XPipeline: Starlight subtraction at scale for MagAO-X

Joseph D. Long, Jared R. Males, Sebastiaan Y. Haffert, Laird M. Close, Katie M. Morzinski, Kyle Van Gorkom, Jennifer Lumbres, Warren Foster, Alexander Hedglen, Maggie Kautz, Alex Rodack, Lauren Schatz, Kelsey Miller, David Doelman, Steven Bos, Matthew A. Kenworthy, Frans Snik, Gilles P.P.L. Otten

Research output: Chapter in Book/Report/Conference proceedingConference contribution


MagAO-X is an extreme adaptive optics (ExAO) instrument for the Magellan Clay 6.5-meter telescope at Las Campanas Observatory in Chile. Its high spatial and temporal resolution can produce data rates of 1 TB/hr or more, including all AO system telemetry and science images. We describe the tools and architecture we use for commanding, telemetry, and science data transmission and storage. The high data volumes require a distributed approach to data processing, and we have developed a pipeline that can scale from a single laptop to dozens of HPC nodes. The same codebase can then be used for both quick-look functionality at the telescope and for post-processing. We present the software and infrastructure we have developed for ExAO data post-processing, and illustrate their use with recently acquired direct-imaging data.

Original languageEnglish (US)
Title of host publicationAdaptive Optics Systems VIII
EditorsLaura Schreiber, Dirk Schmidt, Elise Vernet
ISBN (Electronic)9781510653511
StatePublished - 2022
EventAdaptive Optics Systems VIII 2022 - Montreal, Canada
Duration: Jul 17 2022Jul 22 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceAdaptive Optics Systems VIII 2022


  • coronagraphy
  • high-performance computing
  • post-processing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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