Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

  title={Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey},
  author={Jason J. Wang and Marshall D. Perrin and Dmitry Savransky and Pauline Arriaga and Jeffrey K. Chilcote and Robert J. de Rosa and Maxwell A. Millar-Blanchaer and Christian Marois and Julien Rameau and Schuyler G. Wolff and Jacob Shapiro and Jean-Baptiste Ruffio and J'erome Maire and Franck Marchis and James R. Graham and Bruce A. Macintosh and S. Mark Ammons and Vanessa P. Bailey and Travis S. Barman and Sebastian Bruzzone and Joanna Bulger and Tara H. Cotten and Ren{\'e} Doyon and Gaspard Duch{\^e}ne and Michael P. Fitzgerald and Katherine B. Follette and Stephen J. Goodsell and Alexandra Z. Greenbaum and Pascale Hibon and Li-Wei Hung and Patrick Ingraham and Paul Kalas and Quinn M. Konopacky and James E. Larkin and Mark. S. Marley and Stanimir A. Metchev and Eric L. Nielsen and Rebecca Oppenheimer and David Palmer and Jennifer L. Patience and Lisa Ann Poyneer and Laurent Pueyo and Abhijith Rajan and Fredrik T. Rantakyr{\"o} and Adam C. Schneider and Anand Sivaramakrishnan and Inseok Song and R{\'e}mi Soummer and Sandrine J. Thomas and J. Kent Wallace and Kimberly Ward-Duong and Sloane J. Wiktorowicz},
  journal={Journal of Astronomical Telescopes, Instruments, and Systems},
Abstract. The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and… 

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