- Validation of the solution
- One of the difficulties of self-calibration is to evaluate whether
it has improved the image or not. The self-calibration
solution is biased towards the assumed model. If used with insufficient
signal to noise, it will tend to produce a point source at the
initial peak position, and the bias will be of order of the noise.
This may be inappropriate.
Currently, the validity of the self-calibration solution is based on
the estimated signal to noise ratio for the gains at each time step.
If that SNR is below a user-controlled threshold (by default,
SELF_SNR=6),
the corresponding data is flagged (default value:
SELF_FLAG=YES)
or kept WITHOUT self calibration (if
SELF_FLAG=NO).
- Flagging or not flagging ?
- The decision to flag or not results from a trade-off:
-
SELF_FLAG
\(=\)
Yes : will result in no contamination by bad data, but
may lead to lower angular resolution since long baselines may be flagged.
-
SELF_FLAG
\(=\)
No: will avoid loosing all long baselines (where the SNR is lower)
Both options may be explored, and it is recommended to check afterwards the final angular
resolution with and without flagging. It is however recommended to use
SELF_FLAG
\(=\)
No
for Mosaics, in order to keep the best possible UV coverage for every field.
The following scheme is proposed to check the validity of the self-calibration solution:
- read the status using
SELFCAL SUMMARY
- use
SELFCAL SHOW to verify if the solution is converged
- if it looks good, but noise is still far from theoretical, try
again to self-calibrate with a shorter integration time (
SELF_TIMES).
- if it is not good, try to increase
SELF_TIMES and find an
optimum value. For ALMA data, typical values may be in the range
\(6-60\)
s, and for NOEMA in the range
\(45-120\)
s. Alternatively, you
can also try to decrease
SELF_SNR to lower values, but never
less than 3.
From our experience, the number of loops
SELF_NLOOP does not impact
much the quality of the solution, and 2 to 3 iterations are usually
sufficient.
Warning: the comparison with theoretical noise relies on a proper
scaling of the weights of the UV data. This is fine for the IRAM array,
but data exported from CASA is not always correct in this respect.
UV_PREVIEW can warn you about potential issues in this respect.
UV_REWEIGHT can also evaluate the scaling factor that should be
applied to the weights to recover the apparent noise level.
UV_PREVIEW
requires a sufficient number of spectral channels for this purpose.
By default,
UV_REWEIGHT suffers from a similar restriction,
and both commands may fail if the bandwidth is clobbered with spectral lines or has
strong continuum. However,
UV_REWEIGHT has a
TIME mode where
the noise is estimated from consecutive visibilities, and thus is not
affected by this limitation.
The appropriate scaling factor can be specified in
SELFCAL by
variable
SELF_SNOISE.
