Use Case: Offline: Reduce & Image Single Field Data (with and without single dish data)

Interferometric Use Case for ALMA (based on ALMA SW Memo 11, Science Requirements and Use Cases, modified to include offline processing requirements).

Goal:   Reduce and image data from a detection experiment or high-fidelity imaging experiment of a single ALMA field.

Contact Author:   D. Shepherd

Role(s)/Actor(s):
Primary:   The PI (follows the basic course for this UseCase)
Secondaries:  
  Archive (needed to download data into offline package or disk/tape.)
  Offline (to do the actual data reduction and imaging)

Priority:   Critical

Performance:   Response to user inputs in near real time. Typical reduction session for an experienced user should not take more than a few hours.

Frequency of Use:   Perform this Offline Use Case for each single field imaging experiment run by ALMA.

Preconditions:

1. Observations have been made by ALMA.
2. WVR corrections have been made on-line and stored in the Archive file.
3. Archive file includes all necessary calibration & source observations (e.g. not just a partial scheduling block).
4. Interferometric uv data has been downloaded from the Archive or is available on tape or disk in ALMA FITS format.
5. If combining single dish and interferometric data: calibrated, single dish image is available on disk (downloaded from the archive or reduced in a previous UseCase.

Basic Course:

NOTE: All steps in the Basic Course should be able to be saved to a master script. Alternatively, the user can start from a master pipeline script downloaded from the Archive, and modified to run this entire sequence or just parts of the sequence.

1. Fill the data from the Archive, tape, or disk into the Data Reduction Package.
   
2. Correct antenna gains as a function of elevation based on look-up tables.
   
3. Estimate atmospheric opacity based on weather information and correct the data if needed.
   
4. Edit data interactively and/or automatically:
   A.   Automatic editing requires built-in heuristics which will identify bad data (e.g. pipeline-like).
   B.   Use Pointing, Tsys, Weather information in the decision process to determine location of bad data.
   
5. Using observations of a primary or secondary flux calibrator, determine the flux calibration.
   
6. Estimate the Parallactic angle correction based on a lookup table and correct the data if doing polarization.
   
7. Using observations of a gain calibrator observed between source scans, compute phase & amplitude (including absolute flux) calibration and apply to target scans by an interpolation algorithm suitable for the atmospheric conditions.
   
8. Based on a plot of calibrator solutions displayed with calibrator & source uv data, edit calibrator and source data if a solution interval is bad.
   
9. Using observations of a bandpass calibrator, compute the bandpass for each correlator setup and apply to all data.
   
10. Using observations of a polarization calibrator, determine the instrumental polarization calibration ('leakage' solutions) and apply to all the data.
    
11. Edit the data by deleting antennas with poor bandpass or polarization calibration solutions.
    

1. Weight selected source uv data. Get psf and mosaic sensitivity images generated here and a report of the theoretical RMS noise expected in the image.
   
2. Grid the data, Fourier transform & deconvolve the image to form a clean image.
   
3. Derive a model from the image, that can be used to self-calibrate the image.
   
4. Repeat calibration (above steps) to obtain an incremental phase correction to the gain solutions on short timescales. Apply new calibration to the target data.
   
5. Repeat imaging steps.
   
6. Continue to iterate, finding incremental phase &/or amplitude solutions until incremental improvements are in the noise.
   

1. Identify spectral lines (manually or using header information [or possibly a Lovas catalog?]), identify multiple chunks of continuum channels and do a uv continuum subtraction.
   
2. Save the line-only and continuum-only data separately.
   
3. Edit the source data again, manually or automatically.
   

1. Weight calibrated source uv data. Get psf and mosaic sensitivity images generated here and a report of the theoretical RMS noise expected in the image.
   
2. Grid the data, Fourier transform & deconvolve the image to form a clean image.
   

1. Fourier transform the calibrated single dish image to the uv plane.
   
2. Weight the calibrated interferometer and single dish uv data properly. Get psf and mosaic sensitivity images for the interferometric mosaic field generated here and a report of the theoretical RMS noise expected in the image (both with and without the single dish data added).
   NOTE: Image feathering is not considered because the ALMA single dish will likely not provide good uv overlap and the antenna primary beam FWHM will be greater than 10 times the synthesized beam of ALMA.
3. Grid the combined data, Fourier transform & deconvolve the image using clean, multi-scale clean, or MEM to form a clean image.
   

1. Analyze the image cube for science results. (details are TBD)
   
2. Generate a publication-quality figure with annotation, overlays, and comparison images if desired.
   

1. Write out calibrated target data and images to FITS files on disk or tape.
   

Postconditions:

1. Publication-quality figures are generated.
2. Image statistics and analysis results are available to user.
3. Calibrated data & images are stored for later use if needed.
4. Calibration & imaging script recording session is available (if desired by the user).

Issues to be Determined or Resolved:   None at this time.

Notes:   This Use Case was created by D. Shepherd & S. Myers. It was created to help test the Offline software. Relevant SSR Use Cases from SSR Memo 11 are: 4.6.2 (Retrieve Archived Data); 4.7.1 (Reduce Single Field [in pipeline mode]).

Last modified: 01jul03