Cleaning diffuse/extended sources

[Kingsley]

Hello everyone,
I'm pretty new around here, and also to radio, so please forgive me if this has been covered before.
What is the best approach for cleaning CABB data cubes for diffuse sources? From what I gather CLEAN is more suited for point sources?

Thanks for your help.

[ste616]

Hi Kingsley,

Welcome to the forum and the exciting world of radio astronomy!

Although I won't say that CLEAN is the best or only option, it will work for diffuse sources. CLEAN works on the principle that sources are uncorrelated on the sky (which is a good assumption) and so can be treated as a bunch of point sources. For diffuse sources, if an emission component is strong enough to make the PSF arising from it brighter than the RMS noise level, CLEANing should work pretty well. Of course there are plenty of different CLEAN algorithms, and Miriad does image-based cleaning while CASA does uv-based cleaning.

I would first recommend reading some information about how deconvolution works in Miriad:

http://www.atnf.csiro.au/computing/software/miriad/userguide/node109.html

Please feel free to ask more questions as you play with your data.

[Kingsley]

Thanks for the reply Jamie, is there any advantage in uv vs image cleaning? I can imagine it might offer an advantage in being performed before gridding?

[ste616]

Yes, there are advantages to doing the deconvolution using the uv data. Because you're subtracting the model visibilities you should be able to better remove the objects that have the biggest PSF contributions to the image, which should allow the faintest stuff in the image to appear. But for ATCA data where the uv coverage is relatively sparse, the advantages may be lessened.

[Kingsley]

I'll give it a go to see if it makes much difference. It could be that I need to do more flagging to get the noise level down i guess.