2022
DOI: 10.1088/1538-3873/ac9642
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CASA, the Common Astronomy Software Applications for Radio Astronomy

Abstract: CASA, the Common Astronomy Software Applications, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can handle data from single-dish, aperture-synthesis, and Very Long Baseline Interferometery (VLBI) telescopes. One of its core functionalities is to support the calibration and imaging pipelines for ALMA, VLA, VLA Sky Survey, and the Nobeyama … Show more

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Cited by 327 publications
(55 citation statements)
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References 88 publications
(86 reference statements)
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“…) package version 5.6.1 (McMullin et al 2007;CASA Team et al 2022), while the 12 m Array data were pipeline-calibrated with the same version of . This included all the standard calibration steps applied to the phases and the amplitudes of the data.…”
Section: Alma Observations and Data Processingmentioning
confidence: 99%
“…) package version 5.6.1 (McMullin et al 2007;CASA Team et al 2022), while the 12 m Array data were pipeline-calibrated with the same version of . This included all the standard calibration steps applied to the phases and the amplitudes of the data.…”
Section: Alma Observations and Data Processingmentioning
confidence: 99%
“…To investigate the origin of the feature, we simulate the observation with a similar setup: hour angle, sky position, antenna configuration, and realistic atomospheric noise, but without emission in the sky, using SIMALMA in CASA. 20 (The actual data are taken with ∼2 h observation, with 1 h of integration on a source intermittently separated by calibrator observations and other overheads. In comparison, the simulated observation is a continuous 1 h of integration on the source.)…”
Section: Discussionmentioning
confidence: 99%
“…We use Common Astronomy Software Applications (CASA, CASA Team et al 2022) to reduce the data and perform imaging. A spectral cube is created using tclean task with natural weighting and a 100 km s −1 channel width.…”
Section: Sample and Data Analysismentioning
confidence: 99%