Scaling K2. IV. A Uniform Planet Sample for Campaigns 1–8 and 10–18
Abstract
We provide the first full K2 transiting exoplanet sample, using photometry from Campaigns 1–8 and 10–18, derived through an entirely automated procedure. This homogeneous planet candidate catalog is crucial to perform a robust demographic analysis of transiting exoplanets with K2. We identify 747 unique planet candidates and 57 multiplanet systems. Of these candidates, 366 have not been previously identified, including one resonant multiplanet system and one system with two short-period gas giants. By automating the construction of this list, measurements of sample biases (completeness and reliability) can be quantified. We carried out a light-curve-level injection/recovery test of artificial transit signals and found a maximum completeness of 61%, a consequence of the significant detrending required for K2 data analysis. Through this operation we attained measurements of the detection efficiency as a function of signal strength, enabling future population analysis using this sample. We assessed the reliability of our planet sample by testing our vetting software EDI-Vetter against inverted transit-free light curves. We estimate that 91% of our planet candidates are real astrophysical signals, increasing up to 94% when limited to the FGKM dwarf stellar population. We also constrain the contamination rate from background eclipsing binaries to less than 5%. The presented catalog, along with the completeness and reliability measurements, enable robust exoplanet demographic studies to be carried out across the fields observed by the K2 mission for the first time.
Additional Information
© 2021. The American Astronomical Society. Received 2021 June 22; revised 2021 August 20; accepted 2021 August 31; published 2021 November 23. We thank the anonymous referee for the thoughtful feedback. This work made use of the gaia-kepler.fun cross-match database created by Megan Bedell. The simulations described here were performed on the UCLA Hoffman2 shared computing cluster and using the resources provided by the Bhaumik Institute. This research has made use of the NASA Exoplanet Archive and the Exoplanet Follow-up Observation Program website, which are operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This paper includes data collected by the Kepler mission and obtained from the MAST data archive at the Space Telescope Science Institute (STScI). Funding for the Kepler mission is provided by the NASA Science Mission Directorate. STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 526555. J.Z. acknowledges funding from NASA ADAP grant 443820HN21811. K.H.-U. and J.C. acknowledge funding from NASA ADAP grant 80NSSC18K0431. C.D. acknowleges funding from NASA ADAP grant 80NSSC18K0431 subaward S467134 as well as the David and Lucile Packard Foundation. Software: EVEREST (Luger et al. 2016, 2018), TERRA (Petigura et al. 2013), EDI-Vetter (Zink et al. 2020a), PyMC3 (Salvatier et al. 2015), Exoplanet (Foreman-Mackey et al. 2019), RoboVetter (Thompson et al. 2018), batman Kreidberg (2015), emcee (Foreman-Mackey et al. 2013).Attached Files
Published - Zink_2021_AJ_162_259.pdf
Accepted Version - 2109.02675.pdf
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Additional details
- Eprint ID
- 112224
- Resolver ID
- CaltechAUTHORS:20211203-235102087
- NASA/JPL/Caltech
- NAS 5-26555
- NASA
- 443820HN21811
- NASA
- 80NSSC18K0431
- NASA
- David and Lucile Packard Foundation
- Created
-
2021-12-06Created from EPrint's datestamp field
- Updated
-
2021-12-06Created from EPrint's last_modified field
- Caltech groups
- Infrared Processing and Analysis Center (IPAC)