The Kepler spacecraft was launched on 2009 March 6 with a potential operational lifetime limited by its approximately 10 year supply of propellant (Koch et al. 2010). Kepler’s primary objective is to determine the frequency of Earth-sized planets within the habitable zone of solar-like stars, achieved by detecting planetary transits of stars within high-precision time-series photometry (Borucki et al. 2010; Caldwell et al. 2010). Transit durations typically last a few hours, and they are separated by intervals of days to years. The Kepler mission collects data mostly on a 30-minute cadence near-continuously with > 92% completeness. Detection of transits by small planets requires parts-per-million photometric precision (Jenkins et al. 2002). The primary objective will be realized through the combination of space-based photometric sensitivity, regular observing cadence, a 116 square degree field-of-view containing a large number of target stars, and high duty cycle.

One of the primary Kepler legacies is a community archive containing the multi-year, time-series photometry of 2 × 10⁵ astrophysical targets observed for the planetary survey (Batalha et al. 2010) and community-nominated targets of other astrophysical interest. In addition to exoplanet science, Kepler provides unique datasets and raises scientific potential in fields such as asteroseismology (e.g. Bedding et al. 2011; Chaplin et al. 2011; Antoci et al. 2011; Beck et al. 2011), gyrochronology (Meibom et al. 2011) , stellar activity (e.g. Basri et al. 2011; Walkowicz et al. 2011), binary stars (e.g. Carter et al. 2011; Derekas et al. 2011; Slawson et al. 2011; Thompson et al. 2012), and active galactic nuclei (Mushotzky et al. 2011). This primer will address how the community can mitigate and exploit the public data for stellar and extragalactic science. Many of the techniques presented here are applied to archived light curves and target pixel files and will help optimize the data for astrophysical research.

An understanding of the nature of archived data is critical for the effective exploitation of the Kepler legacy. Kepler provides high-precision photometry on the 1 and 30 minute timescales. The data also contain artifacts that occur through spacecraft operation events and systematic trends over longer timescales as a natural consequence of mission design (Van Cleve & Caldwell 2009; Christiansen et al. 2011). Artifacts can both mask astrophysical signal and be misinterpreted as astrophysical in origin (Christiansen et al. 2011). Furthermore, cavalier approaches to artifact mitigation (e.g. using simple function fits to time-series data) can destroy astrophysical signal. Archived Kepler data have been processed through a data reduction pipeline (Fanelli et al. 2011). The pipeline functions include pixel-level calibration, simple aperture photometry and artifact mitigation. This third step of artifact removal will always be a subjective process. An archive user can either work with the default pipeline correction to be of suitable quality to enable their scientific objectives or choose to perform artifact removal themselves, starting from either the calibrated pixels or aperture photometry.

Up: PyKE Primer Next: Kepler and Data Resources