VLA Self-calibration Tutorial-CASA5.7.0

This page is currently under construction.

Introduction

This CASA guide describes the basics of the self-calibration process and in particular how to choose parameters to achieve the best result. Even after the initial calibration of the dataset using the amplitude calibrator and the phase calibrator, there are likely to be residual phase and/or amplitude errors in the data. Self-calibration is the process of using an existing model, often constructed from imaging the data itself, to reduce the remaining phase and amplitude errors in your image.

The dataset that will be used for this CASA tutorial is an observation of a massive galaxy cluster at z~1 which was taken with the goal to determine the morphology of the radio sources within the cluster.

Data for this Tutorial

Observation Details

Once CASA is up and running in the directory containing the data, then start your data reduction by getting some basic information about the data. The task listobs can be used to get a listing of the individual scans comprising the observation, the frequency setup, source list, and antenna locations.

# in CASA
listobs(vis='MOO_1506+5136_Cband.ms')

================================================================================
           MeasurementSet Name:  /filepath/     MS Version 2
================================================================================
   Observer: Prof. Anthony H. Gonzalez     Project: uid://evla/pdb/34052589  
Observation: EVLA
Data records: 5290272       Total elapsed time = 2853 seconds
   Observed from   13-Oct-2017/20:40:09.0   to   13-Oct-2017/21:27:42.0 (UTC)

Initial Imaging

First, we want to make an initial image which showcases why we need self-calibration in this case.

Link to the task tclean

# in CASA
tclean( vis=...