Published February 15, 2018 | Version Version 1.0.0
Dataset Open

275 Candidates and 149 Validated Planets Orbiting Bright Stars in K2 Campaigns 0-10

  • 1. DTU Space, National Space Institute, Technical University of Denmark; Centre for Star and Planet Formation, Natural History Museum of Denmark & Niels Bohr Institute, University of Copenhagen; Harvard-Smithsonian Center for Astrophysics
  • 2. Harvard-Smithsonian Center for Astrophysics; Department of Astronomy, University of Texas at Austin
  • 3. Harvard-Smithsonian Center for Astrophysics
  • 4. Department of Astrophysical Sciences, Princeton University
  • 5. DTU Space, National Space Institute, Technical University of Denmark; Centre for Star and Planet Formation, Natural History Museum of Denmark & Niels Bohr Institute, University of Copenhagen
  • 6. Astronomy Department, University of California, Berkeley; Division of Geological & Planetary Sciences, California Institute of Technology
  • 7. NASA Exoplanet Science Institute, California Institute of Technology
  • 8. Department of Physics and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology
  • 9. National Optical Astronomy Observatory
  • 10. Department of Astronomy and Astrophysics, University of California, Santa Cruz
  • 11. Astronomy Department, University of California, Berkeley
  • 12. Department of Physics, Southern Connecticut State University
  • 13. Cahill Center for Astrophysics, California Institute of Technology
  • 14. Space Science and Astrobiology Division, NASA Ames Research Center
  • 15. Department of Astronomy, The University of Tokyo
  • 16. Infrared Processing and Analysis Center, California Institute of Technology
  • 17. NASA Goddard Space Flight Center
  • 18. Cahill Center for Astrophysics, California Institute of Technology; Institute for Astronomy, University of Hawai'i at Mānoa
  • 19. Carnegie Observatories

Description

This dataset contains transit model posterior distributions and validation analyses for the 275 exoplanet candidates (in 233 systems) analyzed in Mayo et al. (2018), titled "275 Candidates and 149 Validated Planets Orbiting Bright Stars in K2 Campaigns 0-10".

The dataset takes the form of 233 compressed directories each corresponding to an exoplanet system and titled after its EPIC ID. Within a given directory there are two numpy pickles named EPICXXXXXXXXX_chains.npy and EPICXXXXXXXXX_lnlikes.npy (where XXXXXXXXX is the 9 digit EPIC number) as well as n subdirectories, where n is the number of planet candidates in the system.

The EPICXXXXXXXXX_chains.npy pickle is a representative sample of the posterior distribution of the transit model for a given exoplanet system. The pickle is a numpy array of size (j,k,l), where j is the number of walkers in the Markov chain Monte Carlo ensemble simulation that sampled the posterior distribution (note: we chose to fix j = 2*l), k is the number of walker steps reported in this dataset (the full posteriors were thinned down to between 750 and 10,000 steps), and l is the number of parameters in the transit model for the exoplanet system. The EPICXXXXXXXXX_lnlikes.npy pickle contains the associated ln(likelihood) values for each walker step in the previously described pickle. This pickle is a numpy array of size (j,k) where j and k are defined as above.

The number of parameters will always be of the form 4 + 5*n, where n is again the number of planets in the systems. The first four parameters in the pickle are a baseline offset parameter for the normalized flux, a noise parameter to take the place of flux error bars, and two quadratic limb darkening parameters q1 and q2 based on Kipping et al. (2013). The next five parameters (and each subsequent set of five parameters in multi-candidate systems) refer to the reference epoch (a mid-transit time in BJD - 2454833), the period (in days), log10(Rp/R*), the transit duration (TIV-TI in days), and the impact parameter. It should be noted that there is no consistent ordering of the planets in the posterior samples (for example, in a three planet system parameters 5-9 may refer to planet b, planet c, or planet d). Therefore, planetary periods should be used as reference to identify candidates. All parameters and the nature of the transit model are described in detail in Mayo et al. (2018).

Each subdirectory contains the input and output of the validation analysis conducted via the VESPA validation package (Morton 2012, 2015). For additional details please refer to the relevant citations or the VESPA github repository. Each subdirectory is named after the appropriate candidate listed in Mayo et al. (2018; specifically Tables 5 and 7).

Notes

Funding, grants, and additional support for this research are listed in the acknowledgments section of Mayo et al. (2018).

Files

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md5:403fa5129b5b8bba461c2fea995ad36e
117.2 MB Download
md5:6df99ad8572654cb47bbedf052b64715
259.7 MB Download
md5:951fefb4d8bc53e4165b41e898a8c29a
116.7 MB Download
md5:784f30b7a59940fee8b9bd6d305db8da
119.0 MB Download
md5:486de4c56ae2f43eb272b3e2fcb91310
125.1 MB Download
md5:6b01f2353569489374d9bbd427e6edc7
119.5 MB Download
md5:464caf9037021347551a07107aa59b61
70.5 MB Download
md5:72071685cefdf88b70c4ed31dac14539
116.5 MB Download
md5:0d67f252b6d9de467b8106b1cd10d77e
122.5 MB Download

Additional details

Related works

Is supplement to
10.3847/1538-3881/aaadff (DOI)

References

  • Kipping, D. M. 2013, MNRAS, 435, 2152
  • Morton, T. D. 2012, ApJ, 761, 6
  • Morton, T. D. 2015, VESPA: False positive probabilities calculator, Astrophysics Source Code Library, ascl:1503.011