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The Kepler spacecraft launched on March 7, 2009, initiating NASA’s first search for Earth-size planets orbiting Sun-like stars, with stunning results after being on the job for just over two years. Designing and building the Kepler science pipeline software that processes and analyzes the resulting data to make the discoveries presented a daunting set of challenges.
Although capable of reaching a precision near 20 ppm in 6.5 hours in order to detect 80-ppm drops in brightness corresponding to Earth-size transits, the instrument is sensitive to its environment. Identifying and removing instrumental signatures from the data as well as characterizing the varability of the stars themselves has proven to be extremely important in the quest for Earth-size planets. In addition, the computational intensity of processing the accumulating data compelled us to port the detection and validation pipeline components to the Pleides supercomputer at NASA Ames Research Center. As we look forward to an extended mission of up to 10 years of flight operations, balancing the need for speed against the requirement for ultrahigh precision presents a challenge.
Jon Jenkins is a research scientist for the SETI Institute (www.seti.org ) at NASA Ames Research Center where he conducts research on data processing and detection algorithms for discovering transiting extrasolar planets. He is the Co-Investigator for Data Analysis for NASA Discovery Program’s Kepler Mission (http://www.kepler.nasa.gov ). As the Kepler Mission Analysis Lead, Dr. Jenkins is responsible for developing algorithms for the Kepler Science Operations Center science pipeline and leads the team of scientific programmers who are implementing the software for the science pipeline. In 2010 Dr. Jenkins received NASA’s Exceptional Technology Achievement Medal for his numerous technical achievements throughout development, commissioning and operational phases, which have been critical to the success of Kepler.
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