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  1. SAFe Program
  2. SP-788

Heterogeneous Beam Imaging

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    • Data Processing
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      Understanding the effect of heterogeneous beams on imaging performance, and how this influences design parameters such as integration time and self-cal cycles is vitally important.

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      Understanding the effect of heterogeneous beams on imaging performance, and how this influences design parameters such as integration time and self-cal cycles is vitally important.
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      Report describing the parameter space exploration of images produced using simulated visibilities.

      As a stretch, a report comparing two existing mitigation techniques.

       

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      Report describing the parameter space exploration of images produced using simulated visibilities. As a stretch, a report comparing two existing mitigation techniques.  
    • 4
    • 5
    • 3.25
    • Team_SPAZA
    • Sprint 5
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      Initial outcomes are documented in linked stories - eg.
      https://jira.skatelescope.org/browse/SPAZA-104

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      Initial outcomes are documented in linked stories - eg. https://jira.skatelescope.org/browse/SPAZA-104
    • 12.1
    • Stories Completed, Outcomes Reviewed, Demonstrated, Satisfies Acceptance Criteria
    • PI22 - UNCOVERED

    Description

      A follow on from the work in SP-654, we now have a framework in place to produced simulated visibilities using the MeerKAT+ array configuration with two classes of beam patterns.

      The next step is to being exploring a range of parameters in the imaging chain to see their effect on overall image quality when working in the heterogeneous regime (e.g. source positions, self-cal levels, frequency dependence, etc...).

      This work will also be used to evaluate the time and frequency averaging strategies for MKAT+ and make a recommendation on these parameters.

      As a stretch an evaluation of existing mitigation techniques will be undertaken. As a first pass this will include MFBeam (degredding solution) and DDFacet (AWProjection).

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                r.laing Laing, Robert
                S.Ratcliffe Ratcliffe, Simon
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                  Story Point Burn-up: (100.00%)

                  Feature Estimate: 4.0

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