WorkshopSelfcal

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This page describes the hands-on self calibration portion of the ALMA data reduction workshop. In this session you will carry out self-calibration on ALMA Science Verification data to improve the image quality. This page describes the data and introduces the scripts. It is not a full-fledged CASA guide, only background for the hands on portion of the workshop. For the imaging session in the morning go here: WorkshopImaging

Overview

Data Description

You will use the now-familiar NGC 3256 Band 3 or TW Hydra Band 7 Science Verification data. You have seen these already this morning. Both contain several lines, including CO emission, and continuum emission. We will begin by imaging the continuum emission and using that to self calibrate. We will then see how to apply that self-calibration to improve the line images.

Note that it is perfectly possible to self-calibrate the other TW Hydra data or the Antennae Band 7 data (see AntennaeBand7). If you finish quickly, you might try to write your own script to do this.

Recommended Approach

Review the basics of how to use these scripts in WorkshopImaging. Assuming that you are comfortable with imaging, we suggest to grab the script above. Use it to image NGC 3256 or TW Hydra (just uncomment/comment the relevant portions to apply the script to either data set), making sure that the "calready" parameter is set to True. Then use gaincal to derive the complex gain corrections to each antenna that best match the data to the model. When you are satisfied with these corrections, apply them to the data to create a new corrected data set. Image those data.

The script takes you through one iteration of this self-calibration but the approach can be iterative, improving the model of the source as the corrected data become more and more accurate. Once you are comfortable with the procedure, try iterating and perhaps adding an amplitude calibration to the selfcal. Your degrees of freedom in this process are the solution interval and how you otherwise combine the data (averaging polarizations, spectral windows or channels, using a specific field in a mosaic). Try experimenting with these settings to see how your results are affected. Your basic diagnostic is the plotting of solutions using plotcal but the amount of noise and the structure of the residuals in the final image can also be useful indicators.

Continuum Self Calibration

File:Basic selfcal.py

Continuum-to-Line Self Calibration

Self-calibration can also be used to improve your spectral line imaging.