Poster Abstract

P10.15 Brian Kent (NRAO)

Theme: Data processing pipelines

Pipeline Calibration and Imaging for the Very Large Array

The VLA component of the CASA integrated pipeline produces calibrated measurement sets for the
Karl G. Jansky Very Large Array. The pipeline is written in Python and consists of individual tasks and classes. Each task contains data processing heuristics designed to decide the best CASA task execution parameters for all VLA scheduling blocks above 1 GHz. The overall pipeline heuristics development has been improved through the Very Large Array Sky Survey (VLASS), a community and NRAO driven high-resolution 3 GHz continuum survey currently being carried out. VLASS produces imaging data products that are available to the astronomical community, and serves as a test platform for the NRAO's Science Ready Data Products initiative. We present the pipeline design and workflow as it pertains to the VLA and VLASS, calibration, imaging, and resulting products.

The pipeline is developed by an international consortium of scientists and software developers based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), and the National Astronomical Observatory of Japan (NAOJ),
and the Joint ALMA Observatory (JAO).