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A few (obvious) practical recommendations

Map size
Make an image about twice the size of the primary beam (e.g. $2\times55''$ at 90 GHz and $2\times22''$ at 230 GHz for NOEMA antenna) to ensure that all the area of the primary beam (inner quarter of the dirty map) will be cleaned whatever the deconvolution algorithm is used. However, avoid making a too large dirty image because the CLEAN algorithms will then try to deconvolve region outside the primary beam area where the noise dominates.
Support
Start your first deconvolution without any support to avoid biasing your clean image. If the source is spatially bound, you can define a support around the source and restart the deconvolution with this a priori information. Be careful to check that there is no low signal-to-noise extended structure that could contain a large fraction of the source flux outside your support... Avoid defining a support too close to the natural edges of your source. Indeed, deconvolving noisy regions around your source is advisable because it ensures that you do not bias your deconvolution too much.
Stopping criterion
Choose the right stopping criterion.
Use the stability blueCLEAN_NKEEP parameter preferentially, combined with a blueCLEAN_STOP = r SIGMA with r between 1 or 2. That keeps blueCLEAN_ARES, blueCLEAN_FRES and blueCLEAN_NITER to zero. If it does not work, then
  • Estimate an empirical noise on your first deconvolved cleaned image with magentaSTATISTIC, magentaCLEAN, or magentaSHOW NOISE.
  • If this empirical noise value is similar to the value computed from the visibility weights (this noise value is one of the outputs of the magentaUV_MAP command), your observation is not dynamic range limited. Apart from using a user-specified support (magentaSUPPORT or magentaMASK) there is not much you can do to improve your result,
  • If not, you are dynamic range limited. You may use blueCLEAN_STOP = r % where r depends on the dynamic range as stopping criterium. Alternatively, you can select the effective noise level as the true Sigma, blueCLEAN_STOP = r 'clean%rms' with r being 1 to 2. The problem in such cases is that the noise level may be channel dependent, an issue that is not well handled.
Convergence checks
Ensure that your deconvolution converged by checking that:
  • The cumulative flux as a function of the number of clean component has reached a roughly constant level (use magenta/FLUX option of the deconvolution commands to see this curves, or magentaSHOW CCT or magentaVIEW CCT).
  • The residuals are similar or smaller in the source region (where Clean components were found) compared to elsewhere.
If not, change the values of the stopping criterion, whichever you used.
Deconvolution methods
If you want a robust result in all cases, start with magentaHOGBOM. If you prefer obtaining a quick result, use magentaCLARK but you then first need to check that the dirty sidelobes are not too large on the dirty beam. If you obtain stripes in your Clean image:
  • First check that your deconvolution converged.
  • Then check that there is no spurious visibilities that should be flagged : use command magentaUV_FLAG as a last resort.
  • If it is clear that you have an extended source structure, you should first ask yourself whether you are in the wide-field imaging case and act accordingly (see next chapter). Else you can try a magentaCLEAN variant which better deals with cases that implies a large spatial dynamic. This is rare at NOEMA, but may happen with ALMA.
Outside help
Always consult an expert until you become one.


next up previous contents index
Next: Wide-field imaging and deconvolution Up: Practical advices Previous: Comparison of deconvolution algorithms   Contents   Index
Gildas manager 2023-06-01