New functionality to process Very Long Baseline Interferometry (VLBI) data has been implemented in the CASA package. This includes two new tasks to handle fringe fitting and VLBI-specific amplitude calibration steps. Existing tasks have been adjusted to handle VLBI visibility data and calibration meta-data properly. With these updates, it is now possible to process VLBI continuum and spectral line observations in CASA. This article describes the development and implementation, and presents an outline for the workflow when calibrating European VLBI Network or Very Long Baseline Array data in CASA. Though the CASA VLBI functionality has already been vetted extensively as part of the Event Horizon Telescope data processing, in this paper we compare results for the same data set processed in CASA and AIPS. We find identical results for the two packages and conclude that CASA in some cases performs better, though it cannot match AIPS for single-core processing time. The new functionality in CASA allows for easy development of pipelines or Jupyter notebooks, and thus contributes to raising VLBI data processing to present day standards for accessibility, reproducibility, and reusability.

CASA on the Fringe—Development of VLBI Processing Capabilities for CASA

Goddi C.;
2022-01-01

Abstract

New functionality to process Very Long Baseline Interferometry (VLBI) data has been implemented in the CASA package. This includes two new tasks to handle fringe fitting and VLBI-specific amplitude calibration steps. Existing tasks have been adjusted to handle VLBI visibility data and calibration meta-data properly. With these updates, it is now possible to process VLBI continuum and spectral line observations in CASA. This article describes the development and implementation, and presents an outline for the workflow when calibrating European VLBI Network or Very Long Baseline Array data in CASA. Though the CASA VLBI functionality has already been vetted extensively as part of the Event Horizon Telescope data processing, in this paper we compare results for the same data set processed in CASA and AIPS. We find identical results for the two packages and conclude that CASA in some cases performs better, though it cannot match AIPS for single-core processing time. The new functionality in CASA allows for easy development of pipelines or Jupyter notebooks, and thus contributes to raising VLBI data processing to present day standards for accessibility, reproducibility, and reusability.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/370383
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