VLA Self-calibration Tutorial-CASA5.7.0: Difference between revisions
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== Data for this Tutorial == | == Data for this Tutorial == | ||
===Context=== | === Context === | ||
===Observation Details=== | === Observation Details === | ||
=== Obtaining the Data === | |||
== Initial Imaging == | == Initial Imaging == | ||
Revision as of 18:36, 14 May 2019
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.
Data for this Tutorial
Context
Observation Details
Obtaining the Data
Initial Imaging
more text
Link to the task tclean
# in CASA
tclean( vis=...
