Spectral Bandpass Calibration (bandpass)

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4.4.2 Spectral Bandpass Calibration (bandpass)

For channelized data, it is often desirable to solve for the gain variations in frequency as well as in time. Variation in frequency arises as a result of non-uniform filter passbands or other frequency-dependent effects in signal transmission. It is usually the case that these frequency-dependent effects vary on timescales much longer than the time-dependent effects handled by the gain types ’G’ and ’T’. Thus, it makes sense to solve for them as a separate term: ’B’, using the bandpass task.

The inputs to bandpass are:

#  bandpass :: Calculates a bandpass calibration solution
vis                 =         ’’        #  Name of input visibility file
caltable            =         ’’        #  Name of output gain calibration table
field               =         ’’        #  Select field using field id(s) or field name(s)
spw                 =         ’’        #  Select spectral window/channels
intent              =         ’’        #  Select observing intent
selectdata          =      False        #  Other data selection parameters
solint              =      ’inf’        #  Solution interval
combine             =     ’scan’        #  Data axes which to combine for solve (scan, spw,
                                        #   and/or field)
refant              =         ’’        #  Reference antenna name(s)
minblperant         =          4        #  Minimum baselines _per antenna_ required for solve
minsnr              =        3.0        #  Reject solutions below this SNR (only applies for
                                        #   bandtype = B)
solnorm             =      False        #  Normalize average solution amplitudes to 1.0
bandtype            =        ’B’        #  Type of bandpass solution (B or BPOLY)
     fillgaps       =          0        #  Fill flagged solution channels by interpolation

append              =      False        #  Append solutions to the (existing) table
gaintable           =       [’’]        #  Gain calibration table(s) to apply on the fly
gainfield           =       [’’]        #  Select a subset of calibrators from gaintable(s)
interp              =       [’’]        #  Interpolation mode (in time) to use for each gaintable
spwmap              =         []        #  Spectral windows combinations to form for
                                        #   gaintables(s)
gaincurve           =      False        #  Apply internal VLA antenna gain curve correction
opacity             =         []        #  Opacity correction to apply (nepers), per spw
parang              =      False        #  Apply parallactic angle correction
async               =      False        #  If true the taskname must be started using
                                        #   bandpass(...)

Many of these parameters are in common with the other calibration tasks and are described above in § 4.4.1.

The bandtype parameter selects the type of solution used for the bandpass. The choices are ’B’ and ’BPOLY’. The former solves for a complex gain in each channel in the selected part of the MS. See § 4.4.2.2 for more on ’B’. The latter uses a polynomial as a function of channel to fit the bandpass, and expands further to reveal a number of sub-parameters See § 4.4.2.3 for more on ’BPOLY’.

It is usually best to solve for the bandpass in channel data before solving for the gain as a function of time. However, if the gains of the bandpass calibrator observations are fluctuating over the timerange of those observations, then it can be helpful to first solve for the gains of that source with gaincal , and input these to bandpass via gaintable. See more below on this strategy.

We now describe the issue of bandpass normalization, followed by a description of the options bandtype=’B’ and bandtype=’BPOLY’.

   4.4.2.1 Bandpass Normalization
   4.4.2.2 B solutions
   4.4.2.3 BPOLY solutions

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