TOI-150: A transiting hot Jupiter in the TESS southern CVZ

TL;DR

This paper reports the discovery and confirmation of a hot Jupiter exoplanet orbiting a star in the TESS southern CVZ, using combined space-based and ground-based observations, highlighting the utility of large spectroscopic surveys in exoplanet confirmation.

Contribution

First confirmation of a hot Jupiter in TESS southern CVZ using APOGEE-2 and other ground-based data, demonstrating the effectiveness of large spectroscopic surveys for exoplanet detection.

Findings

Confirmed the planetary nature of TOI-150.01 with radial velocity data.

Demonstrated the capability of APOGEE-2 to confirm giant exoplanets.

Identified potential for additional planets through continued TESS monitoring.

Abstract

We report the detection of a hot Jupiter ($M_{p}=1.75_{-0.17}^{+0.14}\ M_{J}$, $R_{p}=1.38\pm0.04\ R_{J}$) orbiting a middle-aged star ($\log g=4.152^{+0.030}_{-0.043}$) in the Transiting Exoplanet Survey Satellite (TESS) southern continuous viewing zone ($\beta=-79.59^{\circ}$). We confirm the planetary nature of the candidate TOI-150.01 using radial velocity observations from the APOGEE-2 South spectrograph and the Carnegie Planet Finder Spectrograph, ground-based photometric observations from the robotic Three-hundred MilliMeter Telescope at Las Campanas Observatory, and Gaia distance estimates. Large-scale spectroscopic surveys, such as APOGEE/APOGEE-2, now have sufficient radial velocity precision to directly confirm the signature of giant exoplanets, making such data sets valuable tools in the TESS era. Continual monitoring of TOI-150 by TESS can reveal additional planets and subsequent observations can provide insights into planetary system architectures involving a hot Jupiter around a star about halfway through its main-sequence life.

Tables

Table 1. Table 1: Spectroscopic Observations

BJD${}_{}{}^a{}_{\text{TDB}}{}^{}$	RV	$1\sigma$	S/Nb
	(m s-1)	(m s-1)	(pixel-1)
APOGEE-2S:
2458146.705799	4666	77	168
2458148.693524	5073	80	146
PFSc:
2458476.801377	151.15	2.27	52
2458479.785058	$-176.59$	2.25	49
2458501.708368	25.43	2.46	43

Table 2. Table 2: Parameters for the TOI-150 System

Parameter	Units	Value
Stellar Priors:
Effective Temperaturea	$T_e$ (K)	$6029\pm 110$
Surface Gravitya	$\log \left(g\right)$ (cgs)	$4.15\pm 0.12$
Metallicitya	[Fe/H]	$0.25\pm 0.09$
Maximum Visual Extinction	$A_{V,max}$	$0.556$
Distance	(pc)	$336\pm 2$
Derived Model-Dependent Stellar Parametersb:
Mass	$M_{\ast }$ ($M_{\odot }$)	${1.249}_{-0.115}^{+0.069}$
Radius	$R_{\ast }$ ($R_{\odot }$)	${1.551}_{-0.025}^{+0.024}$
Density	${\rho }_{\ast }$ (g ${\mathrm{cm}}^{-3}$)	${0.470}_{-0.045}^{+0.040}$
Surface Gravity	$\log \left(g\right)$ (cgs)	${4.152}_{-0.043}^{+0.030}$
Effective Temperature	$T_e$ (K)	${6003}_{-98}^{+104}$
Metallicity	[Fe/H]	${0.235}_{-0.084}^{+0.083}$
Age	(Gyr)	${4.3}_{-1.3}^{+2.5}$
Parallax	(mas)	$2.974\pm 0.017$
Visual Extinction	$A_V$	${0.188}_{-0.084}^{+0.082}$
Derived Photometric Parameters:		$TESS$	Cousins $I_C$
Linear Limb-darkening Coefficient	$u_1$	${0.21}_{-0.14}^{+0.20}$	${0.41}_{-0.20}^{+0.19}$
Quadratic Limb-darkening Coefficient	$u_2$	${0.39}_{-0.32}^{+0.27}$	$-{0.05}_{-0.17}^{+0.27}$
Dilution Factorc	$D$	$0.49\pm 0.03$	$\cdots$
Derived Orbital Parameters:
Orbital Period	$P$ (days)	${5.857342}_{-0.000066}^{+0.000065}$
Semi-major Axis	$a$ (au)	${0.0583}_{-0.0018}^{+0.0013}$
Semi-amplitude Velocity	$K$ (m $s^{-1}$)	${169.58}_{-12.38}^{+11.90}$
Mass Ratio	$q$	${0.00133}_{-0.00018}^{+0.00013}$
Derived RV Parameters:		APOGEE-2S	PFS
Systemic Velocityd	$\gamma$ (m $s^{-1}$)	${4863}_{-86}^{+85}$	$-{7.73}_{-6.93}^{+6.74}$
Derived Transit Parameters:
Time of Conjunction	$T_C$ (BJDTDB)	${2458326.279039}_{-0.000984}^{+0.001024}$
Scaled Radius	$R_p/R_{\ast }$	${0.0912}_{-0.0023}^{+0.0022}$
Scaled Semi-major Axis	$a/R_{\ast }$	${8.08}_{-0.22}^{+0.13}$
Orbital Inclination	$i$ (degrees)	${88.98}_{-1.01}^{+0.70}$
Transit Impact Parameter	$b$	${0.14}_{-0.10}^{+0.14}$
Transit Duration	$T_{14}$ (hours)	$5.99\pm 0.07$
Derived Planetary Parameters:
Mass	$M_p$ ($M_J$)	${1.75}_{-0.17}^{+0.14}$
Radius	$R_p$ ($R_J$)	$1.38\pm 0.04$
Density	${\rho }_p$ (g ${\mathrm{cm}}^{-3}$)	${0.83}_{-0.11}^{+0.10}$
Surface Gravity	$\log \left(g_p\right)$ (cgs)	${3.215}_{-0.045}^{+0.041}$
Equilibrium Temperaturee	$T_{eq}$ (K)	${1493}_{-32}^{+29}$

Full text

planetary systems — techniques: spectroscopic — techniques: photometric

††facilities: Du Pont (APOGEE-2S), Gaia, Magellan:Clay (PFS), TESS††software: AstroImageJ, astropy, batman, EXOFASTv2, juliet, MultiNest, radvel, SpecMatch-Emp

1 Introduction

The Transiting Exoplanet Survey Satellite (TESS, Ricker et al., 2015) is an ongoing mission designed to survey the entire sky and discover transiting exoplanets around bright, nearby stars. These exoplanets are ideal targets for high-precision spectroscopic observations to provide mass estimates, and for future space- and ground-based atmospheric characterization. Approximately 1000 planets are expected to be detected in the TESS full-frame images around relatively bright stars with TESS magnitudes ($T$) $\sim 11$ (e.g., Barclay et al., 2018). TESS divides the sky into 26 sectors rotating about the ecliptic poles and will observe stars within $\sim 12\arcdeg$ of the poles (the continuous viewing zone, CVZ) for $\sim 351$ days.

In this Letter, we confirm the planetary nature of the candidate TOI-150.01 (TIC 271893367, 2MASS J07315176-7336220, Gaia DR2 5262709709389254528, $T=10.87$, $V=11.39$, $H=10.05$) using TESS photometry, ground-based photometric observations, Gaia DR2 distance estimates, and Doppler velocimetry from the Sloan Digital Sky Survey (SDSS)/APOGEE-2 South spectrograph and the Carnegie Planet Finder Spectrograph (PFS). This Letter is structured as follows. Section 2 presents the observational data and data processing. Section 3 discusses stellar contamination and constraints on binarity and stellar companions, and Section 4 describes our analysis and derivation of the system parameters. A discussion of our results is presented in Section 5.

2 Observations and Data Reduction

2.1 TESS Photometry

TOI-150 was observed by TESS in Sectors $1-4$ and has one planetary candidate, TOI-150.01, with a period of $\sim 5.85$ days derived from the “quick-look pipeline” developed by the MIT branch of the TESS Science Office (C. X. Huang et al. 2019, in preparation). The TESS full-frame image light curves were corrected for systematic trends using the difference imaging analysis toolset described by Oelkers & Stassun (2018). The corrected and extracted light curves are available222https://filtergraph.com/tess_ffi through the Filtergraph data visualization service (Burger et al., 2013), where the flux for each star is extracted using a fixed aperture radius of 3.5 pixels ($\sim 73.5^{\prime\prime}$) and sky annulus radii of 5-7 pixels ($105^{\prime\prime}-147^{\prime\prime}$). We use the “clean” photometry from Oelkers & Stassun (2019), where the light curve has been corrected for systematics using the median trend apparent in 100 other stars of comparable magnitude and located at least 10 TESS pixels ($\sim 210^{\prime\prime}$) from the star. Oelkers & Stassun (2019) warned that some residual variability common to those 100 stars may be injected into a target’s “clean” light curve. The “clean” light curve for TOI-150 exhibited some residual variability and was detrended using a Gaussian process as described in Cañas et al. (2019). There was no further processing of the photometry and no Gaussian process was employed when fitting the photometry and velocimetry.

2.2 TMMT Ground-based Photometry

We observed two transits of TOI-150.01 using the robotic Three-hundred MilliMeter Telescope (TMMT; Monson et al., 2017) at Las Campanas Observatory (LCO) on the nights of 2018 December 13 and 20. Both observations were performed slightly out of focus in the Cousins $I_{C}$ filter (Doi et al., 2010), resulting in a point spread function FWHM of $4\arcsec$. We obtained 221 and 200 frames for the December 13 and 20 observations, respectively, using an exposure time of 120s. In the 1x1 binning mode used, the detector has a 13s readout time between exposures, resulting in an effective cadence of 133s and an observing efficiency of 90%. The December 13 observations began at airmass 2.18, reached 1.40 at the meridian, and ended at airmass 1.48. For the December 20 observations, the corresponding airmasses are 1.96, 1.40, and 1.48.

We processed the photometry using AstroImageJ (Collins et al., 2017) following the procedures described in Stefansson et al. (2017). After experimenting with a number of different apertures, we adopted an object aperture radius of 10 pixels (11″), and inner and outer sky annulii of 14 pixels (17″) and 21 pixels (25″), respectively, for both nights. These values minimized the standard deviation in the residuals for each observation. Following Stefansson et al. (2017), we added the expected scintillation-noise errors to the photometric error (including photon, readout, dark, sky background, and digitization noise).

2.3 Spectroscopic Observations

TOI-150 was observed from the Carnegie Observatory’s LCO on 2018 January 28 and 30 as part of a systematic survey of the TESS southern CVZ carried out using the southern spectrograph of the APO Galaxy Evolution Experiment (APOGEE; Majewski et al., 2017; Zasowski et al., 2017). This survey was initiated as an APOGEE-2S external program led by Carnegie Observatories, which contributed data beyond the scope of the original galactic evolution goals of the SDSS-IV southern survey (Blanton et al., 2017). Both spectra of TOI-150 were obtained with the high-resolution ($R=\Delta\lambda/\lambda\sim 22,500$), near-infrared ($1.51-1.7$ $\,\mathrm{\mu m}$), multi-object APOGEE-2S spectrograph (Wilson et al., 2019) mounted on the Irénée du Pont 2.5 m telescope (Bowen & Vaughan, 1973). For each observation, the APOGEE data pipeline (Nidever et al., 2015) performs sky subtraction, telluric and barycentric correction, and wavelength and flux calibration. The radial velocities (RVs) were derived using a maximum-likelihood cross-correlation method with BT-Settl synthetic spectra (Allard et al., 2012) following the procedure described in Cañas et al. (2019).

\startlongtable

3 Stellar Companions to TOI-150

3.1 Sky-projected Stellar Companions

The large aperture radius ($73.5^{\prime\prime}$) used to process the TESS photometry ensures there will be flux contamination in the light curves. To investigate the background stars, we used Gaia DR2 (Gaia Collaboration et al., 2018) and searched a $10\times 10$ TESS pixel grid centered on TOI-150. The left panel of Figure 1 is an in-focus, seeing-limited image from TMMT overlaid with the $10\times 10$ TESS pixel grid and the stars identified in Gaia DR2, each shaded by the difference to the Gaia $G_{RP}$ magnitude of TOI-150. The right panel of Figure 1 is the $10\times 10$ TESS pixel grid for Sector 1, with all sources within three magnitudes of TOI-150. A total of 47 other stars reside in this region. The brightest stellar neighbor, TIC 271893376 ($T$ = 11.97), is inside the aperture used by Oelkers & Stassun (2019) at a sky-projected distance of $62.23^{\prime\prime}$. TIC 271893376 and all other stars identified by Gaia lie outside the aperture used to process the TMMT photometry.

3.2 Non-detection of Spectroscopic Companions within 1.31*′′* of TOI-150

In lieu of adaptive optics imaging for TOI-150, we use the APOGEE-2S spectra to search for light from secondary stars in the spectrum with the highest signal-to-noise ratio (S/N). The fiber core for APOGEE-2S has a radius of $1.31^{\prime\prime}$. We use the software binspec (El-Badry et al., 2018b, a) to search for the faint spectrum of a second star by modeling the observed stellar spectra as the sum of two input model spectra. The spectrum of the primary star, TOI-150, is fit with a neural network spectral model (Ting et al., 2018). The neural network employed by binspec was trained on the Kurucz stellar library (Kurucz, 1979) and is valid in the regime of $4200\,\mathrm{K}<T_{e}<7000\,\mathrm{K}$, $4.0<\log g<5.0$, and $−1<\,\mathrm{[Fe/H]}<0.5$ for slow rotating ($v_{macro}<45\,\mathrm{km\ s^{-1}}$) main-sequence stars. While binspec is designed to fit both single and binary spectra, it is limited to the detection of moderate-mass ratio binaries ($0.4\lesssim q\lesssim 0.85$). When adopting the model selection statistics and criterion from El-Badry et al. (2018b), there is no indication of a companion, as evidenced by comparison of a single-component fit to a binary component fit, which yields $\Delta\chi^{2}=9.15$ and $f_{imp}=2.2\times 10^{-5}$. The minimum case for binarity requires $\Delta\chi^{2}>300$ and $f_{imp}>0.225$.

4 System Parameters

4.1 Stellar Parameters

The APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP; García Pérez et al., 2016) provides spectroscopic stellar parameters for TOI-150. These parameters are derived from a composite APOGEE-2 spectrum, are empirically calibrated, and with the exception of the surface gravity, are determined to be quite reliable (see Holtzman et al., 2018). For TOI-150, ASPCAP provides $T_{e}=6088\pm 130$ K and $\,\mathrm{[Fe/H]}=0.16\pm 0.01$. The surface gravity was poorly constrained after calibration and the uncalibrated value is $\log g=4.47$.

As the processing of APOGEE-2S data is still in development, we derived an independent set of stellar parameters using the PFS iodine-free “template”. We employed the SpecMatch-Emp algorithm (Yee et al., 2017) to characterize the properties of TOI-150 by comparing the optical spectrum to a library of 404 high-resolution ($R\sim 55,000$), high quality ($\,\mathrm{S/N}>100$) Keck/HIRES stellar spectra that have well-determined properties. In brief, SpecMatch-Emp shifts the observed spectrum to the library wavelength scale, finds the best-matching library spectrum using $\chi^{2}$ minimization, and uses a linear combination of the five best-matching spectra to synthesize a composite spectrum. Following the examples provided by Yee et al. (2017), we compared the spectral order containing the Mg triplet line ($\sim 516-520\,\mathrm{nm}$) to the Keck/HIRES library. The derived parameters are $T_{e}=6029\pm 110$ K, $\log g=4.15\pm 0.12$, $\,\mathrm{[Fe/H]}=0.25\pm 0.09$. The calibrated ASPCAP values for $T_{e}$ and [Fe/H] are within the $1\sigma$ uncertainties from the respective SpecMatch-Emp values. To provide a self-consistent set of stellar parameters that include a reliable $\log g$ value, we adopt the SpecMatch-Emp derived parameters for further analysis of TOI-150.

4.2 System Parameters

We used the EXOFASTv2 analysis package (Eastman, 2017) to model the spectral energy distribution and derive the stellar parameters using MIST stellar models (Choi et al., 2016). We assumed Gaussian priors using the (i) 2MASS $JHK$ magnitudes (Skrutskie et al., 2006), (ii) SDSS $g^{\prime}r^{\prime}i^{\prime}$ and Johnson $BV$ magnitudes from the AAVSO Photometric All-Sky Survey (Henden et al., 2015), (iii) Tycho-2 $B_{T}V_{T}$ magnitudes (Høg et al., 2000), (iv) Wide-field Infrared Survey Explorer magnitudes (Wright et al., 2010), (v) the host star surface gravity, temperature and metallicity derived with SpecMatch-Emp, and (vii) the distance estimate from Bailer-Jones et al. (2018). We adopt a uniform prior for the maximum visual extinction from estimates of Galactic dust extinction by Schlafly & Finkbeiner (2011). The stellar priors and derived stellar parameters with their uncertainties are listed in Table 2. The reported values, derived using distance estimates from Bailer-Jones et al. (2018), are within the $1\sigma$ uncertainties of the values derived when adopting a Gaussian prior based on the distance from (i) the Gaia DR2 parallax, as corrected for a systematic offset, following Stassun & Torres (2018), or (ii) the Bayesian distance estimate for the Gaia RV stellar sample derived by Schönrich et al. (2019).

The juliet analysis package (Espinoza et al., 2018) was employed to jointly model the photometry and velocimetry. juliet utilizes publicly available tools to model the photometry (batman; Kreidberg, 2015) and velocimetry (radvel; Fulton et al., 2018) and performs the parameter estimation using the importance nest-sampling algorithm MultiNest (Feroz et al., 2013; Buchner et al., 2014). We validated the performance of our juliet implementation by performing an analysis on KOI-189 (Díaz et al., 2014). The resulting parameters were essentially identical to those published by Díaz et al. (2014) using the PASTIS planet-validation software. The photometric model is based on the analytical formalism of Mandel & Agol (2002) for a planetary transit assuming a quadratic limb-darkening law. The model is modified to include a dilution factor, $D$, which is the ratio of the out-of-transit flux of the target to that of the total flux from other stars within the photometric aperture. We fit a dilution factor for TESS photometry and use the ground-based TMMT observations, where the aperture excludes all detected Gaia stellar neighbors, to constrain the true transit depth of TOI-150.01.

The radial velocity model is a standard Keplerian model. The few spectroscopic observations of TOI-150 cannot constrain eccentricity and we adopt a circular orbit ($e=0$ and $\omega=90\arcdeg$) for TOI-150.01. The uncertainties from Table 1 are scaled such that the reduced chi-squared statistic, $\chi^{2}_{\nu}$, for each spectrograph is approximately the 50th percentile of the respective complementary cumulative distribution function. For a circular Keplerian orbit, the only degrees of freedom in our radial velocity model are a fraction of the semi-amplitude and the respective systemic velocity. We took a conservative approach and assumed the APOGEE-2N data only constrained $10\%$ of the semi-amplitude, $K$. With these assumptions, the uncertainties listed in Table 1 were inflated by $\sim 1.64$ and $\sim 7.61$ for APOGEE-2N and PFS, respectively, in the joint fit. We have inflated the radial velocity uncertainties such that the best fit agrees with a circular orbit and we note this overestimates the RV uncertainty if TOI-150.01 were on an eccentric orbit. Figure 2 presents the result of the fit to the photometry and velocimetry. Table 2 provides a summary of the stellar priors, together with the inferred system parameters and respective confidence intervals. The uncertainties from the model-dependent stellar parameters were analytically propagated when deriving $M_{p}$, $R_{p}$, $\rho_{p}$, $T_{eq}$, and $a$. \startlongtable

5 Discussion

The modeling reveals that TOI-150 is in the second half of its core-hydrogen burning phase, hosting a transiting hot Jupiter in the TESS southern CVZ. While the current data cannot constrain the eccentricity of the orbit, it reveals the mass and radius are consistent with $1.38\pm 0.04\,\mathrm{R_{J}}$ and $1.75_{-0.17}^{+0.14}\,\mathrm{M_{J}}$, respectively. Figure 3 compares TOI-150 to known gas-giant exoplanets and their host stars. It is slightly inflated compared to exoplanets of comparable mass, which may be a result of stellar irradiation by the host star.

5.1 Opportunities for Further Characterization

The APOGEE-2 and PFS RVs are consistent with the planetary nature of TOI-150.01 and constrain the orbital parameters. Subsequent high-precision spectroscopy will improve the precision of the orbital elements and the physical parameters of TOI-150.01. Additional spectra during transit would make it possible to constrain the apparent spin-orbit misalignment through analysis of the Rossiter-McLaughlin (RM) or reloaded RM effect (e.g., Gaudi & Winn, 2007; Cegla et al., 2016). Cross-correlation of the APOGEE-2S spectra with BT-Settl models reveals that TOI-150 is not a rapidly rotating star. When adopting a rotational velocity of $v\sin i\sim 2\,\mathrm{km\ s^{-1}}$, we estimate an RM effect amplitude of $\sim 16\,\mathrm{m\ s^{-1}}$. This is a value that can be detected using existing high-precision instruments.

TOI-150 will be observable for all 13 TESS Sectors in the southern ecliptic hemisphere. The long observational baseline will facilitate the search for additional planetary companions. While most known hot Jupiters have no detected close companions (e.g., Dawson & Johnson, 2018), a full year of TESS photometry allows for a robust search of transiting companions and transit timing variations. The positive detection of a small, planetary companion to a hot Jupiter from the Kepler mission (e.g., Kepler-730; Cañas et al., 2019) required a long temporal baseline. Detecting a comparable planet will be very difficult for most TESS targets closer to the ecliptic with a $\sim 27$ day observational baseline.

The overlap between the TESS and James Webb Space Telescope (JWST) CVZs also ensures TOI-150 will be observable for a large portion of each JWST cycle. The long TESS observational baseline will establish a precise ephemeris that is necessary for potential emission spectroscopy using JWST.

5.2 Implications of Large-scale Spectroscopic Surveys for TESS

A promising aspect of the TESS mission is that it will provide light curves for most of the sky that overlaps with existing, large-scale spectroscopic surveys, such as APOGEE-2. Troup et al. (2016) published 57 planetary candidates from previous APOGEE data and estimated the end of APOGEE-2 will have $\sim 1300$ substellar candidates orbiting different stellar populations and galactic environments. APOGEE-2 already has spectra for over 300,000 stars, most with $\geq 3$ observations, and has one northern and two southern programs observing the TESS CVZs. While the APOGEE-2 north and south spectrographs were designed for chemodynamics studies of the Milky Way, the precision is sufficient to detect giant exoplanets around bright stars (e.g., HD 114762b, as shown in Troup et al., 2016). The two APOGEE-2 observations of TOI-150 represent a $2\sigma$ detection of the hot Jupiter RV signal and were sufficient to exclude an eclipsing binary scenario and trigger subsequent PFS observations.

Once TESS begins observations in the northern ecliptic hemisphere, where there is more overlap with the bulk of APOGEE-2 data, it will be possible to effectively “precover” a TESS-detection for a hot Jupiter in APOGEE-2 velocimetry. While high-precision spectroscopy is still required to derive the most precise planetary mass, APOGEE-2 data can serve to (i) vet TESS candidates for eclipsing binaries (e.g., Fleming et al., 2015), (ii) provide spectroscopic parameters of the host star via ASPCAP (e.g., Wilson et al., 2018), and (iii) derive masses for giant planets when sufficient APOGEE observations are available. When TESS begins northern observations in late 2019, the planned 16th data release of SDSS (DR16) will provide a large, complementary data set for validating, and in some cases confirming, exoplanets around bright stars.

6 Acknowledgements

We thank the anonymous referee for a thoughtful reading of the manuscript and comments that improved the quality of this publication. C.I.C. and G.S. acknowledge support by NASA Headquarters under the NASA Earth and Space Science Fellowship Program through grants 80NSSC18K1114 and NNX16AO28H, respectively. C.I.C., C.F.B., and S.M. acknowledge support from NSF awards AST 1517592, 100667, 1126413, 1310885, N.D. acknowledges support from NFS award AST 1616684, and K.G.S acknowledges support from NASA XRP grant 17-XRP17 2-0024. S.W. thanks the Heising-Simons Foundation for their generous support. Support for this work was provided by NASA through Hubble Fellowship grants HST-HF2-51399.001 (awarded to J.K.T.) and #51386.01 (awarded to R.L.B.) by STScI, which is operated by the Association of Universities for Research in Astronomy, Inc., under contract NAS5-26555. D.A.G.H. acknowledges support from the State Research Agency (AEI) of the Spanish Ministry of Science, Innovation and Universities (MCIU) and the European Regional Development Fund (FEDER) under grant AYA-2017-88254-P. The research leading to these results has (partially) received funding from the European Research Council (ERC) under the EU’s Horizon 2020 research and innovation programme (grant agreement N∘670519: MAMSIE) and from the Fonds Wetenschappelijk Onderzoek - Vlaanderen under the grant agreement G0H5416N (ERC Opvangproject).

Part of this research was conducted using the Advanced CyberInfrastructure computational resources provided by The Institute for CyberScience at The Pennsylvania State University (http://ics.psu.edu), including the CyberLAMP cluster supported by NSF grant MRI-1626251.

Some of the data presented in this Letter were obtained from MAST. 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. 2MASS is a joint project of the University of Massachusetts and IPAC at Caltech, funded by NASA and the NSF. This Letter includes data collected by the TESS mission, which are publicly available from MAST. Funding for the TESS mission is provided by NASA’s Science Mission directorate. 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.

Funding for SDSS-IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.