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Visibility Processing

The flagging, splitting and calibration of a mosaic experiment are rather similar to a conventional experiment. The following concentrates on the differences only. This section will assume that, as is usual, only a single phase calibrator is used for all pointings.

• Flagging: Flagging differs only in that, when the instrument is continually changing to a new pointing centre, it can be more difficult to spot the outliers which indicate bad data.

  In its processing, tvflag usually produces a gap in its display every time the source being observed is changed. When mosaicing, this can very quickly mount up to taking the entire display (and tvflag will complain about not being able to determine an appropriate averaging interval). In this case, options=nosrc can be used to suppress the gap and allow tvflag to average across source changes.

• Splitting: As with conventional reduction, for calibration and imaging purposes, it is easiest in Miriad to split the data into datasets containing a `single source' and single frequency band. For a mosaic experiment, all the pointings from the object of interest should be considered a `single source'. As the ATCA on-line system labels each pointing with a different field name, uvsplit would normally break the dataset into one file per pointing. To avoid this, use uvsplit's mosaic option. This causes uvsplit to use the source name up to any underscore character. Thus, assuming you have used the field naming convention of Section 21.3, uvsplit will not split apart all the separate pointings.

  If you failed to follow the naming convention, the select keyword of uvaver and uvsplit can be used to split the dataset up. This is left as an exercise for the reader.

  For example, assuming a dataset containing calibrators and an observation of the LMC (with appropriately named fields), the following inputs will generate datasets for the calibrators and a single dataset for all the LMC data.

  UVSPLIT
  vis=mosaic.uv	The input dataset.
  options=mosaic	Assume mosaic experiment, so create
  	multi-pointing output where necessary.

• Data Selection: With mosaic visibility datasets, the select=ra and select=dec selection sub-commands can be useful to extract or manipulate a subset of the visibility data.
• Calibration: Determining the calibration solutions does not differ from that described in Chapter 12. You will then use gpcopy to copy the calibration tables to the multi-pointing dataset.