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Published March 2020 | Accepted Version + Published
Journal Article Open

A Sub-Neptune-sized Planet Transiting the M2.5 Dwarf G 9-40: Validation with the Habitable-zone Planet Finder

Abstract

We validate the discovery of a 2-Earth-radii sub-Neptune-sized planet around the nearby high-proper-motion M2.5 dwarf G 9-40 (EPIC 212048748), using high-precision, near-infrared (NIR) radial velocity (RV) observations with the Habitable-zone Planet Finder (HPF), precision diffuser-assisted ground-based photometry with a custom narrowband photometric filter, and adaptive optics imaging. At a distance of d = 27.9 pc, G 9-40b is the second-closest transiting planet discovered by K2 to date. The planet's large transit depth (~3500 ppm), combined with the proximity and brightness of the host star at NIR wavelengths (J = 10, K = 9.2), makes G 9-40b one of the most favorable sub-Neptune-sized planets orbiting an M dwarf for transmission spectroscopy with James Webb Space Telescope, ARIEL, and the upcoming Extremely Large Telescopes. The star is relatively inactive with a rotation period of ~29 days determined from the K2 photometry. To estimate spectroscopic stellar parameters, we describe our implementation of an empirical spectral-matching algorithm using the high-resolution NIR HPF spectra. Using this algorithm, we obtain an effective temperature of T_(eff) = 3404±73K, and metallicity of [Fe/H] = −0.08±0.13. Our RVs, when coupled with the orbital parameters derived from the transit photometry, exclude planet masses above 11.7M⊕ with 99.7% confidence assuming a circular orbit. From its radius, we predict a mass of M = 5.0^(+3.8)_(−1.9) M⊕ and an RV semiamplitude of K = 4.1^(+3.1)_(−1.6) ms⁻¹, making its mass measurable with current RV facilities. We urge further RV follow-up observations to precisely measure its mass, to enable precise transmission spectroscopic measurements in the future.

Additional Information

© 2020 The American Astronomical Society. Received 2019 July 8; revised 2019 October 29; accepted 2019 November 29; published 2020 February 12. We thank the anonymous referee for a thoughtful reading of the manuscript and for useful suggestions and comments that made for a clearer manuscript. This work was partially supported by funding from the Center for Exoplanets and Habitable Worlds. The Center for Exoplanets and Habitable Worlds is supported by the Pennsylvania State University, the Eberly College of Science, and the Pennsylvania Space Grant Consortium. This work was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program through grants NNX16AO28H and 80NSSC18K1114. We acknowledge support from NSF grants AST-1006676, AST-1126413, AST-1310885, AST-1517592, AST-1310875, the NASA Astrobiology Institute (NAI; NNA09DA76A), and PSARC in our pursuit of precision radial velocities in the NIR. Computations for this research were performed on the Pennsylvania State University's Institute for CyberScience Advanced CyberInfrastructure (ICS-ACI). We acknowledge support from the Heising-Simons Foundation via grant 2017-0494. These results are based on observations obtained with the Habitable-zone Planet Finder Spectrograph on the Hobby–Eberly Telescope. We thank the resident astronomers and telescope operators at the HET for the skillful execution of our observations with HPF. The Hobby–Eberly Telescope is a joint project of the University of Texas at Austin, the Pennsylvania State University, Ludwig-Maximilians-Universität Múnchen, and Georg-August Universität Gottingen. The HET is named in honor of its principal benefactors, William P. Hobby and Robert E. Eberly. The HET collaboration acknowledges the support and resources from the Texas Advanced Computing Center. These results are based on observations obtained with the 3 m Shane Telescope at Lick Observatory. The authors thank the Shane telescope operators, AO operators, and laser operators for their assistance in obtaining these data. These results are based on observations obtained with the Apache Point Observatory 3.5 m telescope, which is owned and operated by the Astrophysical Research Consortium. We wish to thank the APO 3.5 m telescope operators for their assistance in obtaining these data. This paper includes data collected by the Kepler telescope. The Kepler and K2 data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). The Space Telescope Science Institute is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non-HST data is provided by the NASA Office of Space Science via grant NNX09AF08G and by other grants and contracts. Funding for the K2 Mission is provided by the NASA Science Mission directorate. This research 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 has made use of the VALD database, operated at Uppsala University, the Institute of Astronomy RAS in Moscow, and the University of Vienna. 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. Facilities: K2 - , Gaia - , ARCTIC/ARC 3.5 m - , ShaneAO/Lick 3 m - , HPF/HET 10 m. - Software: AstroImageJ (Collins et al. 2017), astroplan (Morris et al. 2018), astropy (Astropy Collaboration et al. 2013), astroquery (Ginsburg et al. 2018), barycorrpy (Kanodia & Wright 2018), batman (Kreidberg 2015), corner.py (Foreman-Mackey 2016), celerite (Foreman-Mackey et al. 2017), emcee (Foreman-Mackey et al. 2013), everest (Luger et al. 2018), EXOFASTv2 (Eastman 2017), GNU parallel (Tange 2015), iDiffuse (Stefansson et al. 2018b), Jupyter (Kluyver et al. 2016), juliet (Espinoza et al. 2019), matplotlib (Hunter 2007), numpy (Van Der Walt et al. 2011), MC3 (Cubillos et al. 2017), MRExo (Kanodia et al. 2019), pandas (McKinney 2010), pyde (Parviainen 2016), radvel (Fulton et al. 2018), SERVAL (Zechmeister et al. 2018), statsmodels (Seabold et al. 2017), telfit (Gullikson et al. 2014), VESPA (Morton 2012, 2015).

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Additional details

Created:
August 22, 2023
Modified:
October 19, 2023