CASA, the Common Astronomy Software Applications package, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and NSF's Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can process data from both single-dish and aperture-synthesis telescopes, and one of its core functionalities is to support the data reduction and imaging pipelines for ALMA, VLA and the VLA Sky Survey (VLASS).

Latest CASA Release: 6.5*

                • CASA paper: "CASA, the Common Astronomy Software Applications for Radio Astronomy", PASP, 134, 114501
                • Modular CASA: separate python wheels for casafeather, casabrowser and casalogger GUIs.
                • Modular CASA: the CASA6 build system has been refactored to improve modularity within the code base, to better streamline dependency management, and to support future development and deployment requirements.
                • deconvolve: new task for image-domain deconvolution.
                • mvuvbin: new experimental task to save a measurement set as a UV grid.
                • uvcontsub: new implementation, old uvcontsub task deprecated.
                • setjy: updated VLA flux calibrator model images at C, X and Ka bands; will catch unreasonable input spectral index.
                • fringefit: support for ‘uvrange’ and 'corrcomb' parameters; new functionality 'concatspw' or combine='spw'.
                • fringefit: updated to allow the use of the cal library to apply pre-calibration.
                • table tool: new table tool method tb.getcoliter(), for iterator access to casacore tables.
                • applycal: handles calibration tables with fewer SPWs than the applying MS.
                • tclean: new iteration control parameter ‘nmajor’.
                • tclean: new parameter 'fullsummary' to avoid issues with large cubes and increased MPI records.
                • tclean: more stable cube imaging with 'awproject'; numerical fixes w-term correction 'awproject'.
                • simobserve support added for component lists having higher order spectral terms.
                • sdimaging: new parameter ‘enablecache’ for improved performance.
                • applycal: per scan interpolation.
                • mstransform: parameter ‘douvcontsub’ deprecated.
                • flagdata: mode=’shadow’ now uses the uvw values from the UVW column.
                • tclean/tsdimaging: performance improvements of about 10-16 percent, and improved runtime performance of ephemeris imaging.
                • tclean: corrections to the math implemented for the uvtaper weighting scheme.
                • simulator tool: new parameter ‘simint’ in sm.settrop() to control time granularity, down to 0.1s.
                • simulator tool: now works with primary beams and a component list with spectral structure.
                • imbaseline: new task for image-based baseline subtraction for single-dish data.
                • msmetadata tool: ALMA-specific methods 'rxband()' and 'subwindows()'.
                • corrbit(): new method in msmetadata tool for returning the value in SPECTRAL_WINDOW:: SDM_CORR_BIT column.
                • plotms: added support for additional axes of calibration tables.
                • setjy: parameter "modimage" removed (use parameter "model" instead).
                • tclean: return dictionary now includes additional information about the minor cycles.
                • Mac OS 12: bug fixed that prevented the OS 11/Python 3.6 package to open on Mac OS 12.
                • tclean: bug fixed that prevented UV taper to work with weighting=’natural’.

                 For details and more, see

The CASA team has begun exploring options for a new generation of software to meet the growing demands of current and future radio telescopes. This CASA Next Generation Infrastructure (CNGI) prototype package is a demonstration of the current state of our research efforts. Its primary purpose is to showcase new data structures for MeasurementSet and Image contents built entirely in Python atop the popular technology stack of numpy, dask, and xarray.

The CNGI prototype documentation contains Visibility and Image overview sections that describe a selection of core mathematics, manipulation, middleware and analysis functions to demonstrate the simplicity and scalability of the technology choices. Notional examples of Calibration, Flagging and Imaging are provided to illustrate future design and implementation direction. A detailed explanation of technology choices, including the xarray and dask frameworks, the zarr storage format, and the functional design architecture can be found in the Development section.

Finally, the most compute intensive areas of CASA imaging are implemented and benchmarked to demonstrate the parallel scalability and raw performance now possible from a pure-Python software stack.

We invite anyone interested to explore the new cngi_prototype package. We welcome your feedback at

CASA is being developed by an international team of scientists based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), and the National Astronomical Observatory of Japan (NAOJ), under the guidance of NRAO.