TY - JOUR
T1 - Architectures of exoplanetary systems - I. A clustered forward model for exoplanetary systems around Kepler's FGK stars
AU - He, Matthias Y.
AU - Ford, Eric B.
AU - Ragozzine, Darin
N1 - Funding Information:
We thank the entire Kepler team for years of work leading to a successful mission and data products critical to this study. We acknowledge many valuable contributions with members of the Kepler Science Team's working groups on multiple body systems, transit timing variations, and completeness working groups. We thank Keir Ashby, Danley Hsu, Neal Munson, Shane Marcus, and Robert Morehead for contributions to the broader SysSim project. We thank Derek Bingham, Earl Lawrence, Ilya Mandell, Oded Aahronson, Ben Bar-Oh, Dan Fabrycky, Jack Lissauer, Gijs Mulders, Aviv Ofir, and Jason Rowe for useful conversations. We thank Rebekah Dawson for reading preliminary drafts of this paper and providing detailed suggestions. MYH acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), funding reference number PGSD3-516712-2018. EBF and DR acknowledge support from NASA Origins of Solar Systems grant # NNX14AI76G and Exoplanet Research Program grant # NNX15AE21. EBF acknowledges support from NASA Kepler Participating Scientist Program Cycle II grant # NNX14AN76G. MYH and EBF acknowledge support from the Penn State Eberly College of Science and Department of Astronomy & Astrophysics, the Center for Exoplanets and Habitable Worlds, and the Center for Astrostatistics. EBF acknowledges support and collaborative scholarly discussions during residency at the Research Group on Big Data and Planets at the Israel Institute for Advanced Studies. The citations in this paper have made use of NASA's Astrophysics Data System Bibliographic Services. This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This work made use of the stellar catalogue from Hsu et al. (2019) and thus indirectly the gaiakepler.fun crossmatch data base created by Megan Bedell. Several figures in this manuscript were generated using the corner.py package (Foreman-Mackey 2016). We acknowledge the Institute for CyberScience (http://ics.psu.edu/) at The Pennsylvania State University, including the CyberLAMP cluster supported by NSF grant MRI-1626251, for providing advanced computing resources and services that have contributed to the research results reported in this paper. This study benefited from the 2013 SAMSI workshop on Modern Statistical and Computational Methods for Analysis of Kepler Data, the 2016/2017 Program on Statistical, Mathematical and Computational Methods for Astronomy, and their associated working groups. This material was based upon work partially supported by the National Science Foundation under Grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute (SAMSI). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Funding Information:
We thank the entire Kepler team for years of work leading to a successful mission and data products critical to this study. We acknowledge many valuable contributions with members of the Kepler Science Team’s working groups on multiple body systems, transit timing variations, and completeness working groups. We thank Keir Ashby, Danley Hsu, Neal Munson, Shane Marcus, and Robert Morehead for contributions to the broader SysSim project. We thank Derek Bingham, Earl Lawrence, Ilya Mandell, Oded Aahronson, Ben Bar-Oh, Dan Fabrycky, Jack Lissauer, Gijs Mulders, Aviv Ofir, and Jason Rowe for useful conversations. We thank Rebekah Dawson for reading preliminary drafts of this paper and providing detailed suggestions. MYH acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), funding reference number PGSD3-516712-2018. EBF and DR acknowledge support from NASA Origins of Solar Systems grant # NNX14AI76G and Exoplanet Research Program grant # NNX15AE21. EBF acknowledges support from NASA Kepler Participating Scientist Program Cycle II grant # NNX14AN76G. MYH and EBF acknowledge support from the Penn State Eberly College of Science and Department of Astronomy & Astrophysics, the Center for Exoplanets and Habitable Worlds, and the Center for Astrostatistics. EBF acknowledges support and collaborative scholarly discussions during residency at the Research Group on Big Data and Planets at the Israel Institute for Advanced Studies. The citations in this paper have made use of NASA’s Astrophysics Data System Bibliographic Services. This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program. This work made use of the stellar catalogue from Hsu et al. (2019) and thus indirectly the gaia-kepler.fun crossmatch data base created by Megan Bedell. Several figures in this manuscript were generated using the corner.py package (Foreman-Mackey 2016). We acknowledge the Institute for CyberScience (http://ics.psu.edu/) at The Pennsylvania State University, including the CyberLAMP cluster supported by NSF grant MRI-1626251, for providing advanced computing resources and services that have contributed to the research results reported in this paper. This study benefited from the 2013 SAMSI workshop on Modern Statistical and Computational Methods for Analysis of Kepler Data, the 2016/2017 Program on Statistical, Mathematical and Computational Methods for Astronomy, and their associated working groups. This material was based upon work partially supported by the National Science Foundation under Grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute (SAMSI). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Observations of exoplanetary systems provide clues about the intrinsic distribution of planetary systems, their architectures, and how they formed. We develop a forward modelling framework for generating populations of planetary systems and 'observed' catalogues by simulating the Kepler detection pipeline (SysSim). We compare our simulated catalogues to the Kepler DR25 catalogue of planet candidates, updated to include revised stellar radii from Gaia DR2. We constrain our models based on the observed 1D marginal distributions of orbital periods, period ratios, transit depths, transit depth ratios, transit durations, transit duration ratios, and transit multiplicities. Models assuming planets with independent periods and sizes do not adequately account for the properties of the multiplanet systems. Instead, a clustered point process model for exoplanet periods and sizes provides a significantly better description of the Kepler population, particularly the observed multiplicity and period ratio distributions. We find that 0.56+−001815 of FGK stars have at least one planet larger than 0.5R⊕ between 3 and 300 d. Most of these planetary systems (∼ 98 per cent) consist of one or two clusters with a median of three planets per cluster. We find that the Kepler dichotomy is evidence for a population of highly inclined planetary systems and is unlikely to be solely due to a population of intrinsically single planet systems. We provide a large ensemble of simulated physical and observed catalogues of planetary systems from our models, as well as publicly available code for generating similar catalogues given user-defined parameters.
AB - Observations of exoplanetary systems provide clues about the intrinsic distribution of planetary systems, their architectures, and how they formed. We develop a forward modelling framework for generating populations of planetary systems and 'observed' catalogues by simulating the Kepler detection pipeline (SysSim). We compare our simulated catalogues to the Kepler DR25 catalogue of planet candidates, updated to include revised stellar radii from Gaia DR2. We constrain our models based on the observed 1D marginal distributions of orbital periods, period ratios, transit depths, transit depth ratios, transit durations, transit duration ratios, and transit multiplicities. Models assuming planets with independent periods and sizes do not adequately account for the properties of the multiplanet systems. Instead, a clustered point process model for exoplanet periods and sizes provides a significantly better description of the Kepler population, particularly the observed multiplicity and period ratio distributions. We find that 0.56+−001815 of FGK stars have at least one planet larger than 0.5R⊕ between 3 and 300 d. Most of these planetary systems (∼ 98 per cent) consist of one or two clusters with a median of three planets per cluster. We find that the Kepler dichotomy is evidence for a population of highly inclined planetary systems and is unlikely to be solely due to a population of intrinsically single planet systems. We provide a large ensemble of simulated physical and observed catalogues of planetary systems from our models, as well as publicly available code for generating similar catalogues given user-defined parameters.
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U2 - 10.1093/mnras/stz2869
DO - 10.1093/mnras/stz2869
M3 - Article
AN - SCOPUS:85077587144
SN - 0035-8711
VL - 490
SP - 4575
EP - 4605
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
IS - 4
ER -