The Skynet Algorithm for Single-Dish Radio Mapping Public Deposited

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  • February 26, 2019
  • Berger, Travis A.
    • Affiliation: College of Arts and Sciences, Department of Physics and Astronomy
  • After the National Radio Astronomy Observatory’s 20-meter diameter telescope in Green Bank, West Virginia was added to the Skynet Robotic Telescope Network - which includes optical telescopes spanning four continents - a need for a radio data-processing pipeline arose. Therefore, development began to create a pipeline similar to optical Skynet’s Afterglow, and the single-dish radio mapping algorithm was born. This algorithm has a number of advantages over traditional techniques, such as basket-weaving. (1) The algorithm makes use of weighted modeling, instead of weighted averaging, to interpolate between signal measurements. This smooths the data, but without blurring it beyond instrumental resolution. Techniques that rely on weighted averaging blur point sources sometimes as much as 40%. (2) The algorithm makes use of local, instead of global, modeling to separate astronomical signal from instrumental and/or environmental signal drift along the telescope’s scans. (3) The algorithm uses a very similar, local modeling technique to separate astronomical signal from radio-frequency interference (RFI). (4) Unlike other techniques, the algorithm does not require data to be collected on a rectangular grid or regridded before processing. (5) Any pixel density may be selected for the final image. Here, the procedure is presented and evaluated using both simulated and real data. The algorithm is being integrated into the image-processing library of Skynet. Default data products will be generated on the fly, but will be customizable by the user in real time.
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  • In Copyright
  • Funding: NASA North Carolina Space Grant
  • Reichart, Daniel
  • Bachelor of Science
Honors level
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Degree granting institution
  • University of North Carolina at Chapel Hill
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