Jason J. Wang, University of California, Berkeley
Marshall D. Perrin, Space Telescope Science Institute
Dmitry Savransky, Cornell University College of Engineering
Pauline Arriaga, University of California, Los Angeles
Jeffrey K. Chilcote, Kavli Institute for Particle Astrophysics and Cosmology
Robert J. De Rosa, University of California, Berkeley
Maxwell A. Millar-Blanchaer, Jet Propulsion Laboratory
Christian Marois, National Research Council Canada
Julien Rameau, Institut de Recherche sur les Exoplanètes
Schuyler G. Wolff, Space Telescope Science Institute
Jacob Shapiro, Cornell University College of Engineering
Jean Baptiste Ruffio, Kavli Institute for Particle Astrophysics and Cosmology
Jérôme Maire, Center for Astrophysics & Space Sciences
Franck Marchis, SETI Institute
James R. Graham, University of California, Berkeley
Bruce Macintosh, Kavli Institute for Particle Astrophysics and Cosmology
S. Mark Ammons, Lawrence Livermore National Laboratory
Vanessa P. Bailey, Kavli Institute for Particle Astrophysics and Cosmology
Travis S. Barman, The University of Arizona
Sebastian Bruzzone, Western University
Joanna Bulger, National Institutes of Natural Sciences - National Astronomical Observatory of Japan
Tara Cotton, University of Georgia
René Doyon, Center for Astrophysics & Space Sciences
Gaspard Duchêne, University of California, Berkeley
Michael P. Fitzgerald, University of California, Los Angeles
Katherine B. Follette, Amherst College
Stephen Goodsell, Gemini Observatory
Alexandra Z. Greenbaum, University of Michigan, Ann Arbor
Pascale Hibon, European Southern Observatory Santiago
Li Wei Hung, US National Park Service
Patrick Ingraham, Large Synoptic Survey Telescope
Paul Kalas, University of California, Berkeley
Kimberly Ward-Duong, Arizona State UniversityFollow
et al, Various Institutions

Document Type


Publication Date


Publication Title

Journal of Astronomical Telescopes, Instruments, and Systems


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 on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-Time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.


circumstellar disks, Data Cruncher., data processing, exoplanets, Gemini planet imager, high contrast imaging










Peer reviewed accepted manuscript.



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