq,outdisk are Jy/pixel

out2name,out2class Convolved image. Units

out2seq,out2disk are Jy/beam

nmaps=1 No mosaicing

niter=10 Number of iterations

noise Specify noise level carefully

flux=5 Specify zero spacing to 5% or

flux=0 let program work it out or

flux=-5 Specify minus zeros apcing to 50%

bmaj=0 Convolving beam If 0,

bmin=0 program fits main lobe of

bpa=0 dirty beam to work it out.