Jon Jenkins, Affiliation: SETI Institute/NASA Ames Research Center Planetary Detection: The Kepler Mission The Kepler telescope was launched into orbit in March 2009 to determine the frequency of Earth-sized planets transiting their Sun-like host stars in the habitable zone -- that range of orbital distances for which liquid water would pool on the surface of a terrestrial planet such as Earth or Mars. This daunting task demands an instrument capable of measuring the light output from each of over 150,000 stars over a 115 square degree field of view simultaneously at an unprecedented photometric precision of 20 ppm on 6.5-hour intervals. Kepler is opening up a new vista in astronomy and astrophysics and is operating in a new regime where the instrumental signatures compete with the miniscule signatures of terrestrial planets transiting their host stars. The dynamic range of the intrinsic stellar variability observed in the light curves is breathtaking: RR Lyrae stars explosively oscillate with periods of approximately 0.5 days, doubling their brightness over a few hours. Some flare stars double their brightness on much shorter time scales at unpredictable intervals. At the same time, some stars exhibit quasi-coherent oscillations with amplitudes of 50 ppm that can be seen by eye in the raw flux time series. The richness of Kepler's data lies in the huge dynamic range for the variations in intensity >10^4 and the large dynamic range of time scales probed by the data, from a few minutes to weeks, months, and ultimately, to years. Kepler is an audacious mission that places rigorous demands on the science pipeline used to process the ever-accumulating, large amount of data and to identify and characterize the minute planetary signatures hiding in the data haystack. We give an overview of the Science pipeline that reduces the pixel data to obtain flux time series and detect and characterize planetary transit signatures. In particular, we detail the adaptive, wavelet-based transit detector that performs the automated search through each light curve for transit signatures of Earth-sized planets. We describe a Bayesian Maximum A Posteriori (MAP) estimation approach under development to improve our ability to identify and remove instrumental signatures from the light curves that minimizes any distortion of astrophysical signals in the data and prevents the introduction of additional noise that may mask small, transit features. This approach leverages the availability of thousands of stellar targets on each CCD detector in order to construct an implicit forward model for the systematic error terms identified in the data as a whole. The Kepler Mission will not be the last spaceborne astrophysics mission to scan the heavens for planetary abodes. Several transit survey missions have been proposed to NASA and to ESA and some are under development. Clearly, these future missions can benefit from the lessons learned by Kepler and will face many of the same challenges that in some cases will be more difficult to solve given the significantly larger volume of data to be collected on a far greater number of stars than Kepler has had to deal with. Given the intense interest in exoplanets by the public and by the astronomical community, the future for exoplanet science appears to just be dawning with the initial success of the Kepler Mission.