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The California Kepler Survey VII. Precise Planet Radii Leveraging Gaia DR2 Reveal the Stellar Mass Dependence of the Planet Radius Gap

Fulton, Benjamin J. and Petigura, Erik A. (2018) The California Kepler Survey VII. Precise Planet Radii Leveraging Gaia DR2 Reveal the Stellar Mass Dependence of the Planet Radius Gap. Astronomical Journal, 156 (6). Art. No. 264. ISSN 1538-3881. http://resolver.caltech.edu/CaltechAUTHORS:20180815-103847335

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Abstract

The distribution of planet sizes encodes details of planet formation and evolution. We present the most precise planet size distribution to date based on Gaia parallaxes, Kepler photometry, and spectroscopic temperatures from the California-Kepler Survey. Previously, we measured stellar radii to 11% precision using high-resolution spectroscopy; by adding Gaia astrometry, the errors are now 3%. Planet radius measurements are, in turn, improved to 5% precision. With a catalog of ~1000 planets with precise properties, we probed in fine detail the gap in the planet size distribution that separates two classes of small planets, rocky super-Earths and gas-dominated sub-Neptunes. Our previous study and others suggested that the gap may be observationally under-resolved and inherently flat-bottomed, with a band of forbidden planet sizes. Analysis based on our new catalog refutes this; the gap is partially filled in. Two other important factors that sculpt the distribution are a planet's orbital distance and its host-star mass, both of which are related to a planet's X-ray/UV irradiation history. For lower-mass stars, the bimodal planet distribution shifts to smaller sizes, consistent with smaller stars producing smaller planet cores. Details of the size distribution including the extent of the "sub-Neptune desert" and the width and slope of the gap support the view that photoevaporation of low-density atmospheres is the dominant evolutionary determinant of the planet size distribution.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3847/1538-3881/aae828DOIArticle
https://arxiv.org/abs/1805.01453arXivDiscussion Paper
ORCID:
AuthorORCID
Fulton, Benjamin J.0000-0003-3504-5316
Petigura, Erik A.0000-0003-0967-2893
Additional Information:© 2018 The American Astronomical Society. Received 2018 May 4; revised 2018 September 6; accepted 2018 October 9; published 2018 November 14. We thank the Kepler and Gaia teams for years of work making these precious data sets possible. We are grateful for Andrew Howard's guidance and comments on our manuscript. We thank Eddie Schlafly and Gregory Green for guidance regarding the treatment of dust extinction. We thank Alberto Krone-Martins for discussions regarding the Gaia mission and its data products. Daniel Huber kindly assisted with the isoclassify package. We thank D. Hsu and E. Ford for help using their SysSym code. E.A.P. acknowledges support from Hubble Fellowship grant HST-HF2-51365.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc. for NASA under contract NAS 5-26555. This research has made use of NASA's Astrophysics Data System. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Finally, the authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has long had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. Facilities: Keck:I (HIRES) - , Kepler - , Gaia. - Software: All code used in this paper is available at https://github.com/California-Planet-Search/cksgaia/. We made use of the following publicly available Python modules: astropy (Astropy Collaboration et al. 2013), isoclassify (Huber et al. 2017), lmfit (Newville et al. 2014), matplotlib (Hunter 2007), numpy/scipy (van der Walt et al. 2011), and pandas (McKinney 2010).
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
NASA Hubble FellowshipHST-HF2-51365.001-A
NASANAS 5-26555
Gaia Multilateral AgreementUNSPECIFIED
Subject Keywords:planetary systems
Record Number:CaltechAUTHORS:20180815-103847335
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180815-103847335
Official Citation:Benjamin J. Fulton and Erik A. Petigura 2018 AJ 156 264
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:88824
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:15 Aug 2018 17:54
Last Modified:14 Nov 2018 22:53

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