Self-calibration

Using an imaging step to make a self-calibration model is quite a common scenario in radio astronomy. WSClean can be used to perform this imaging step. Imaging is often used in self-calibration when it is not sufficient to just transfer the solutions from a calibration observation, for example because the ionosphere needs to be calibrated for in the direction of the target observation. There are three main approaches, supporting a range of scenarios:

  • Perform self-calibration from model visibilities. When performing a normal imaging run with WSClean, with an -mgain value less than 1 (which will enable major iterations in the imaging run), WSClean will fill the MODEL_DATA column. This column can then be used during calibration (e.g. with DP3). The advantage of this is that it is relatively fast and easy.

    Tools like DP3 can be instructed to calibrate from the MODEL_DATA column. When using Casa’s tasks for calibration, the calibration tasks will also use the MODEL_DATA and calibrate the CORRECTED_DATA using this column.

    Filling the MODEL_DATA requires a setting of mgain < 1. A typical value of mgain is 0.8. As long as mgain is not 1, WSClean will end with a major iteration, and the MODEL_DATA column will be calculated for the final model that was constructed during the deconvolution.

    This approach does not allow direction-dependent calibration. For that, use one of the following methods.

  • Let WSClean output a source component list (see Component lists) and use this list during the calibration. Tools like DP3 support this format directly. The advantages of this approach are i) that it is easier to apply the beam (and other effects) on a source list; ii) it is very accurate; iii) it is possible to prune/edit the source list. A disadvantage can be that if the number of sources is very large, the direct prediction of the component list (inside calibration) will be very slow.

    Direction-dependent calibration can be performed by clustering the components, and using a direction-dependent calibration tool such as DP3. This is the approach used by the Rapthor pipeline.

    When performing an imaging run with the purpose of creating a component list, some performance can be gained by using the -skip-final-iteration option. This option skips the prediction-imaging round after finishing the deconvolution. The final images may have slightly lower quality, but the model (images/list) is complete.

  • Perform self-calibration from an already existing model image. The -predict option can be used to fill the MODEL_DATA column with a prediction from a pre-existing image (see prediction). After having predicted model visibilities, these visibilities can be used to calibrate the data. Direction-dependent calibration can be performed by predicting into different columns (using the -model-column option).

Polarized imaging & calibration

It is possible to self-calibrate on Stokes I or on multiple polarizations. If you run WSClean on the desired polarizations one by one, e.g. on XX and then on YY, or jointly clean them, the MODEL_DATA column will have all imaged polarizations correctly filled in. Assuming the column does not exist yet, the first run will create the MODEL_DATA column, set all values to zero and then fill the XX column. The second run will notice the MODEL_DATA already exists, and only update the YY column. B. McKinley has used this method and did a few self-cal loops to create very deep and well-calibrated Fornax A images. All polarizations can be selected by using the options -pol xx,xy,yx,yy, -pol iquv, or -pol rr,rl,lr,ll. For info on polarimetric deconvolution settings, see polarimetry deconvolution.

CASA on-the-fly mode

Certain CASA commands (e.g. ft) will put keywords in a measurement set that turn on the “on-the-fly” (otf) mode. In OTF mode, CASA will ignore the MODEL_DATA column and use other keywords to determine the model data. To make use of the MODEL_DATA afterwards, you can use the delmod CASA command to disable OTF mode:

` delmod(vis='myobs.ms',otf=True,scr=False) `

WSClean will never use or change OTF keywords in the measurement set.

Next chapter: Image weighting