Measuring Transit Signal Recovery in the Kepler Pipeline II: Detection Efficiency as Calculated in One Year of Data

September 2015 • 2015ApJ...810...95C

Authors • Christiansen, Jessie L. • Clarke, Bruce D. • Burke, Christopher J. • Seader, Shawn • Jenkins, Jon M. • Twicken, Joseph D. • Catanzarite, Joseph D. • Smith, Jeffrey C. • Batalha, Natalie M. • Haas, Michael R. • Thompson, Susan E. • Campbell, Jennifer R. • Sabale, Anima • Kamal Uddin, AKM

Abstract • The Kepler planet sample can only be used to reconstruct the underlying planet occurrence rate if the detection efficiency of the Kepler pipeline is known; here we present the results of a second experiment aimed at characterizing this detection efficiency. We inject simulated transiting planet signals into the pixel data of ∼10,000 targets, spanning one year of observations, and process the pixels as normal. We compare the set of detections made by the pipeline with the expectation from the set of simulated planets, and construct a sensitivity curve of signal recovery as a function of the signal-to-noise of the simulated transit signal train. The sensitivity curve does not meet the hypothetical maximum detection efficiency; however, it is not as pessimistic as some of the published estimates of the detection efficiency. For the FGK stars in our sample, the sensitivity curve is well fit by a gamma function with the coefficients a = 4.35 and b = 1.05. We also find that the pipeline algorithms recover the depths and periods of the injected signals with very high fidelity, especially for periods longer than 10 days. We perform a simplified occurrence rate calculation using the measured detection efficiency compared to previous assumptions of the detection efficiency found in the literature to demonstrate the systematic error introduced into the resulting occurrence rates. The discrepancies in the calculated occurrence rates may go some way toward reconciling some of the inconsistencies found in the literature.


IPAC Authors


Jessie Christiansen

Associate Scientist