I remember thinking about this briefly in a post further down, and neither Amanda nor I could come to a good solution without resorting to Miriad. After running into the problem myself and spending a lot of time dealing with AIPS, I think I've come to a solution.
Caveat: this is only valid for combining VLA data with other VLA data. I don't think it will work with ATNF/GMRT + VLA data, but I haven't tried.
I managed to fix this problem in the case of VLA data with a combination of UVCOP, SPECR, and CVEL. Basically, it works because the VLA correlator setup is all multiples of two. In general, if you have a data set with twice as many channels, it has half the channel spacing. This is not always true due to an observer's ability to set up IFs in different ways, but the channel spacings should always differ by some power of two.
Now for the solution(s).
For example, imagine you have spectral line data set A with 127 channels and spacing of 6.1 kHz, and data set B with 255 channels and spacing of 3.05 kHz. (The extra channel from each needed to make a power of two is the Channel 0 data set. So you really only have 127 instead of 128 and 255 instead of 256 channels.) Effectively, you will have to either double the channel spacing of data set B, or half the channel size of data set A.
In order to DBCON, you will need to jump through many AIPS hoops in order to make sure that both data sets have:
- the same number of channels
- the same spectral resolution
- the same frequencies assigned to the same channels
To degrade the high-resolution data:
- First, you will need to use UVCOP to chop off one channel in data set B, so an integer number of channels in SPECR will give you the correct velocity resolution. It shouldn't matter if you chop one off from the beginning or from the end, as these are generally line free.
- Next, use SPECR to regrid data set B to the proper channel spacing. In this case, you will want a channel spacing of 6.1 kHz. This means that you need to tell SPECR to regrid to half as many channels. Each new channel has twice the original channel spacing. In this case, you will tell SPECR to use npoints 127, which is conveniently half of 254.
- Now run CVEL on both data sets. The correct inputs are described at the bottom of this guide. The main APARM values to set are:
aparm(1) = [velocity in m/s to be assigned to..]
aparm(2) = [..this channel number]
Essentially, you have regridded both of your data sets to a system where the given velocity is assigned to the given channel. It may spit out a lot of errors saying that it is shifting the channels by many km/s, but as long as the same channels in both data sets correspond to the same velocities, you're set.
- Run UVCOP to chop off additional channels if necessary. In this case, the data sets should be the same, but depending on correlator settings, you may have to chop off additional channels. This time, always chop them off from the end, because you have regridded your data so that the first channels in the set line up with the first channels in the other data set.
- Run DBCON to combine both data sets. DBCON will shift RA and Dec as long as the pointing centers aren't vastly different.
To oversample the low-resolution data:
- Use SPECR to regrid data set A to 254 (NOT 255) channels. This will effectively chop your channel width in half, so it matches data set B. You will deal with the fact that both data sets have a different number of channels in a few steps, so don't worry.
- Use CVEL to assign the same frequency to the same channel for both observations. This will shift each spectrum in frequency/channel, but will not resize the channel spacing. More instructions for using CVEL are at the bottom of the guide. The important inputs are:
aparm(1) = [velocity in m/s to be assigned to..]
aparm(2) = [..this channel number]
Essentially, you have regridded both of your data sets to a system where the given velocity is assigned to the given channel. CVEL may spit out a LOT of errors telling you that you are shifting your channels by a lot, but as long as your galaxy shows up in the same channels in both datasets, you should be okay.
- use UVCOP to chop off additional channels. Data set A (after SPECR) has 1 fewer channel than data set B. Fix this by chopping off the last channel of data set B using UVCOP. Set BCHAN 0 and ECHAN 254.
- Use DBCON to combine data set A (after SPECR + CVEL) and data set B (after CVEL + UVCOP). It should shift the RA and Dec of the one of the data sets unless they have vastly different pointing centers.
Now for something completely different (aka additional notes):
Occasionally you will have to chop off more channels from data set A, depending on your correlator set up for both observations. The key point is to make sure that both data sets have the same number of channels with the same channel spacing and the same velocity definition (e.g., channel 52 = -50 km/s).
And now some info on running CVEL. In some of our observations, we did not use Doppler tracking (Oh, EVLA, you'll be awesome one day), so we also had to tell CVEL the rest frequency of our HI line so it could calculate gas velocity. You may not need all of these inputs, but here's how I had to set the APARM values, which is really the meat of CVEL:
aparm -50000 52 1 0 1.420e09 5752 1 0
What does this mean? Well!
aparm(1) = -50000
aparm(2) = 52
Together these two values shift the spectrum so that a velocity of -50000 m/s lines up with channel 52. This will be different for each galaxy - in our case, it's a galaxy with a systemic velocity of -50000 m/s (NGC 404 in fact).
aparm(3) = 1
aparm(4) = 0
These set the velocity definition. The first sets the reference to heliocentric velocity, and the second tells AIPS to use the optical definition.
aparm(5) = 1.420e09
aparm(6) = 5752
This sets the rest frequency of your line in GHz. AIPS does not have enough precision for all the significant figures, so you have to use two APARM values. If you're working with something other than HI, I recommend reading the help file to figure out how to input your frequency.
aparm(7) = 1
This is set to 1 for VLA data.
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