With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systema
tic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of reasonable robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.
The Kepler Mission relies on precise differential photometry to detect the 80 parts per million (ppm) signal from an Earth-Sun equivalent transit. Such precision requires superb instrument stability on time scales up to ~2 days and systematic error r
emoval to better than 20 ppm. To this end, the spacecraft and photometer underwent 67 days of commissioning, which included several data sets taken to characterize the photometer performance. Because Kepler has no shutter, we took a series of dark images prior to the dust cover ejection, from which we measured the bias levels, dark current, and read noise. These basic detector properties are essentially unchanged from ground-based tests, indicating that the photometer is working as expected. Several image artifacts have proven more complex than when observed during ground testing, as a result of their interactions with starlight and the greater thermal stability in flight, which causes the temperature-dependent artifact variations to be on the timescales of transits. Because of Keplers unprecedented sensitivity and stability, we have also seen several unexpected systematics that affect photometric precision. We are using the first 43 days of science data to characterize these effects and to develop detection and mitigation methods that will be implemented in the calibration pipeline. Based on early testing, we expect to attain Keplers planned photometric precision over 80%-90% of the field of view.
