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
Obtaining the Data
Observation Details
# in CASA
listobs(vis='MOO_1506+5136_Cband.ms')
Initial Imaging
more text
Link to the task tclean
# in CASA
tclean( vis=...
