Discovery image of the exoplanet 51 Eridani b taken in the near-infrared light with the Gemini Planet Imager on Dec. 21, 2014. The bright central star has been mostly removed to enable the detection of the million-times fainter planet.IMAGE CREDIT: GEMINI OBSERVATORY AND J. RAMEAU (UDEM) AND C. MAROIS NRC HERZBERG.
A team of researchers has developed an automated data architecture to process and index data from the Gemini Planet Imager Exoplanet Survey (GPIES).GPIES, which began in 2014, is a multiyear, direct imaging survey designed to discover and characterize young, Jupiter-sized exoplanets. The data architecture, refered to as the Data Cruncher, can make data products available less than an hour after data is collected byGPIES, and with no human intervention. This can expedite follow up observations of objects of interest.
The details are outlined in the paper, “Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey,” which was published in theJournal of Astronomical Telescopes, Instruments, and Systems. The work was supported by the Nexus for Exoplanet System Science (NExSS).NExSSis aNASAresearch coordination network supported in part by theNASAAstrobiology Program. This program element is shared betweenNASA’s Planetary Science Division (PSD) and the Astrophysics Division.
The Gemini Planet Imager Exoplanet Survey (GPIES) campaign is partially funded by National Science Foundation (NSF),NASA, the University of California and the Laboratory Directed Research and Development funding at the Lawrence Livermore National Laboratory.