Physical Sciences and Mathematics Commons^™

Automated Data Processing Architecture For The Gemini Planet Imager Exoplanet Survey, Jason J. Wang, Marshall D. Perrin, Dmitry Savransky, Pauline Arriaga, Jeffrey K. Chilcote, Robert J. De Rosa, Maxwell A. Millar-Blanchaer, Christian Marois, Julien Rameau, Schuyler G. Wolff, Jacob Shapiro, Jean Baptiste Ruffio, Jérôme Maire, Franck Marchis, James R. Graham, Bruce Macintosh, S. Mark Ammons, Vanessa P. Bailey, Travis S. Barman, Sebastian Bruzzone, Joanna Bulger, Tara Cotton, René Doyon, Gaspard Duchêne, Michael P. Fitzgerald, Katherine B. Follette, Stephen Goodsell, Alexandra Z. Greenbaum, Pascale Hibon, Li Wei Hung, Patrick Ingraham, Paul Kalas, Kimberly Ward-Duong, Et Al

Astronomy: Faculty Publications

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 calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up …