Spatial Transfer Functions, revisit 4

Last report was a bit of a fiasco. There were problems all over the place I didn't understand. I still don't but I've fixed them. My best guess at this point is that a pass-by-reference led to an unacceptable modification of an image. That doesn't even make sense - there was no place it could have happened - but, there you have it.

So, going through the process step by step.

This is the effect of smoothing an image:

Note from the 3rd figure that 100% recovery isn't reached until ~700 arcseconds.


Next question: What is happening at large spatial scales in the flat-spectrum simulations?

No obvious problems there.

Hmm, no apparent problem here either, though one might ask why the two curves approach each other in sky05 (alpha=-0.5).

So it appears that the reason for the bump up at low frequencies (long wavelengths) must be because of edge effects. After much hassle, I've addressed that by cropping images.

Finally, the averaged results:

So we've got an Official Spatial Transfer Function.

However, of course, we must note that there is a dependence on the atmosphere amplitude to source amplitude ratio: it appears that large-scale structure is *easier* to recover when the atmosphere is at higher amplitude. This makes sense: it is easier to distinguish faint astrophysical signal from bright atmosphere in this case. The reason I didn't run simulations to test this more is that the S/N ratio on small scales becomes poor for the low astrophysical amplitudes.

Definitive Testing

It is now possible to make artificial timestreams!

First round of tests:
For pointing maps with ~21 scans in 15" steps, array angle is approximately negligible.
deconv does NOT recover point sources, but reconv does (perfectly)
The algorithm starts to decay and produce weird ringey residuals at a S/N ~300. The residuals are only at the 1% level out to S/N ~1000.