SDP (AA2) Low Self-calibration pipeline

Building on a RASCIL-based imaging and deconvolution pipeline, this will provide an MVP pipeline with required documentation and sample data which can gradually be iterated into the Low self-calibration pipeline.

Who?

• Commissioning scientists
• SKA Science Regional Centers (SRCs)
• Astronomers 

What?

• RASCIL-based workflow in python calling functions to do flagging, calibration and imaging.
• Tested on LOFAR data or other low-frequency data with qualities similar to Low
• Defines a sequence of processing steps that defines a minimal workflow producing a limited-quality but meaningful end product.
• Capability to be iterated into full deconvolution and DD calibration pipeline
• Can use coarse-grained processing components adapted from existing software

Why?

•  Commissioning scientists benefit from a working low self-calibration pipeline to create first imaging results.
• SRCs can use the SKA-LOW self-calibration pipeline to serve their end users or use it as starting point for fine tuning to produce new workflows serving the needs of their astronomical end users.
• The SKA-LOW self-calibration pipeline will produce imaging products with sufficient quality to be useful for most astronomers who are not radio interferometry expert.