Task: mfflat Purpose: Flatten the spectral variation of a visibility data-set. Categories: calibration MFFLAT is a MIRIAD task which flattens the spectral variation of a visibility data-set. This is used in multi-frequency synthesis, where it is desirable to eliminate the dominant spectral variation from the data (i.e. flatten the spectral variation), and so reduce the spectral artifacts in the mapping and deconvolution process. MFFLAT works by modifying the calibration tables of the input data-sets. Key: vis Names of the input visibility data-sets. Several can be given. Wildcard expansion is supported. On output, the calibration tables of the data-set have been modified in such a way as to eliminate the dominant spectral variation. Key: model The input model. This must be MFS image, consisting of an intensity and a scaled-derivative plane. This is analysed to determine the dominant spectral index.

Generated by miriad@atnf.csiro.au on 02 Jun 2021