Wednesday, July 9, 2008

How to Know When You Can Self-Cal and What Solint To Use

Have you ever done a self-calibration run to find out the self cal is actually making your images worse, not better? Have you ever guessed at what SOLINT to use while self calibrating? I know I have!

People always say you should evaluate the signal-to-noise of your data before self-calibrating, but I never understood what this meant until today! There is a simple equation to find out if you can self-cal and if the SOLINT you are considering might be too short....

First image your data and clean it pretty good. Afterwards you can look in the image header and not the total cleaned flux. This is your 'Signal'.

Second of all, you want to calculate the noise in your data, per baseline per SOLINT. First, measure the rms noise in your image, in Jy/beam (sig_image). Next, calculate the number of baselines in your data (N_base where N_base = ((N_ant * N_ant-1) / 2) and N_ant is the number of operational antennae). Finally, figure out how much time-on-source went into making your image, in minutes (TOS). The noise of your data per baseline for a given SOLINT (in minutes) is then:
Noise = sig_image * sqrt(N_base) * sqrt(TOS/SOLINT)

Now, compare the 'Signal' with the 'Noise'. For 'P' self cal, you want the Signal to be at least 5 times greater than the Noise. If it's not, then increase your SOLINT. For A&P self cal, you probably want a signal-to-noise of 10-20, at least.

Note: If you are doing multi-facet imaging (at lower frequencies), you want to use the total flux in your data-- that is the sum from all facets, The image headers tell you this as 'CCTOTAL'.

No comments: