ALMA's dirty beams


  1. Produce a set of point spread function images, both snapshots and 4 hour integrations, for each of ALMA's 12m configurations, for various declinations.
  2. Extract interesting parameters from those images and put them in tables.


ALMA will have 28 configurations (counting only the outbound ones) in its array of 12m antennas, so obviously some sort of script(s) for setting things up, running almasimmos, and summarizing the results is in order. Fortunately CASA comes with python.

Input model

Dirty beams do not depend on the sky, but I went ahead and gave almasimmos a 1 Jy CLEAN component to look at:
  1. dec = -23
  2. direcshun = "J2000 18h00m00.03s %sd0m0.0s" % dec
  3. cl.addcomponent(dir=direcshun,flux=1.0, freq='672.0GHz')
  4. compname = "" % dec
  5. cl.rename(compname)
  6. cl.done()

Generating the visibilities ran almasimmos with two nested loops:
  1. Configuration: the notable thing here is that it adjusted the pixel size for each configuration using avgsep.
  2. Observation length: Both snapshot (30 seconds) and extended (4 hours).

I ended up moving each declination into its own directory to maintain some sanity. CASA is able to cd without any trouble!

Summarizing the results

Provides functions for generating dirty beams with other weightings, writing the dirty beam images to FITS files, and summarizing their FWHMs, minima, and RMSs.

Example output

  Snapshot 4h Exposure
Cfg. Min RMS Maj (mas) Min (mas) Min RMS Maj (mas) Min (mas)
O-03 -0.024 0.0002 493.351 425.440 -0.020 0.0001 512.248 426.609
O-04 -0.028 0.0007 432.399 370.056 -0.019 0.0002 447.253 370.983
O-05 -0.026 0.0017 369.905 317.162 -0.019 0.0006 383.540 317.847

Snapshot 4h Exposure

-- RobReid - 21 Sep 2007
Topic revision: r2 - 2007-09-23, RobReid
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