# TOI-220 $b$: a warm sub-Neptune discovered by TESS††thanks: Based on
observations made with ESO Telescopes at the La Silla Observatory under
programs ID 1102.C-0923, 1102.C-0249, 0102.C-0584, 60.A.9700, and 60.A-9709.

S. Hoyer,1 D. Gandolfi,2 D. J. Armstrong,3,4 M. Deleuil,1 L. Acuña,1 J. R. de
Medeiros,5 E. Goffo,2 J. Lillo-Box,6 E. Delgado Mena,7,8 T. A. Lopez,1, A.
Santerne,1 S. Sousa,7,8 M. Fridlund,9,10 V. Adibekyan,7,8 K. A. Collins,11 L.
M. Serrano,2 P. Cortés-Zuleta,1 S. B. Howell,12 H. Deeg,13,14 A. Aguichine,1
O. Barragán,15 E. M. Bryant,3,4 B. L. Canto Martins,5 K. I. Collins,16 B. F.
Cooke,3,4 R. F. Díaz,17 M. Esposito,18 E. Furlan,18 S. Hojjatpanah,7,8 J.
Jackman,3,4 J. M. Jenkins,12 E. L. N. Jensen,20 D. W. Latham,9 I. C. Leão,5 R.
A. Matson,21 L. D. Nielsen,22 A. Osborn,3,4J. F. Otegi,22,23 F. Rodler,24 S.
Sabotta,18 N. J. Scott,12 S. Seager,25,26,27 C. Stockdale,28 P. A. Strøm,3,4
R. Vanderspek,25 V. Van Eylen,29 P. J. Wheatley,3,4 J. N. Winn,30 J. M.
Almenara,31 D. Barrado,6 S. C. C. Barros,7,8 D. Bayliss,3,4 F. Bouchy,22 P. T.
Boyd,32 J. Cabrera,33 W. D. Cochran,34 O. Demangeon,7,8 J. P. Doty,35 X.
Dumusque,22 P. Figueira,7,24 W. Fong,25 S. Grziwa,36 A. P. Hatzes18 P.
Kabáth,37 E. Knudstrup,38 J. Korth,36 J. H. Livingston,39 R. Luque,13,14 O.
Mousis,1 S. E. Mullally,40 H. P. Osborn,25,41 E. Pallé,13,14 C. M. Persson,10
S. Redfield,42 N. C. Santos,7,8 J. Smith,12,43 J. Šubjak,37 J. D.
Twicken,12,43 S. Udry22 D. A. Yahalomi11,44
The authors’ affiliations are shown in Appendix H Contact e-mail:
<EMAIL_ADDRESS>
(Last updated XX; in original form XX)

###### Abstract

In this paper we report the discovery of TOI-220 $b$, a new sub-Neptune
detected by the Transiting Exoplanet Survey Satellite (TESS) and confirmed by
radial velocity follow-up observations with the HARPS spectrograph. Based on
the combined analysis of TESS transit photometry and high precision radial
velocity measurements we estimate a planetary mass of 13.8 $\pm$ 1.0 M⊕ and
radius of 3.03 $\pm$ 0.15 R⊕, implying a bulk density of 2.73 $\pm$ 0.47
$\textrm{g\,cm}^{-3}$. TOI-220 $b$ orbits a relative bright (V=10.4) and old
(10.1$\pm$1.4 Gyr) K dwarf star with a period of $\sim$10.69 d. Thus, TOI-220
$b$ is a new warm sub-Neptunes with very precise mass and radius
determinations. A Bayesian analysis of the TOI-220 $b$ internal structure
indicates that due to the strong irradiation it receives, the low density of
this planet could be explained with a steam atmosphere in radiative-convective
equilibrium and a supercritical water layer on top of a differentiated
interior made of a silicate mantle and a small iron core.

###### keywords:

Planetary systems – Planets and satellites: fundamental parameters – Planets
and satellites: individual: TYC 8897-01263-1 – Stars: fundamental parameters –
Techniques: photometric – Techniques: radial velocities

††pubyear: 2020††pagerange: TOI-220 $b$: a warm sub-Neptune discovered by
TESS††thanks: Based on observations made with ESO Telescopes at the La Silla
Observatory under programs ID 1102.C-0923, 1102.C-0249, 0102.C-0584,
60.A.9700, and 60.A-9709.–H

##  1 Introduction

Launched in April 2018, the Transiting Exoplanet Survey Satellite (TESS) space
mission (Ricker et al., 2015) has discovered about 98 confirmed new exoplanets
and more than 2450 candidates111Source: NASA Exoplanet Archive (Akeson et al.,
2013), as of 20 January 2021.. Among all the confirmed exoplanets, one class
of particular interest are the small-sized planets (R $<$ 5 R⊕) orbiting
bright stars (V $<$ 11 mag) with periods shorter than 10 days. Within this
parameter space there is the so-called Neptunian desert (Szabó & Kiss, 2011;
Mazeh et al., 2016), which is a region that presents a significant paucity of
hot/highly irradiated planets with respect to the overall planet population.
This deficit could be seen as evidence of photoevaporation and/or tidal
disruptions (Owen & Lai, 2018) or of core-powered atmospheric mass loss
mechanism (Ginzburg et al., 2018; Gupta & Schlichting, 2019). Currently, of
all the known planets in the Neptunian desert only a very small number have
precisely measured masses (e.g. West et al., 2019; Armstrong et al., 2020;
Jenkins et al., 2020), preventing a comprehensive understanding of the
formation history of these objects. On the other side, there is a population
of sub-Neptune size planets exposed to a milder stellar irradiation that
usually present a gas-rich envelope with equilibrium temperatures below 1000 K
(e.g. Morley et al., 2015; Crossfield & Kreidberg, 2017; Gao et al., 2020). In
this paper we present the discovery and confirmation of TOI-220 $b$, a sub-
Neptune orbiting TYC 8897-01263-1, an old (10.1 Gyr) K0 V high proper motion
southern star with a magnitude of 9.69 in the TESS bandpass (V=10.47). The
brightness of the star, therefore, enabled a precise high SNR radial velocity
(RV) follow-up campaign with the High Accuracy Radial velocity Planet Searcher
(HARPS, Pepe et al., 2002) spectrograph mounted at the ESO La Silla 3.6 m
telescope, in the framework of the NCORES (e.g., Nielsen et al., 2020;
Armstrong et al., 2020) and KESPRINT (e.g., Gandolfi et al., 2018; Carleo et
al., 2020) collaborations. The confirmation of the planetary nature of TOI-220
$b$ is based on the simultaneous analysis of the TESS photometry and HARPS RV
measurements.

The rest of the paper is organized as follows. The gathered observations of
the TOI-220 system are described in Sect. 2. The stellar analysis, the
combined modelling and the timing analysis of the transits are presented in
Sect. 3. In Sect. 4 we describe the Bayesian analysis of the internal
structure of TOI-220 $b$ and the final discussion is presented in Sect. 5.

##  2 Observations

###  2.1 TESS observations

During TESS Southern ecliptic hemisphere observations, TOI-220 was observed
through sectors 1–12 with the exception of sector 3. By the end of the writing
of this work, the sectors 27 and 28 light curves were released, as part of the
TESS extended survey in the Southern hemisphere. These data were included in
the timing analysis (Sect. 3.4) and in the search for transits of the
hypothetical planet $c$ (Appendix C). The transit signals of TOI-220.01 (aka
TOI-220 $b$) were detected by the TESS Science Processing Operations Center
(SPOC, Jenkins et al., 2016) transit search pipeline (Jenkins, 2002; Jenkins
et al., 2010; Li et al., 2019). The transit detection threshold crossing
event, with a periodicity of 10.695 d, a depth of $\sim$900 ppm, and a
SNR$\sim$28, subsequently passed all SPOC data validation diagnostic tests
(Twicken et al., 2018) and was promoted to TESS Object of Interest (TOI)
status as a planet candidate (Guerrero et al., submitted). For each TESS
sector, the light curve of the target was retrieved from the Mikulski Archive
for Space Telescopes (MAST) archive. In this work, the two-minute cadence
Presearch Data Conditioning Simple Aperture Photometry (PDCSAP) light curves
(Stumpe et al., 2012; Stumpe et al., 2014; Smith et al., 2012) detrended with
the SPOC algorithms were used. Two or three transits of TOI-220 $b$ were
identified using a simple Box Least Squares (BLS) analysis on per-Sector light
curves. After a first inspection of the flux time series of each sector some
transits of TOI-220 $b$ were discarded due to SNR considerations and/or due to
large systematics in the flux time series. This was the case for the full
light curve of Sector 11. A few transits with poor coverage (incomplete
transits) were also discarded. Therefore, only one or two transits per TESS
Sector were finally extracted. A total of 17 out of the 24 transits of TOI-220
$b$ observed by TESS were considered for further analysis. After a first
estimation of the individual time of transits using the period obtained from
the BLS analysis, we extracted the photometric light curves around 0.4 days
before/after the transit central time, when possible. The TESS sector, central
time, and the 2 min RMS of each transit used in this work are reported in
Table 1 and the light curves are shown in Fig. 1.

Figure 1: TOI-220 $b$ transit light curves extracted from the TESS data. The black solid line represents the best transit model (Sect. 3.3). The labels indicate the corresponding TESS sector.  Table 1: Summary of TOI-220 $b$ transits extracted from the TESS data. TESS | transit mid-time | RMS(2 min)
---|---|---
Sector | [BJD_TDB] | [ppm]
S01 | 2458335.9024 | 890
S01 | 2458346.5976 | 941
S02 | 2458357.2928 | 897
S02 | 2458378.6832 | 903
S04 | 2458421.4640 | 979
S04 | 2458432.1592 | 909
S05 | 2458442.8544 | 942
S05 | 2458453.5496 | 949
S06 | 2458474.9400 | 952
S06 | 2458485.6352 | 882
S07 | 2458496.3304 | 908
S07 | 2458507.0257 | 929
S08 | 2458528.4161 | 924
S09 | 2458549.8065 | 911
S10 | 2458592.5873 | 833
S12 | 2458635.3681 | 961
S12 | 2458646.0633 | 938

###  2.2 HARPS follow-up

We obtained radial velocity measurements of TOI-220 with the HARPS
spectrograph (Mayor et al., 2003) mounted on the 3.6 m telescope at ESO’s La
Silla Observatory. HARPS is a stabilized high-resolution spectrograph with
resolving power of R $\approx$ 115000, capable of sub m s-1 RV precision. In
total 101 observations were taken between 18 November 2018 and 11 October 2019
in high accuracy mode, of which 91 were used in the combined fit. Observations
were performed under programmes 1102.C-0923 (PI: Gandolfi), 1102.C-0249 (PI:
Armstrong), 0102.C-0584 (PI: De Medeiros), 60.A-9700 and 60.A-9709 (technical
time). A typical exposure time of 1800 s was used, on occasion adjusted
between 1500 s and 2100 s depending on sky condition and observing schedule.
We achieved a typical signal-to-noise per pixel of 60 and an RV precision of
1.0 m s-1.

Eight observations acquired on the nights between 25 and 27 November 2018 were
excluded. On these dates the ThAr lamp used for wavelength calibration of
HARPS was deteriorating and was subsequently exchanged on 28 November 2018.
The changing flux ratio between the thorium and argon emission lines of the
dying ThAr lamp induced a 2 m s${}^{-1}\,$d-1 drift in the wavelength solution
of the instrument over 5 d. The problematic data were confirmed by comparing
unpublished data from the HARPS-N solar telescope (Dumusque et al., 2015;
Collier Cameron et al., 2019) and those of the Helios program on HARPS, which
also observes the Sun daily. Another observation done on the night of the 19
January 2019 was excluded due to an earthquake on that night222
https://www.volcanodiscovery.com/earthquakes/2019/01/20/01h32/magnitude7-NearCoastofCentralChile-
quake.html.. Finally, one observation on the night of the 17 April 2019 was
excluded due to its very low signal-to-noise ratio. This gives 91 useful
spectra.

The data were reduced with the HARPS data reduction software (DRS; Lovis &
Pepe, 2007). Radial velocity measurements were derived using the weighted
cross-correlation function (CCF) method using a K0 numerical mask (Pepe et
al., 2002). For each spectrum, the DRS provides also the contrast, the full
width at half maximum (FWHM), and the bisector inverse slope (BIS) of the
cross-correlation function, as well as the Ca ii H & K lines activity
indicator ($\log$ R${}^{\prime}_{\mathrm{HK}}$). We also extracted additional
activity indexes and spectral diagnostics, namely, H$\alpha$, Na D,
chromaticity (CRX), and differential line width (dLW), using the code SERVAL
(Zechmeister et al., 2018). The 91 DRS and SERVAL RV measurements and activity
indicators are listed in Tables 10 and 12. Time stamps are given in
Barycentric Julian Dates in Barycentric Dynamical Time (BJD_TDB). The RV time
series along with the best fitting model (Sect. 3.3) are shown in Fig. 7. We
found an RV jitter below 2 m s-1, consistent with the low activity level of
the star (see Sect. 3.1 and 3.3).

###  2.3 High resolution imaging

To search for contaminating stars in the TESS photometric aperture, TOI-220
was observed on 9 January 2020 with the Zorro speckle instrument at Gemini
South telescope333https://www.gemini.edu/sciops/instruments/alopeke-zorro/..
Zorro provides simultaneous speckle imaging in two bands, 562 nm and 832 nm,
with output data products including a reconstructed image, and robust limits
on companion detections (Howell et al., 2011). The contrast curve for the 832
nm is shown in Fig. 2. We also calculated from our high-resolution images the
probability of contamination from blended and undetectable sources in the TESS
aperture. We call this the blended source confidence (BSC) and the steps for
estimating this probability are fully described in Lillo-Box et al. (2014). We
used a python implementation of this technique (bsc, by J. Lillo-Box) which
uses the trilegal444http://stev.oapd.inaf.it/cgi-bin/trilegal. galactic model
(version 1.6; Girardi et al., 2012) to retrieve a simulated source population
of the region around the corresponding target555This is done in python by
using the astrobase implementation by Bhatti et al. (2020).. From this
simulated population, the density of stars around the target position (radius
r=1∘) was derived with the associated probability of chance-alignment at a
given contrast magnitude and separation. We used the default parameters for
the bulge, halo, thin/thick disks, and the lognormal initial mass function
from Chabrier (2001). The Zorro contrast curve was then used to constrain this
parameter space and estimate the final probability of undetected potentially
contaminant sources. We considered as potentially contaminant sources those
with a maximum contrast magnitude of $\Delta m_{\rm max}=-2.5\log{\delta}$,
with $\delta$ being the transit depth of the candidate planet in the TESS
band. This represents the maximum magnitude that a blended star can have to
mimic this transit depth. We converted the depth in the TESS passband to the
Zorro filters by using simple conversions using the TIC catalogue magnitudes
and linking the 562 nm filter to the SDSSr band and the 832 nm filter to the
SDSSz band. The corresponding conversions imply $\Delta m_{\rm
562\,nm}=0.954\Delta m_{\rm TESS}$ and $\Delta m_{\rm 832\,nm}=0.920\Delta
m_{\rm TESS}$.

We applied this technique to TOI-220 using the two contrast curves available
from the Gemini/Zorro instrument. The result provides a very low probability
for an undetected source capable of mimicking the transit signal of 0.055 %
for the 562 nm image and 0.015 % for the 832 nm image. We underline that using
high-resolution images allowed us to significaly improve these probabilities
by 26 % and 81 % for the 562 nm and 832 nm images, respectively, when
comparing to the raw probabilities (i.e, without high-resolution images). As
an example, we show in Fig. 2 the contrast curve and the results of the BSC
analysis. In addition, by using the tpfplotter code (Aller et al., 2020) we
ruled out the presence of contaminant sources within the TESS photometric
aperture down to a $\Delta{\rm mag}=8$ mag in the Gaia DR2 catalogue (see Fig.
3).

Figure 2: Contrast curve from the Gemini/Zorro instrument for the 832 nm
filter (solid black line). The color on each angular separation and contrast
bin represents the probability of a chance-aligned source with these
properties at the location of the target, based on TRILEGAL model (see Sect.
2.3 within the main text). The maximum contrast of a blended binary capable of
mimicking the planet transit depth is shown as a dotted horizontal line. The
green-shaded region represents the non-explored regime by the high-spatial
resolution image. The BSC corresponds to the integration of $P_{\rm aligned}$
over this shaded region. Figure 3: Target Pixel File of the TESS frame for
TOI-220 corresponding to Sector 1 and computed with tpfplotter (Aller et al.,
2020). The SPOC pipeline aperture is highlighted as red squares and the Gaia
DR2 catalogue is over plotted with symbol sizes proportional to the magnitude
contrast with the target.

###  2.4 Ground based photometric follow-up

We observed transit ingresses of TOI-220 $b$ in Pan-STARRS $z$-short band on
13 February 2019 and 21 December 2019 from the LCOGT (Brown et al., 2013) 1.0
m network node at South Africa Astronomical Observatory. We used the TESS
Transit Finder, which is a customized version of the Tapir software package
(Jensen, 2013), to schedule our transit observations. The $4096\times 4096$
LCOGT SINISTRO cameras have an image scale of 0.389$\arcsec$ per pixel,
resulting in a $26\arcmin\times 26\arcmin$ field of view. The images were
calibrated by the standard LCOGT banzai pipeline, and photometric data were
extracted with AstroImageJ (Collins et al., 2017). The 13 February 2019 images
were focused and have typical stellar point-spread-functions with a FWHM of
$1\aas@@fstack{\prime\prime}9$, and circular apertures with radius
$4\aas@@fstack{\prime\prime}3$ were used to extract the differential
photometry. The 21 December 2019 images were defocused and have typical
stellar point-spread-functions with a FWHM of $5\aas@@fstack{\prime\prime}2$,
and circular apertures with radius $7\aas@@fstack{\prime\prime}8$ were used to
extract the differential photometry. The light curves are presented in
Appendix 14.

##  3 Data analysis

###  3.1 Stellar parameters

We derived the spectroscopic parameters and chemical abundance of TOI-220 from
the co-added spectrum, which has an S/N per pixel at 5500 Å of $\sim$600\. We
used ares+moog, and followed the methodology described in Santos et al. (2013)
and Sousa (2014) to derive the stellar atmospheric parameters (Teff, $\log g$,
microturbulence, [Fe/H]), and their respective uncertainties. We first
measured equivalent widths (EW) of iron lines on the combined HARPS spectrum
of TOI-220 using the ares v2 code666The ares v2 code can be downloaded at
http://www.astro.up.pt/~sousasag/ares. (Sousa et al., 2015). Then we used a
minimization process where we assume ionization and excitation equilibrium to
converge in the best set of spectroscopic parameters. This process makes use
of a grid of Kurucz model atmospheres (Kurucz, 1993) and the radiative
transfer code MOOG (Sneden, 1973). Stellar abundances of the elements were
derived using the classical curve-of-growth analysis method assuming local
thermodynamic equilibrium (e.g. Adibekyan et al., 2012; Adibekyan et al.,
2015; Delgado Mena et al., 2014; Delgado Mena et al., 2017). Abundances of the
volatile elements, C and O, were derived following the method of Delgado Mena
et al. (2010); Bertran de Lis et al. (2015). Since the two analysed spectral
lines of oxygen (6158.17Å and 6300.3Å) are usually weak and the 6300.3Å line
is blended with a Ni line (see e.g. Bertran de Lis et al., 2015), the EWs of
these lines were manually measured with the task splot in IRAF. All the [X/H]
ratios are obtained by doing a differential analysis with respect to a high
S/N solar spectrum from HARPS, obtained from archival observations of the
asteroid Vesta.

The stellar parameters and abundances of the elements are presented in Table
3. These results are in agreement with the values obtained from the Bayesian
analysis described in Sect. 3.3. We found that the [X/Fe] ratios of $\alpha$
elements are slightly above solar. This fact together with a metallicity of
-0.22 dex indicate that TOI-220 is probably an old star from the thin disk
(e.g. Delgado Mena et al., 2019). Moreover, we used the chemical abundances of
some elements to derive ages through the so-called chemical clocks (i.e.
certain chemical abundance ratios which have a strong correlation for age). We
applied the 3D formulas described in Table 10 of Delgado Mena et al. (2019),
which also consider the variation in age produced by the effective temperature
and iron abundance. We used the chemical clocks [Y/Mg], [Y/Zn], [Y/Ti],
[Y/Si], [Y/Al], [Sr/Ti], [Sr/Mg] and [Sr/Si] from which we obtain a weighted
average age of 10.1 $\pm$ 1.4 Gyr. This age is in agreement (within their
uncertainties) with the age obtained from the Bayesian analysis described in
the Sect. 3.3.

Following Johnson & Soderblom (1987) we calculated the space velocity
components (UVW) with respect to the local standard of rest, adopting the
standard solar motion (U⊙, V⊙, W⊙) = (11.1, 12.24, 7.25) km s-1 of Schönrich
et al. (2010). Then, following Bensby et al. (2003) we calculated the
probability of the star belonging to different stellar populations. For more
details about the calculations of the kinematic properties of the stars see
Adibekyan et al. (2012). Our calculations suggest that TOI-220 belongs to the
galactic thin disk with a 98 % probability, in agreement with the chemical
classification.

Finally, Canto Martins et al. (2020) studied TOI-220 in their recent study of
1000 TOIs and found no evidence of a coherent rotation period in the
photometry, indicative of a low activity level. With a mean value of the Ca ii
H & K lines activity index of $\log$ R${}^{\prime}_{\mathrm{HK}}$ = $-5.07\pm
0.05$, TOI-220 is magnetically less active than the Sun whose $\log$
R${}^{\prime}_{\mathrm{HK}}$ ranges from $-$4.86 to $-$4.95 from solar maximum
to minimum (Hall et al., 2007).

###  3.2 Periodogram analysis of the HARPS measurements

We performed a frequency analysis of the HARPS RVs and spectral diagnostics to
search for the Doppler reflex motion induced by TOI-220 $b$ and unveil the
presence of additional signals that might be associated to stellar activity
and/or arise from the orbital motion of other planets in the system.

The generalized Lomb-Scargle (GLS) periodogram (Zechmeister & Kürster, 2009)
of the HARPS DRS RVs (Fig. 4, upper panel) shows a significant peak at fb =
0.093 d-1, i.e., the orbital frequency of the transiting planet detected in
the TESS light curve. We estimated its false-alarm probability (FAP) using the
bootstrap method described in Murdoch et al. (1993). Briefly, we computed the
periodogram of 106 mock time-series obtained by shuffling the RV measurements
and their uncertainties, while keeping the time-stamps fixed. We defined the
FAP as the fraction of those periodograms whose highest power exceeds the
observed power of fb in the periodogram of the original HARPS data at any
frequency. We found no false positives out of our 106 trials, implying that fb
has a FAP $<$ 10-6. Moreover, the peak at fb does not appear in any of the
periodograms of the activity indicators777For the CCF’s FWHM and BIS we
arbitarily adopted uncertanties twice as large as those of the RV
measurements. (Fig. 4), confirming that the Doppler signal is induced by the
presence of a _bona fide_ planet, namely, TOI-220 $b$.

We subtracted the Doppler signal of the transiting planet TOI-220 b from the
HARPS RVs by fitting a circular model,fixing the period and T0 to the values
derived from the modelling of the TESS light curves (with T0 being equal to
the mid-time of the first TESS transit), while allowing for the systemic
velocity and RV semi-amplitude to vary. The GLS periodogram of the RV
residuals displays significant (FAP $\,<\,$ 0.1 %) power at frequencies lower
than $\sim$0.008 d-1 (125 d), with a peak at about 0.0032 d-1 (309 d) (Fig. 4,
second panel). Despite this peak being undetected in the periodograms of the
activity indicators and line asymmetry diagnostics (Fig. 4) – suggesting the
presence of an additional outer companion – we note that its period is poorly
constrained, being comparable to the temporal baseline of our observations
(327 d). Moreover, the position of this peak depends on the last poorly-
sampled measurements. Therefore, as discussed in Sect. 3.3.2, the exact nature
of this long period signal can not be firmly constrained with the currently
available RV data.

Figure 4: From top to bottom: Generalized Lomb-Scargle periodograms of the
HARPS RV measurements (upper panel); the RV residuals following the
subtraction of the signal of the transiting planet (second panel); the
activity indicators of TOI-220 (remaining panels). The 0.1 % false alarm
probability (FAP) estimated using the bootstrap method is shown with
horizontal dashed lines. The vertical red lines mark the orbital frequencies
the transiting planet TOI-220 $b$ (fb = 0.093 d-1) and of the additional
Doppler signal we found in the HARPS RVs ($f_{\mathrm{c}}$ = 0.0032 d-1).

###  3.3 PASTIS analysis

The Planet Analysis and Small Transit Investigation Software (Díaz et al.,
2014; Santerne et al., 2015), pastis, was used for the joint analysis of the
transit light curves, the radial velocities and the spectral energy
distribution of TOI-220. The pastis package implements a fully Bayesian
analysis of the data and uses the Markov Chain Monte Carlo (MCMC) method to
sample the posterior distribution of the resulting parameters (see e.g.
Santerne et al., 2019; Lopez et al., 2019, and references therein). We draw
the posterior distributions of all free parameters after merging the best MCMC
chains, i.e. those with the largest model likelihood ($\log$ L) from a sample
of 30 chains with $10^{6}$ steps each. The convergence of these chains is
checked by a Kologorov-Smirnov (K-S) test after the burn-in period (BI) of
each chain has been removed. Here, the BI phase corresponds to the initial
portion of each chain with a $\log$ L mean and variance 2 $\sigma$ away from
the corresponding values of the last 10 % of the chain. Then, after removing
the BI phase, the selected chains correspond to those with a median $\log$ L
within 2 $\sigma$ of the best chain (i.e. the chain with the largest median
$\log$ L) and with a K-S test p-value above 10-30.

As mentioned in Sect. 2, 17 individual transits of TOI-220 $b$ were extracted
from the TESS light curves and input to pastis. Additionally, a nightly
binning was applied to the RV data in order to minimize the jitter induced by
stellar activity and/or granulation, ending up thus with 69 points out of the
total 91 RV measurements. The transits were modelled using jktebop software
(Southworth, 2008) and the RV data using keplerian orbits.

####  3.3.1 Stellar SED analysis

pastis also models the host star by fitting the spectral energy distribution
(SED) to the BT-Settl atmosphere models (Allard et al., 2012), Dartmouth
evolutionary tracks (Dotter et al., 2008) and the quadratic limb darkening
coefficients for TESS bandpass based on the tables from Claret & Bloemen
(2011).

After a preliminary analysis using all the available magnitudes of TOI-220
(Table 2) we obtained a very poor fit of the visual magnitudes, in particular
in the V band. We attributed this result to inconsistencies with the magnitude
zero point used or with unreliable V magnitude estimations due to saturation
of stars brighter than V=10 mag in the case of the APASS catalogue (Henden et
al., 2015). As pastis does not implement the use of Gaia magnitudes by the
time of this analysis, we decided to use only 2MASS (Skrutskie et al., 2006)
and AllWISE (Cutri et al., 2013) magnitudes for the bayesian analysis. For
this, we took TOI-220’s NIR magnitudes as reported in the TESS Input Catalogue
(TICv8, Stassun et al., 2019). The host star was modelled for the effective
temperature, T${}_{\text{eff}}$; surface gravity, $\log$ $g$; metallicity,
[M/H]; distance, d; color excess, E(B$-$V); the systemic radial velocity, v0,
using as priors either normal or uniform distributions as presented in Table
6. The SED and best stellar model obtained with pastis are displayed in Fig. 5
and the fitted and derived stellar parameters are listed in Table 3. The
resulting stellar parameters are consistent within their uncertainties with
the values obtained independently from the spectral analysis described in
Sect. 3.1.

Figure 5: Top panel: spectral energy distribution of TOI-220 with the best
stellar atmosphere model from the BT-SETTL library obtained with pastis (blue
solid line). Residuals are shown in the bottom panel (error bars include the
fitted jitter from the analysis).

In order to corroborate the TOI-220’s effective temperature obtained with
pastis and to discard any bias we could have introduced by using only NIR
magnitudes, the observed and theoretical SEDs for TOI-220 were compared using
the Virtual Observatory Spectral Analyzer (VOSA, Bayo et al., 2008). The
observed SED was constructed using the four IR bands W1-W4 from allWISE, the
J, H, and Ks bands from 2MASS (Skrutskie et al., 2006), and also including the
3 bands from Gaia (Gaia Collaboration et al., 2018). As before, the
theoretical fluxes were computed from the grids of theoretical stellar spectra
BT-Settl (AGSS2009, Allard et al., 2012). A best fit with the observed data
was computed by $\chi^{2}$ minimization by testing effective temperature
values ranging from 1000–7000 K with steps of 100 K. We also adopted the
estimation of interstellar extinction provided in the TESS input catalog
(Stassun et al., 2019), then computing the reddening according to Fitzpatrick
(1999) and Schlafly & Finkbeiner (2011). The SED and the fitted stellar model
are shown in Fig. 13. This independent analysis provides an effective
temperature of 5300 $\pm$ 50 K, in very good agreement with the result from
pastis. This analysis also shows no IR-excess, suggesting the absence of
circumstellar material around TOI-220, at least in the WISE infrared bands.

Figure 6: Top: TOI-220 $b$ transit light curve built by joining the 17 TESS
transits used in this work (blue points and 12 min bins in red) together with
the best model (solid curve) obtained with pastis analysis. The residuals are
shown in the bottom panel.

####  3.3.2 Planetary analysis

Figure 7: Radial velocity time series with the best fitted model superimposed
with the corresponding residuals are shown in the top and middle panel,
respectively. The phased radial velocity measurements are shown in the bottom
panel. The error bars include the fitted jitter for each case. Additional, a
fitted quadratic long-term is represented by a solid red curve in the middle
pannel (see Sect 3.3.2 for details).

Based on the periodograms presented in Sect. 3.2, the data analysis of the
TOI-220 system was performed taking into account the presence of a single
planet in the system to probe the 10.69 d periodic signal. Additionally, we
also included a quadratic, long-term RV trend in the modelling.

For the single planet scenario we modelled the planetary orbital period, P;
the reference transit epoch, T0; the star-planet radius ratio,
$R_{\text{s}}/R_{\text{p}}$; the radial velocity semi-amplitude, K; and the
inclination, eccentricity and argument of the periastron of the orbit: $i$,
$e$ and $\omega$, respectively. The prior distribution used for each parameter
is reported in Table 6. The posterior distribution of all the free parameters
was drawn from the best 15 MCMC chains after removing the burn-in (BI) time
(7–22 % of the chain). The full list of fitted and derived parameters of the
system together with its respective 68.3 % confidence interval are given in
Table 3 and 4 for the star and planet, respectively. Despite the good fit of
the keplerian model, it seems that a structure is still present in the RV
residuals (see e.g. Fig. 4, second panel). To better assess the significance
of this trend, we applied the Anderson-Darling (A-D) test (Stephens, 1974) to
the RV residuals (Table 7). The A-D test is a modification of the K-S test to
evaluate whether a data sample comes from a specific distribution; in our case
we tested the RV residuals against a Normal distribution. The test’s result is
compared then to a set of critical values in a range of significance levels.
In particular, the A-D test statistic (see Table 7) of the RV residuals is
greater than the critical value at 15 % significance, 0.580 > 0.547
($\alpha=0.15$), therefore the normality hypothesis of the RV residuals is
rejected evidencing that they may contain astrophysical information not
included in our single planet model.

Therefore, we also explored the effect of including a radial velocity
quadratic trend in the RV modelling. For this, we used the same initial setup
as before but adding two extra terms to account for a quadratic drift in the
stellar radial velocity. We set a wide uniform distribution as a prior for the
amplitude of the drift coefficients (Table 6). Here, we selected the best 20
MCMC chains after removing the BI (7–27 % of the chain) to draw the posterior
distributions of the fitted parameters. The fitted drift coefficients are
reported in Table 3 and the RV drift together with the 1-planet model are
shown in Fig. 7. Despite the amplitude of the residuals being smaller when
compared to the single planet scenario, the structure in the first epochs (t <
2458440.20 BJD) in the RV residuals seems to remain. But in this case, the
normality of the residuals is not rejected by the A-D test. We show in Table 7
the result of this and other statistical tests which favour the inclusion of
the RV drift in the modelling. Notably, the TOI-220 $b$ parameters are not
affected by including this RV long term drift (Table 4). In Appendix E we show
the mass constraints of a hypothetical second orbital body based on the
estimated RV drift. Finally, we also checked the results when including a
second planet in the modelling with a wide prior in the orbital period around
the peak observed in the RV residual periodogram (300$\pm$100 d). We found
that the RMS of the RV residuals are reduced, however, the resulting
parameters for the second planet are poorly constrained. Based on this
together with the fact that all the obtained parameters of TOI-220 $b$ remain
fully compatible between models (see Table 4); and specially considering the
baseline of the RV monitoring (only 327 d compared with the periodogram peak
of the RV residuals of $\sim$309 d) and that the location of this peak
strongly depends on the data points considered to calculate the periodogram;
we adopt the values derived using the 1-planet with the quadratic RV long term
drift shown in Tables 3 and 4 for the star and planet, respectively. We
obtained for TOI-220 $b$ a planetary mass and radius of
M${}_{\text{p}}$=13.8$\pm$1.0 M⊕ and R${}_{\text{p}}$=3.03$\pm$0.15 R⊕. The
fitted orbital period and reference epoch are P=10.695264(86) d and
T0=2458335.9020(14) [BJD_TDB], respectively. The best model for each
individual transit is shown in Fig. 1 and in Fig. 6 for the complete folded
light curve of the 17 TESS transits. The best RV model including the RV
quadratic drift and its residuals are displayed in Fig. 7. As a sanity check,
we performed an independent joint analysis of the transit photometry and HARPS
Doppler measurements using the code pyaneti (Barragán et al., 2019). We
adopted the same PASTIS RV models and found consistent results well within the
nominal error bars, corroborating the results of our analysis.

###  3.4 Transit Timing Variations

We performed the timing analysis of TOI-220 $b$ using the 17 TESS transits
from sectors 1-12, the 4 transits of sectors 27-28; and the 2 transit
observations obtained with the LCOGT telescopes. For this, we fixed all the
transit parameters to the values obtained from pastis analysis in Sect. 3.3.2
except for the T${}_{\text{c}}$, R${}_{\text{p}}$/R${}_{\text{s}}$ and the
inclination which were let free to vary. As the two LCOGT transits have a
relative lower quality in terms of photometric precision and sampling; and
owing to the fact that they cover only the ingress of the transit (see Fig.
14) we fixed also the inclination to i=87.88 $\deg$ for the modelling of these
light curves. For the mid-times of the TESS transits, we used as priors a
normal distribution with a 0.4 d width centred in the values obtained from the
BLS analysis (Table 1). For each transit fit we used 20 MCMC chains of 105
iterations. The obtained values for R${}_{\text{p}}$/R${}_{\text{s}}$ and
inclination are consistent within the uncertainties in all the transits. The
resulting transit mid-times are reported in Table 9. The average uncertainty
of the transit mid-times is around 7 min. The first LCOGT transit has an
uncertainty larger than 30 min in comparison with the 6 min of second LCOGT
transit. As this light curve has a very poor photometric quality and transit
coverage, we removed it from the analysis. With the obtained mid-times and the
ephemeris equation:

$\text{T}_{\text{c}}(n)=2458335.9021(14)[\text{BJD\\_TBD}]+n\times
10.695264(86),$ (1)

where P and T0 are from Sect. 3.3.2; we estimated the timing residuals of
TOI-220 $b$ as presented in Fig. 8 and Table 9. All the transit times are
consistent within the uncertainties with a constant orbital period; the RMS of
the O$-$C points is around 4.7 min. In addition, the statistical A-D test
supports the hypothesis that the timing residuals are drawn from a normal
distribution, discarding thus, orbital perturbations induced by a possible
close companion.

Figure 8: Observed minus Calculated diagram of the transit mid-times of TOI-220 $b$. Blue symbols correspond to TESS transits while the red symbol correspond to the second LCOGT transit observation. The shaded region represents the projected 1$\sigma$ uncertainties of ephemeris equation of TOI-220 $b$ (Sect. 3.4). Table 2: TOI-220 main IDs, celestial coordinates and magnitudes. Parameter | value | reference
---|---|---
TIC | 150098860 | (1)
TOI | 220 | (2)
TYC | 8897-01263-1 | (1)
APASS | 29859752 | (3)
2MASS | J06071197-6159487 | (4)
WISE | J060711.93-615949.5 | (5)
Gaia DR2 | 5481210874877547904 | (6)
RA (J2000) | 06:07:11.967 | (1)
DEC (J2000) | -61:59:48.895 | (1)
$\mu_{\text{RA}}$ [mas yr-1] | -17.815 $\pm$ 0.046 | (6)
$\mu_{\text{DEC}}$ [mas yr-1] | -68.361 $\pm$ 0.042 | (6)
Band | value | reference
TESS | $9.688\pm 0.006$ | (1)
Johnson-V | $10.416\pm 0.263$ | (3)
Johnson-B | $11.152\pm 0.032$ | (3)
2MASS-J | $9.030\pm 0.024$ | (4)
2MASS-H | $8.631\pm 0.031$ | (4)
2MASS-Ks | $8.542\pm 0.025$ | (4)
WISE-W1 | $8.476\pm 0.023$ | (5)
WISE-W2 | $8.525\pm 0.020$ | (5)
WISE-W3 | $8.381\pm 0.021$ | (5)
WISE-W4 | $8.526\pm 0.167$ | (5)
Gaia G | 10.1897 $\pm$ 0.003 | (6)
Gaia Bp | 10.6078 $\pm$ 0.0012 | (6)
Gaia Rp | 9.6408 $\pm$ 0.0007 | (6)
(1) TIC v8 (Stassun et al., 2019).
(2) TOI Catalogue (Guerrero et al. Submitted).
(3) AAVSO Photometric All-Sky Survey (Henden et al., 2015).
(4) Two Micron All Sky survey (Skrutskie et al., 2006).
(5) AllWISE Catalogue (Cutri et al., 2013).
(6) Gaia DR2 (Gaia Collaboration et al., 2018).

Table 3: Stellar properties of TOI-220. Parameter | Value | Ref.
---|---|---
T${}_{\text{eff}}$ [K] | 5273 $\pm$ 115 | (1)
T${}_{\text{eff}}$ [K] (adopted) | 5298 $\pm$ 65 | (2)
T${}_{\text{eff}}$ [K] | $5384\pm 77$ | (3)
T${}_{\text{eff}}$ [K] | $5182\pm 45$ | (4)
$\log$ $g$ [cgs] (adopted) | 4.37 $\pm$ 0.11 | (2)
$\log$ $g$ [cgs] | 4.25 $\pm$ 0.07 | (4)
$\log$ $g$ [cgs] | 4.49 $\pm$ 0.03 | (3)
V${}_{\text{turb}}$ [km s-1] | 0.694 $\pm$ 0.058 | (2)
[Fe/H] [dex] | -0.217 $\pm$ 0.044 | (2)
[M/H] [dex] | -0.19 $\pm$ 0.05 | (3)
[Fe/H] [dex] | -0.2 $\pm$ 0.07 | (4)
[Mg/H] [dex] | -0.10 $\pm$ 0.05 | (2)
[Si/H] [dex] | -0.14 $\pm$ 0.04 | (2)
[O/H] [dex] | -0.031 $\pm$ 0.072 | (2)
[C/H] [dex] | -0.214 $\pm$ 0.045 | (2)
[Cu/H] [dex] | -0.176 $\pm$ 0.044 | (2)
[Zn/H] [dex] | -0.172 $\pm$ 0.027 | (2)
[Sr/H] [dex] | -0.156 $\pm$ 0.077 | (2)
[Y/H] [dex] | -0.293 $\pm$ 0.094 | (2)
[Zr/H] [dex] | -0.236 $\pm$ 0.071 | (2)
[Ba/H] [dex] | -0.237 $\pm$ 0.025 | (2)
[Ce/H] [dex] | -0.166 $\pm$ 0.045 | (2)
[Nd/H] [dex] | -0.100 $\pm$ 0.039 | (2)
$v$ sin $i$ [km s-1] | 2.90 $\pm$ 0.35 | (4)
V${}_{\text{mac}}$ [km s-1] | 0.9 $\pm$ 0.4 | (4)
V${}_{\text{mic}}$ [km s-1] | 0.85 $\pm$ 0.10 | (4)
Age [Gyr] (adopted) | 10.1 $\pm$ 1.4 | (2)
Age [Gyr] | 10.7${}^{+2.1}_{-3.1}$ | (3)
Distance [pc] | 89 $\pm$ 4 | (3)
E(B$-$V) [mag] | 0.163 $\pm$ 0.087 | (3)
Systemic RV, v0 [m s-1] | 26.45827 $\pm$ 0.00037 | (3)
RV drift lin. coeff. [m s-1 d-1] | -0.0379(80) | (3)
RV drift quad. coeff. [m s-1 d-2] | 0.000149(31) | (3)
Radius [R☉] | 0.858 $\pm$ 0.032 | (3)
Mass [M☉] | 0.825 $\pm$ 0.028 | (3)
Density [$\rho_{\sun}$] | 1.31 $\pm$ 0.15 | (3)
Limb darkening coeff. u${}_{\text{a}}^{\text{\tiny{TESS}}}$ | 0.352 $\pm$ 0.014 | (3)
Limb darkening coeff. u${}_{\text{b}}^{\text{\tiny{TESS}}}$ | 0.2475 $\pm$ 0.0077 | (3)
(1) TIC v8 (Stassun et al., 2019).
(2) From spectral analysis (Sect.3.1). Values correspond to weighted
average and the standard deviation.
(3) From pastis analysis (Sect. 3.3). Derived values assume
R☉=695 508 km and M☉= 1.98842 $\times$ 1030 kg.
(4) From spectral analysis validation (Appendix A) .
Table 4: Results on the planetary parameters obtained from pastis simultaneous analysis of the data assuming a single planet system and by including a long term quadratic drift in the RVs. Derived values assume M⊕ = 5.9736$\times$1024 kg, R⊕ = 6 378 137 m, AU = 149 597 870.7 km and zero albedo for the equilibrium temperature. Parameter (fitted) | 1 Planet | 1 Planet + RV drift (adopted)
---|---|---
Orbital period, P [d] | 10.695264(87) | 10.695264(86)
Reference transit time, T0 [BJD$\\_$TDB] | 2458335.9021(14) | 2458335.9020(14)
Planet-to-star radius ratio, R${}_{\text{p}}$/R${}_{\text{s}}$ | 0.03227 $\pm$ 0.00078 | 0.03235 $\pm$ 0.00076
Orbital inclination, $i$ [$\degr$] | $87.86\pm 0.14$ | $87.88\pm 0.12$
RV semi-amplitude, K [m s-1] | 4.47 $\pm$ 0.36 | 4.56 $\pm$ 0.32
Orbital eccentricity, $e$ | $0.029^{\tiny{+0.034}}_{-0.021}$ | $0.032^{+0.038}_{-0.023}$
Argument of periastron, $\omega$ [$\degr$] | 159 $\pm$ 150 | $248^{+66}_{-190}$
Parameter (derived) |  |
Mass [M⊕] | $13.6\pm 1.2$ | $13.8\pm 1.0$
Radius [R⊕] | $3.02\pm 0.17$ | $3.03\pm 0.15$
bulk density, $\rho_{\text{p}}$ [g cm-3] | 2.69 $\pm$ 0.55 | 2.73 $\pm$ 0.47
System scale, a/R${}_{\text{s}}$ | 22.3 $\pm$ 1.0 | 22.33 $\pm$ 0.80
Impact parameter, $b$ | $0.832\pm 0.026$ | $0.836\pm 0.022$
Transit duration, T14 [h] | 2.231 $\pm$ 0.054 | 2.239 $\pm$ 0.055
orbital semi-major axis, a [AU] | 0.08920 $\pm$ 0.0010 | 0.08911 $\pm$ 0.0010
Mean equilibrium temperature, T${}_{\text{eq}}$ [K] | 806 $\pm$ 25 | 805 $\pm$ 21
Instrument-related parameters |  |
HARPS jitter [m s-1] | 1.71000 $\pm$ 0.00021 | 1.35000 $\pm$ 0.00024
SED jitter [mag] | 0.048 $\pm$ 0.025 | 0.049 $\pm$ 0.026
TESS jitter [ppm] | 111$\pm$74 | 111$\pm$ 74
TESS out-of-transit flux | 1.000093(30) | 1.000093(30)

##  4 Planetary Structure

Figure 9: Mass-Radius diagram of the confirmed exoplanets with mass and radius measurements better than 20 % and 10 %, respectively. The symbol’s color scales with the equilibrium temperature of the planet. TOI-220 $b$ location in the diagram is highlighted with the red arrow and black circle. Solar System planets are also shown for reference. Composition models from Zeng et al. (2019) are displayed with dash brown and green lines. Those for a planet at 800 K with an Earth-like composition topped with various proportion of a steam and supercritical water layer (Mousis et al., 2020) are displayed with blue solid lines. Table 5: Output parameters retrieved by the MCMC interior and atmosphere modeling. Parameter | Value
---|---
Total mass, M${}_{\text{p}}$ [M⊕] | 13.8$\pm$0.7
Total radius, R${}_{\text{p}}$ [R⊕] | 3.06$\pm$0.12
Total density, $\rho_{\text{p}}$ [g cm-3] | 2.65$\pm$0.28
Core mass fraction, CMF | 0.08$\pm$0.03
Water mass fraction, WMF | 0.62$\pm$0.10
Fe/Si mole ratio | 0.64$\pm$0.11
Mg/Si mole ratio | 1.16$\pm$0.10
Mg number, # Mg | 0.85-1.0
Temperature at 300 bar, T${}_{\text{surf}}$ [K] | 3536$\pm$203
Planetary albedo, $a_{\text{p}}$ | 0.230$\pm$0.001
Atmospheric thickness, z [km] | 1111$\pm$99
Atmospheric mass, M${}_{\text{atm}}$ [M${}_{\oplus}\ 10^{-3}$] | 1.31$\pm$0.16
Core+Mantle radius, [R${}_{\text{p}}$ units] | 0.47$\pm$0.05
Figure 10: Sampled 2D marginal posterior distribution function for the CMF and
WMF of TOI-220 $b$ (blue region). The PDF mean and the 1$\sigma$ confidence
interval is marked by the yellow cross and curve, respectively. TOI-220 $b$ is
consistent with a water rich planet (WMF=0.62$\pm$0.10) with a very small core
(CMF=0.08$\pm$0.03). Earth and Mercury values are presented for comparison.
Figure 11: Mass-Period diagram of the confirmed exoplanets to date with masses
and periods below 100 M⊕ and 50 d, respectively (same planets sample as Fig.
9). The symbols size represents the radius of the planet while its equilibrium
temperature is coded by the color of the symbol. TOI-220 $b$ is outlined with
a black circle. The dashed lines mark the edges of the Neptune-desert from
Mazeh et al. (2016).

Figure 9 shows the mass-radius diagram of all the confirmed exoplanets to
date888from http://exoplanet.eu/ as of 27 January 2021., with a precision
better than 20 % and 10 % in their mass and radius, respectively. TOI-220 $b$
is well located in a domain of the sub-Neptune size planets. We investigate
the interior of TOI-220 $b$ in order to get some insights into its
composition. To that purpose we used the model of internal structure developed
by Brugger et al. (2017) and recently updated by Mousis et al. (2020) to
include a steam and supercritical water layer for the special case of highly-
irradiated planets. When the pressure and temperature are above the critical
point of water, water is in supercritical phase. To describe this water layer,
we use the Equation of State (EOS) of Mazevet et al. (2019), which includes
experimental and theoretical data of water at pressures and temperatures
higher than the critical point of water. TOI-220 $b$ being strongly irradiated
with an equilibrium temperature of 806 K, the model allows to address how its
composition could differ from that of a Neptune-like planet with a large
gaseous envelope overlying a rocky core. We followed the method described in
Lillo-Box et al. (2020) and Acuña et al. (2021) exploring the core mass
fraction (CMF, the ratio of the mass of the core and the total planetary mass)
and the water mass fraction (WMF, the ratio of the mass of the water layer
-steam and supercritical- and the total mass) of the planet as free parameters
in an MCMC Bayesian framework adapted from Dorn et al. (2015).

We use as input parameters the planetary mass and radius, and the Fe/Si and
Mg/Si mole ratios. The latter are calculated with the stellar abundances in
Table 3 as Fe/Si = 0.65$\pm$0.09 and Mg/Si = 1.17$\pm$0.17. The code allows to
explore the posterior distribution functions of three compositional
parameters: CMF, WMF, and the Mg number ($\\#$ Mg), which is a proxy for the
level of differentiation of the planet as described by Sotin et al. (2007) and
Brugger et al. (2017). If most of the Mg is located in the mantle and Fe in
the core, the planet is highly differentiated and $\\#$ Mg is close to one
(0.9 for the case of Earth). On the contrary, if Mg and Fe are mixed in the
mantle, $\\#$ Mg will have lower values ($\simeq$ 0.6). In the MCMC algorithm,
we assume uniform prior distributions of the CMF, WMF and the Mg number.

Table 5 shows the retrieved values of the three free compositional parameters,
in addition to the observables (mass, radius and mole ratios), and the
atmospheric variables. The posterior distributions of the CMF and WMF are also
shown in Fig. 10. We used an MCMC algorithm to obtain samples of the posterior
distribution of all our observable parameters: mass, radius, Fe/Si and Mg/Si.
Convergence is achieved when the output parameters of the model reproduce the
observed values within the 1$\sigma$ confidence intervals. Our results
indicate that a planetary structure composed of a core rich in Fe, a silicate
mantle and a supercritical water layer topped by a steam atmosphere in
radiative-convective equilibrium is a likely scenario for TOI-220 $b$.

Since its host star is less enriched in Fe than the Sun and Earth (Fe/Si =
0.93), its CMF is significantly lower ($0.08\pm 0.03$) than the terrestrial
value, 0.32. As can be seen in Table 5, the large $\\#$ Mg obtained (0.85–1.0)
is indicative of a highly-differentiated core and mantle configuration such as
the Earth ($\\#$ Mg=0.9). Furthermore, as shown in Fig. 10, TOI-220 $b$ could
be a water-rich planet with a minimum WMF of 52%, which is compatible with the
composition derived for water-rich satellites in the Solar System, such as
Titan, and a maximum WMF of 72%, which is below the average water proportion
found in comets (see Fig. 12 of McKay et al., 2019). Moreover, most of the
water mass would be under pressure and temperature conditions beyond the
supercritical point, forming a supercritical and steam water layer that would
constitute 47% of the total radius.

##  5 Discussion

Figure 12: Histogram of the planetary radius for planets with periods below
100 d as presented in Fulton & Petigura (2018). The location of the radius gap
and the size of TOI-220 $b$ ($\pm$1 $\sigma$) are shown with the black-dashed
and orange-shaded lines, respectively.

The combined analysis of the photometric and spectroscopic data has fully
confirmed the planetary nature of the TOI-220 $b$ transiting candidate. We
noted the presence of a structure in the RV residuals on the exact nature of
which, instrumental or planetary, we could not conclude with the data
currently available. Therefore, any further investigation of the long-period
signals would requires additional RVs. Thus, we adopt the values derived using
a single planet model in the system and including a quadratic long term trend
in the RVs. In Fig. 11 we show the mass-period diagram of all the confirmed
exoplanets including TOI-220 $b$ (same sample as Fig. 9). The symbol size
scales with the radii of planets while the color represents the planet’s
equilibrium temperature. TOI-220 $b$ is located in the region of the warm sub-
Neptunes class of exoplanets (T${}_{\text{eq}}$<1000 K) with a relatively
large size (3 R⊕).

A paucity of exoplanets has been reported in the planet size distribution
around 1.5-2.0 R⊕ (e.g. Fulton et al., 2017; Fulton & Petigura, 2018; Van
Eylen et al., 2018), in particular for a M${}_{\star}\sim$ 0.8 M☉ the gap is
around 1.6 R⊕. It is suggested that this gap is driven by photoevaporation
mass-loss which acts shifting planets with gaseous envelopes towards a rocky
Super-Earth population (R<1.7 R⊕). TOI-220 $b$ lies above the gap in the
Fulton’s diagram (see Fig. 12) in the not so populated high end of the size
distribution of planets (R$\gtrsim$3 R⊕) orbiting low mass stars (M⋆<0.97 M☉),
as can be seen in Fig. 8 and 9 in Fulton & Petigura (2018). The atmospheric
composition of TOI-220 $b$, either with a thick H/He layer or water rich
content, suggests a formation in the protoplanetary disk past the snow line
followed by slow migration. The host’s age of $\sim$10 Gyr points to a very
evolved system and the large planet’s radius suggests the planet was massive
enough to keep its atmosphere despite the large irradiation received by its
host star. To get a first estimate of the atmospheric escape of TOI-220 $b$,
we used equations of Aguichine et al. (Submitted). We found that the mass lost
by Jeans’ escape is negilible even for light species (H/He) due to the surface
gravity of the planet. Only $\sim$0.1 M⊕ could be removed by XUV photo-
evaporation along its 10.1 Gyr of life. This picture is consistent with the
idea that the fate of warm sub-Neptunes located above the gap in the Fulton’s
diagram (Fig. 12) is not to end their evolution as naked cores (see Deleuil et
al., 2020; Bean et al., 2021, and references therein). Precise measurements of
physical parameters of planets and its host stars, like the ones presented in
this work, are key to shape the knowledge of the formation and evolution
processes that sculpt the planet population in this region of parameter space.

Complementarily, we have performed an interior structure and atmosphere
analysis within a Bayesian framework to constrain the composition of TOI-220
$b$ given its density and the stellar abundances of the host star. The low
density of this strongly irradiated planet could be explained with a water-
rich atmosphere that reaches the supercritical phase at its base, with a
silicate mantle and an iron core as its bulk. As an alternative the planet
might have a solid core surrounded by a thick H/He atmosphere. Future work
should explore this possibility but also a composition with a well-mixed water
and H/He atmosphere, since these are the most common volatiles that can form
low-mass planets. The confirmation of the water-rich atmosphere scenario would
also require conducting atmospheric characterisation to search for water
spectral features. Following Kempton et al. (2018) we thus calculate TOI-220
$b$ transmission spectroscopy metric to check whether the planet would be
amenable to such a characterization by JWST or the ELT. We obtained a value of
45, which is well below the threshold of 84 for planets in this range of size,
making of TOI-220 $b$ atmosphere likely out of reach for the next decade.

## Acknowledgements

SH acknowledges CNES funding through the grant 837319. MD acknowledges the
CNES support. V.A., E.D.M., S.G.S., N.C.S., S.C.C.B. and S.Hoj. acknowledge
support by FCT - Fundação para a Ciência e a Tecnologia (Portugal) through
national funds and by FEDER through COMPETE2020 - Programa Operacional
Competitividade e Internacionalização by these grants: UID/FIS/04434/2019;
UIDB/04434/2020; UIDP/04434/2020; PTDC/FIS-AST/32113/2017 &
POCI-01-0145-FEDER-032113; PTDC/FIS-AST/28953/2017 &
POCI-01-0145-FEDER-028953. V.A., E.D.M., S.C.C.B., S.G.S. and O.D.S.D further
acknowledge the support from FCT through Investigador FCT contracts
IF/00650/2015/CP1273/CT0001, IF/00849/2015/CP1273/CT0003,
IF/01312/2014/CP1215/CT0004, CEECIND/00826/2018–POPH/FSE(EC) and
DL57/2016/CP1364/ CT0004, respectively. S.Hoj. further acknowledges the
support by FCT through the fellowship PD/BD/128119/2016. DJA acknowledges
support from the STFC via an Ernest Rutherford Fellowship (ST/R00384X/1).
L.M.S. and D.G. gratefully acknowledge financial support from the CRT
foundation under Grant No. 2018.2323 “Gaseous or rocky? Unveiling the nature
of small worlds". JRM, BLCM and ICL acknowledge continuous grants from the
brazilian funding agencies CNPq, CAPES and FAPERN. This study was financed in
part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil
(CAPES)-Finance Code 001. PK and JS acknowledge the MSMT INTER-TRANSFER grant
LTT20015. This paper includes data collected with the TESS mission, which are
publicly available from the Mikulski Archive for Space Telescopes (MAST).
Funding for the TESS mission is provided by NASA’s Science Mission
directorate. We acknowledge the use of public TESS Alert data from pipelines
at the TESS Science Office and at the TESS Science Processing Operations
Center. This research has made use of the Exoplanet Follow-up Observation
Program website, which is operated by the California Institute of Technology,
under contract with the National Aeronautics and Space Administration under
the Exoplanet Exploration Program. Resources supporting this work were
provided by the NASA High-End Computing (HEC) Program through the NASA
Advanced Supercomputing (NAS) Division at Ames Research Center for the
production of the SPOC data products. This research has made use of computing
facilities operated by CeSAM data center at LAM, Marseille, France; and the
Data & Analysis Center for Exoplanets (DACE), which is a facility based at the
University of Geneva (CH) dedicated to extrasolar planets data visualisation,
exchange and analysis. DACE is a platform of the Swiss National Centre of
Competence in Research (NCCR) PlanetS, federating the Swiss expertise in
Exoplanet research. This research has made use of data obtained from the
portal exoplanet.eu of The Extrasolar Planets Encyclopaedia. 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 makes
use of observations from the LCOGT network. D.G. warmly thanks Alessia
Barbiero and Pietro Giordano for the inspiring conversations at the time the
HARPS follow-up of TOI-220 was started in November 2018.

Software: We gratefully acknowledge the open source software which made this
work possible: astropy (Astropy Collaboration et al., 2013; Price-Whelan et
al., 2018), ipython (Pérez & Granger, 2007), numpy (Van Der Walt et al.,
2011), scipy (Jones et al., 2001), matplotlib (Hunter, 2007), jupyter (Kluyver
et al., 2016), pandas (McKinney, 2010; Pandas development team., 2020).

Facilities: TESS, ESO:3.6m (HARPS spectrograph), Gemini:South (Zorro), LCOGT,
Exoplanet Archive

##  6 Data Availability

The TESS photometric data used in this work is available via Mikulski Archive
for Space Telescopes (MAST) archive and TFOP program. Radial velocity
measurements and the derived stellar activity indicators are provided in
Tables 10 and 12, respectively.

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##  Appendix A Validation of stellar parameters

In addition to what has been presented in Sect. 3.1, as an independent
validation, we also derived the main stellar parameters by applying the
Spectroscopy Made Easy package (SME, Valenti & Piskunov, 1996; Piskunov &
Valenti, 2017) to the co-added high signal-to-noise HARPS spectrum. SME uses
grids of 1-D LTE stellar models to iteratively calculate synthetic spectra
where by following a minimizing strategy each synthetic spectrum is compared
to the normalized co-added spectrum observed data. The process is repeated by
changing input parameters until we obtain a match for the line profiles of
individual diagnostic lines, leading to values for Teff, $\log$ $g$,
metallicity, and $v$ sin $i$. The turbulent velocities are calculated
according to the empirical relations of Bruntt et al. (2010) and Doyle et al.
(2014) and are held fixed in the determination of the other parameters. We
refer to Fridlund et al. (2020) for more details and references. With this, we
found a slightly cooler T${}_{\text{eff}}$ = 5182 $\pm$ 45 K, while the rest
of the calculated values $\log$ $g$ = 4.25 $\pm$ 0.07, Fe/H = $-$0.2 $\pm$
0.07, $v$ sin $i$ = 2.9 $\pm$ 0.35 km s-1, Vmic = 0.85 $\pm$ 0.1 km s-1
(fixed) and Vmac = 0.9 $\pm$ 0.4 km s-1, are in good agreement with the
respective results of Sect. 3.1 presented in Table 3. Finally, the result of
the independent SED fitting of TOI-220 described in Sect. 3.3.1 is shown in
Fig. 13.

Figure 13: Independent SED fitting of TOI-220 using Gaia (magenta squares),
2MASS (green triangles) and WISE magnitudes (red circles). The blue solid line
represents the fitted theoretical stellar model. See Sect.3.3 for details.

##  Appendix B Priors of the Bayesian analysis

In Table 6 we present the list of the prior distributions used for each
parameter fitted with pastis code in Sect. 3.3.

Table 6: List of the prior distributions used in pastis analysis: $\mathcal{N}(\mu,\sigma^{2})$: Normal with mean $\mu$ and width $\sigma$; $\mathcal{U}(a,b)$: Uniform dist. between $a$ and $b$; $\mathcal{T}(\mu,\sigma^{2},a,b)$: Truncated normal distribution with mean $\mu$, width $\sigma$ between $a$ and $b$; and $\mathcal{S}(a,b)$: Sine dist. between $a$ and $b$. (*): parameters included in the RV drift modelling. Stellar parameters | distribution
---|---
Effective Temperature, T${}_{\text{eff}}$ [K] | $\mathcal{N}(5300,100)$
Surface gravity, $\log$ $g$ [cgs] | $\mathcal{N}(4.5,0.1)$
Metallicity, [M/H] [dex] | $\mathcal{N}(-0.2,0.05)$
Distance, d [pc] | $\mathcal{N}(90.54,5)$
E(B$-$V) [mag] | $\mathcal{U}(0,1)$
Systemic RV, v0 [m s-1] | $\mathcal{U}(20,30)$
Reference Time RV [BJD_TDB] (*) | 2458450
RV drift lin. coeff. [m s-1 d-1] (*) | $\mathcal{U}(-50,50)$
RV drift quad. coeff. [m s-1 d-2] (*) | $\mathcal{U}(-50,50)$
Planetary parameters |
Orbital period, P [d] | $\mathcal{N}(10.6,0.5)$
Reference transit time, T0 [BJD_TDB] | $\mathcal{N}(2458335.9026,0.1)$
Planet-to-star radius ratio, R${}_{\text{p}}$/R${}_{\text{s}}$ | $\mathcal{U}(0.029,0.04)$
RV semi-amplitude, K [m s-1] | $\mathcal{U}(0,10)$
Orbital inclination, $i$ [°] | $\mathcal{S}(85,90)$
Orbital eccentricity, $e$ | $\mathcal{T}(0,0.32,0,1)$
Argument of periastron, $\omega$ [$\degr$] | $\mathcal{U}(0,360)$
Instrument parameters |
TESS contamination [%] | $\mathcal{T}(0,0.005,0,1)$
TESS jitter [ppm] | $\mathcal{U}(0.0,0.1)$
TESS out-of-trasit flux | $\mathcal{U}(0.99,1.01)$
HARPS jitter [km s-1] | $\mathcal{U}(0.0,0.1)$
SED jitter [mag] | $\mathcal{U}(0,1)$

##  Appendix C Search for transits of planet-c in TESS light curve

As mentioned in Sect. 2, by the end of the writing of this manuscript two new
sectors (27 and 28) from the second pass of TESS in the Southern hemisphere
became available. These new data extend the photometric baseline for
additional 43 days to the initial 311 days of the first sectors (after a gap
of 395 days), allowing for a search of evidence of transits of additional
planet in longer orbital periods. For this, we used the Box Least Squares
(BLS) periodogram method over the TOI-220 full TESS light curve, i.e. the
photometric time series containing the data of all the available sectors. We
identified and masked the transits of TOI-220 $b$ at the orbital period of
10.69 d before conducting a wide search of transit-like features in a wide
range of periods and durations adopting the minimun number of events in the
light curve as two. It is worth mentioning that a photometric feature at
BTJD$\sim$1417 was consistently identified as the first event by the BLS
method. We confirmed that this event correspond to a known systematic spike
reported in the TESS data release notes of the sector 4. After removing it, we
found no significant peaks in the BLS. All the TESS light curves were also
visually inspected searching for individual transits but only very low SNR
features were identified. Therefore, there is no significant evidence of
transits of an additional planet in the TESS data.

##  Appendix D Statistics and RV residuals of the 2 fitted models

In Table 7 we reported different statistical metrics we used to compare the
models analyzed in Sect. 3.3.2: the single planet model with and without a
radial velocity drift. We show the likelihood of each model and the
$\Delta$AIC (which favours the inclusion of the RV drift) as well as the RMS
of the radial velocity residuals and the Anderson-Darling test to check for
the normality of the residuals. See detailed discussion in Sect. 3.3.2.

Table 7: Statistical comparison of the 2 models explored in this work.  Parameter | 1 planet | 1 planet + RV drift
---|---|---
$\log$ L | 55474 | 55484
$\Delta$AIC | 15 | 0
RV residuals RMS [m s-1] | 1.93 | 1.69
A-D test | 0.580 | 0.294
$\log$ L: log of the model likelihood.
AIC: Akaike information criterion.
A-D: Anderson-Darling test, to be compared with a critical value of
0.547, corresponding to a 15 % significance for normality rejection.

##  Appendix E Mass constraints of a hypothetical companion based on the RV
drift

We note that the RV drift defined by the linear and quadratic coefficients of
Table 3, which had been defined against the epoch of the first RV point
(2458440.752469 BJD), can be replaced by a purely quadratic expression, given
by $RV_{dr}=c_{2}(t-T_{0,dr})^{2}+k$, where $c_{2}$ is the quadratic
coefficient of Table 3, $k$ is an offset without physical implications, and
$T_{0,dr}$ defines the ’vertex’ of the parabolic function. With $c_{1}$ being
the linear coefficient of the RV drift, the time of the vertex relative to the
first RV-point is given by: $t_{v}=-c_{1}/(2c_{2})=127.18$ d, which results in
an absolute value of $T_{0,dr}=2458567.933677$ BJD. This conversion permits us
to describe the RV drift as a consequence of a hypothetical circular Keplerian
orbit, with the drift given by:

$y=-K\cos{\frac{2\pi t}{P}},$ (2)

where $K$, $P$ and $t$ are the RV-amplitude, the period, and the time relative
to $T_{0,dr}$. Considering that the second order Taylor expansion of $y=a\
\cos{bx}$ is given by $y=a-\frac{1}{2}x^{2}(ab^{2})+O(x^{4})$, the RVs of the
Keplerian orbit can be approximated to second order by:

$y^{\prime}=-K+[\frac{2\pi^{2}K}{P^{2}}]t^{2},$ (3)

where the term in brackets corresponds now to the RV-drift’s quadratic
coefficient of Table 3. Hence:

$c_{2}=\frac{2\pi^{2}K}{P^{2}}=0.000149(31)\,[\text{m}\,\text{s}^{-1}\,\text{d}^{-2}]$
(4)

For a given value of $P$, we may now solve this for $K$, and – using the
stellar mass indicated in Table 3 – derive the mass of the hypothetical
orbiter. This leads to the mass limits shown in Table 8. A lower limit of 750
days has been set, which is given by the validity of the Taylor approximation,
which gets worse for shorter orbital periods. We note that only periods of
less then $\approx$10000 d or 30 years lead to realistic masses, since longer
periods correspond to stellar mass components that would have been detected by
other means; e.g. through the SED of the target.

Table 8: Mass constraints based on the quadratic RV drift. $K$, $Kmin$ and $Kmax$ are the RV amplitudes corresponding to equation 4 solved for $K$, with the lower and upper errors set by the errors of $c_{2}$. Mpl is the orbiting object’s mass in units of Jupiter masses, based on the central $K$ value and a stellar mass of 0.828 M☉. P [d] |  $K_{min}$ [m s-1] |  $K$ [m s-1] |  $K_{max}$ [m s-1] | Mpl [MJup]
---|---|---|---|---
750 | 3.36 | 4.25 | 5.13 | 0.17
1000 | 5.98 | 7.55 | 9.12 | 0.33
3000 | 53.80 | 67.94 | 82.07 | 4.25
10000 | 597.80 | 754.84 | 911.90 | 70.5
30000 | 5380.16 | 6793.59 | 8207.02 | 916

##  Appendix F Timing analysis of TOI-220 $b$

In Table 9 we reported the fitted transit time for each of the transits
analyzed in Sect. 3.4. The transit ID is the same used in Table 1. The results
of the two LCO transits (Fig. 14) are also shown. We reported the difference
between these transit times and the estimated TOI-220 $b$ ephemeris equation
(Eq. 1) which are presented in Fig. 8.

Transit ID | T${}_{\text{C}}$ [BJD_TBD] | +$\sigma$ | -$\sigma$ | O$-$C [min]
---|---|---|---|---
S01a | 2458335.8997 | 0.0052 | 0.0083 | -3.46
S01b | 2458346.5996 | 0.0089 | 0.0089 | 3.22
S02a | 2458357.2865 | 0.0054 | 0.0054 | -8.82
S02b | 2458378.6835 | 0.0057 | 0.0100 | 0.50
S04a | 2458421.4632 | 0.0034 | 0.0034 | -1.46
S04b | 2458432.1539 | 0.0076 | 0.0076 | -8.03
S05a | 2458442.8599 | 0.0040 | 0.0040 | 7.43
S05b | 2458453.5537 | 0.0041 | 0.0041 | 5.32
S06a | 2458474.9390 | 0.0042 | 0.0042 | -2.21
S06b | 2458485.6384 | 0.0058 | 0.0058 | 3.75
S07a | 2458496.3270 | 0.0041 | 0.0041 | -5.85
S07b | 2458507.0268 | 0.0049 | 0.0049 | 0.69
S08 | 2458528.4135 | 0.0031 | 0.0031 | -4.83
S09 | 2458549.8031 | 0.0051 | 0.0051 | -6.16
S10 | 2458592.5848 | 0.0066 | 0.0046 | -5.24
S12a | 2458635.3685 | 0.0028 | 0.0028 | -1.43
S12b | 2458646.0667 | 0.0052 | 0.0052 | 2.80
LCO1 | 2458528.420 | 0.024 | 0.024 | 4.53
LCO2 | 2458838.5808 | 0.0042 | 0.0042 | 1.86
S27a | 2459041.7915 | 0.0037 | 0.0037 | 2.85
S27b | 2459052.4835 | 0.0041 | 0.0041 | -1.86
S28a | 2459063.1839 | 0.0033 | 0.0033 | 5.54
S28b | 2459084.5670 | 0.0093 | 0.0093 | -5.16
Table 9: Transit mid-times obtained from individual fitting and their
respective timing residuals (Sect. 3.4) using P=10.695264(87) d and
T0=2458335.9021(14) [BJD_TBD] (Sect.3.3.2). Figure 14: Two transits of TOI-220
$b$ obtained with telescopes of the LCOGT network. The solid curves correspond
to the fitted model of the timing analysis of the system (Sect 3.4) and are
labelled with the corresponding ID of Table 9.

##  Appendix G Radial velocity data

In Tables 10 and 12 we report the radial velocity measurements together with
the stellar activity indicators used in these work derived from the HARPS DRS
and SERVAL, respectively (see Sect. 2.2).

Table 10: HARPS DRS radial velocity measurements and activity indicators of TOI-220. Exposure time and signal-to-noise ratio per pixel at 550 nm are given in the last two columns. BJD_TDB | RV | $\sigma_{\text{RV}}$ | BIS | FWHM | CCF |  $\log$ R${}^{\prime}_{\mathrm{HK}}$ | $\sigma_{\text{$\log$\,R${}^{\prime}_{\mathrm{HK}}$}}$ | EXPTIME | SNR (550 nm)
---|---|---|---|---|---|---|---|---|---
$[$d] | [km s-1] | [km s-1] | [km s-1] | [km s-1] | CONTRAST |  |  | [s] | per pixel
2458440.708866 | 26.4650 | 0.0010 | -0.0273 | 6.1504 | 40.3215 | -5.0453 | 0.0102 | 1800 | 74.8
2458440.800232 | 26.4658 | 0.0010 | -0.0233 | 6.1550 | 40.3239 | -5.0352 | 0.0114 | 1800 | 73.4
2458441.758120 | 26.4637 | 0.0010 | -0.0211 | 6.1550 | 40.2942 | -5.0432 | 0.0111 | 1800 | 73.8
2458441.778259 | 26.4620 | 0.0009 | -0.0253 | 6.1559 | 40.2737 | -5.0481 | 0.0080 | 1800 | 83.0
2458442.807269 | 26.4601 | 0.0009 | -0.0254 | 6.1487 | 40.3025 | -5.0262 | 0.0104 | 1800 | 80.2
2458442.828449 | 26.4621 | 0.0010 | -0.0260 | 6.1543 | 40.3186 | -5.0557 | 0.0122 | 1800 | 79.9
2458443.686568 | 26.4573 | 0.0009 | -0.0256 | 6.1541 | 40.2811 | -5.0555 | 0.0101 | 1800 | 78.1
2458443.775781 | 26.4572 | 0.0010 | -0.0267 | 6.1510 | 40.2879 | -5.0614 | 0.0119 | 1800 | 71.4
2458444.809444 | 26.4567 | 0.0015 | -0.0265 | 6.1551 | 40.2335 | -5.0456 | 0.0181 | 1800 | 50.3
2458446.782081 | 26.4577 | 0.0008 | -0.0211 | 6.1489 | 40.2909 | -5.0626 | 0.0092 | 1800 | 90.4
2458446.830311 | 26.4568 | 0.0009 | -0.0252 | 6.1547 | 40.2613 | -5.0637 | 0.0111 | 1800 | 89.9
2458447.738845 | 26.4586 | 0.0008 | -0.0237 | 6.1512 | 40.2769 | -5.0318 | 0.0082 | 1800 | 87.4
2458447.834355 | 26.4585 | 0.0009 | -0.0277 | 6.1535 | 40.2766 | -5.0801 | 0.0114 | 1800 | 81.7
2458451.730670 | 26.4629 | 0.0008 | -0.0270 | 6.1515 | 40.3034 | -5.0619 | 0.0086 | 1800 | 92.5
2458451.805994 | 26.4611 | 0.0009 | -0.0250 | 6.1557 | 40.2822 | -5.0528 | 0.0118 | 1800 | 83.3
2458452.702375 | 26.4586 | 0.0008 | -0.0249 | 6.1487 | 40.3235 | -5.0401 | 0.0081 | 1500 | 88.2
2458452.782399 | 26.4587 | 0.0008 | -0.0268 | 6.1491 | 40.3037 | -5.0383 | 0.0098 | 1800 | 90.7
2458453.631164 | 26.4596 | 0.0009 | -0.0255 | 6.1596 | 40.2811 | -5.0500 | 0.0090 | 1800 | 83.5
2458453.773665 | 26.4572 | 0.0009 | -0.0216 | 6.1523 | 40.3094 | -5.0261 | 0.0093 | 1500 | 83.5
2458454.627488 | 26.4527 | 0.0012 | -0.0228 | 6.1487 | 40.3376 | -5.0787 | 0.0169 | 1500 | 61.2
2458454.750359 | 26.4528 | 0.0014 | -0.0269 | 6.1542 | 40.2969 | -5.0989 | 0.0200 | 1800 | 53.3
2458455.673973 | 26.4538 | 0.0012 | -0.0219 | 6.1500 | 40.3438 | -5.0740 | 0.0158 | 1500 | 60.4
2458455.790907 | 26.4516 | 0.0012 | -0.0247 | 6.1566 | 40.3110 | -5.0154 | 0.0146 | 1800 | 62.2
2458467.755644 | 26.4523 | 0.0009 | -0.0251 | 6.1536 | 40.3024 | -5.0391 | 0.0109 | 1500 | 80.6
2458468.701619 | 26.4530 | 0.0010 | -0.0242 | 6.1563 | 40.3013 | -5.0400 | 0.0101 | 1500 | 76.3
2458469.796343 | 26.4550 | 0.0012 | -0.0271 | 6.1548 | 40.2970 | -5.0806 | 0.0184 | 1500 | 65.4
2458471.743546 | 26.4612 | 0.0011 | -0.0286 | 6.1537 | 40.3077 | -5.0479 | 0.0144 | 1500 | 69.9
2458473.769591 | 26.4618 | 0.0008 | -0.0210 | 6.1545 | 40.2550 | -5.0396 | 0.0090 | 1800 | 91.0
2458473.790575 | 26.4602 | 0.0008 | -0.0206 | 6.1549 | 40.2674 | -5.0433 | 0.0103 | 1800 | 90.8
2458475.700867 | 26.4556 | 0.0010 | -0.0263 | 6.1564 | 40.2620 | -5.0359 | 0.0112 | 1500 | 75.3
2458477.683346 | 26.4526 | 0.0010 | -0.0214 | 6.1553 | 40.2887 | -5.0420 | 0.0107 | 1800 | 78.4
2458478.764436 | 26.4519 | 0.0010 | -0.0224 | 6.1545 | 40.2691 | -5.0313 | 0.0123 | 1800 | 81.5
2458479.671230 | 26.4565 | 0.0011 | -0.0252 | 6.1502 | 40.2764 | -5.0191 | 0.0115 | 1800 | 66.7
2458480.721428 | 26.4585 | 0.0008 | -0.0259 | 6.1560 | 40.2723 | -5.0374 | 0.0088 | 1800 | 90.2
2458484.774635 | 26.4585 | 0.0010 | -0.0226 | 6.1556 | 40.2878 | -4.9952 | 0.0122 | 1500 | 74.8
2458486.707656 | 26.4512 | 0.0015 | -0.0257 | 6.1485 | 40.3665 | -5.0866 | 0.0265 | 1500 | 52.9
2458487.719322 | 26.4529 | 0.0011 | -0.0192 | 6.1580 | 40.2910 | -5.0331 | 0.0144 | 1500 | 69.9
2458488.654032 | 26.4539 | 0.0012 | -0.0229 | 6.1566 | 40.3144 | -5.0545 | 0.0145 | 1500 | 60.1
2458488.794703 | 26.4516 | 0.0012 | -0.0229 | 6.1561 | 40.3274 | -5.0834 | 0.0222 | 1500 | 68.0
2458489.695779 | 26.4506 | 0.0025 | -0.0164 | 6.1595 | 40.3359 | -5.1050 | 0.0572 | 1500 | 34.6
2458489.817157 | 26.4522 | 0.0024 | -0.0165 | 6.1478 | 40.3351 | -5.2218 | 0.0715 | 1500 | 36.1
2458490.775790 | 26.4522 | 0.0014 | -0.0237 | 6.1567 | 40.3240 | -5.1718 | 0.0303 | 1500 | 58.0
2458491.667815 | 26.4571 | 0.0013 | -0.0252 | 6.1522 | 40.2983 | -4.9942 | 0.0147 | 1500 | 60.4
2458491.787386 | 26.4577 | 0.0017 | -0.0199 | 6.1502 | 40.2760 | -5.0854 | 0.0313 | 1500 | 48.0
2458501.597810 | 26.4573 | 0.0013 | -0.0258 | 6.1493 | 40.2993 | -5.0926 | 0.0183 | 1500 | 56.1
2458501.714141 | 26.4537 | 0.0014 | -0.0271 | 6.1552 | 40.2865 | -5.0426 | 0.0208 | 1500 | 54.5
2458502.585805 | 26.4593 | 0.0011 | -0.0274 | 6.1552 | 40.2717 | -5.0338 | 0.0130 | 1500 | 65.8
2458502.714208 | 26.4582 | 0.0011 | -0.0206 | 6.1536 | 40.3083 | -5.0889 | 0.0159 | 1500 | 73.2
2458504.675128 | 26.4600 | 0.0012 | -0.0258 | 6.1602 | 40.2833 | -5.0751 | 0.0170 | 1500 | 65.3
2458505.654443 | 26.4601 | 0.0010 | -0.0212 | 6.1560 | 40.2635 | -5.0220 | 0.0109 | 1500 | 72.6
2458506.564996 | 26.4558 | 0.0009 | -0.0261 | 6.1547 | 40.2964 | -5.0245 | 0.0083 | 1500 | 83.5
2458506.726419 | 26.4538 | 0.0011 | -0.0222 | 6.1567 | 40.2421 | -5.1025 | 0.0181 | 1500 | 75.1
2458507.570571 | 26.4557 | 0.0014 | -0.0259 | 6.1586 | 40.3063 | -5.0686 | 0.0203 | 1500 | 55.0
2458507.729911 | 26.4560 | 0.0014 | -0.0248 | 6.1560 | 40.2585 | -5.1037 | 0.0263 | 1500 | 58.5
2458508.653091 | 26.4533 | 0.0015 | -0.0202 | 6.1525 | 40.3208 | -5.0814 | 0.0274 | 1800 | 54.4
2458508.673450 | 26.4530 | 0.0015 | -0.0162 | 6.1554 | 40.2769 | -5.0783 | 0.0275 | 1800 | 55.3
2458514.784388 | 26.4608 | 0.0012 | -0.0229 | 6.1629 | 40.2459 | -5.0436 | 0.0185 | 1800 | 69.8
2458515.753041 | 26.4586 | 0.0016 | -0.0213 | 6.1576 | 40.2386 | -5.0440 | 0.0302 | 1240 | 50.8
2458516.577968 | 26.4592 | 0.0010 | -0.0270 | 6.1551 | 40.3106 | -5.0600 | 0.0126 | 1500 | 79.0
2458516.748836 | 26.4584 | 0.0015 | -0.0263 | 6.1649 | 40.2796 | -5.1390 | 0.0314 | 1500 | 55.9
2458517.578103 | 26.4552 | 0.0011 | -0.0230 | 6.1566 | 40.3041 | -5.0307 | 0.0140 | 1500 | 69.1
Continued |  |  |  |  |  |  |  |  |
Table 11: continued

HARPS DRS radial velocity measurements and activity indicators of TOI-220.
Exposure time and signal-to-noise ratio per pixel at 550 nm are given in the
last two columns.  BJD_TDB RV $\sigma_{\text{RV}}$ BIS FWHM CCF $\log$
R${}^{\prime}_{\mathrm{HK}}$
$\sigma_{\text{$\log$\,R${}^{\prime}_{\mathrm{HK}}$}}$ EXPTIME SNR (550 nm)
$[$d] [km s-1] [km s-1] [km s-1] [km s-1] CONTRAST [s] per pixel
2458519.545756 26.4548 0.0015 -0.0236 6.1538 40.3182 -5.0835 0.0255 1500 52.5
2458519.730269 26.4523 0.0029 -0.0186 6.1508 40.2656 -5.2730 0.1117 1500 31.6
2458520.745206 26.4550 0.0021 -0.0245 6.1680 40.2821 -5.1150 0.0508 1500 41.5
2458521.549624 26.4544 0.0013 -0.0215 6.1534 40.3222 -5.0607 0.0192 1500 59.9
2458522.730498 26.4573 0.0016 -0.0215 6.1522 40.3176 -5.1530 0.0509 1500 55.9
2458524.738624 26.4591 0.0012 -0.0232 6.1538 40.3246 -5.0988 0.0283 1500 69.5
2458528.634749 26.4563 0.0015 -0.0292 6.1511 40.3093 -5.1221 0.0343 1500 53.7
2458529.725206 26.4513 0.0017 -0.0294 6.1658 40.1514 -4.9232 0.0266 1500 51.2
2458530.732839 26.4519 0.0016 -0.0271 6.1521 40.3033 -5.2255 0.0526 1500 54.9
2458531.549651 26.4538 0.0009 -0.0238 6.1536 40.3071 -5.0648 0.0120 1800 80.7
2458535.589291 26.4626 0.0010 -0.0252 6.1534 40.2066 -4.9657 0.0097 1800 79.7
2458537.672021 26.4609 0.0010 -0.0262 6.1585 40.2762 -5.0910 0.0222 1800 82.0
2458538.689271 26.4560 0.0013 -0.0312 6.1611 40.2935 -5.1449 0.0319 1800 66.9
2458539.678801 26.4530 0.0011 -0.0244 6.1564 40.2975 -5.0551 0.0220 1800 76.0
2458540.700230 26.4541 0.0014 -0.0254 6.1546 40.3270 -5.1352 0.0364 1800 63.8
2458542.669892 26.4534 0.0011 -0.0263 6.1511 40.3212 -5.1218 0.0237 1800 80.4
2458543.677293 26.4538 0.0010 -0.0270 6.1592 40.3075 -5.1119 0.0218 1800 89.6
2458546.690397 26.4611 0.0015 -0.0279 6.1612 40.3362 -5.1225 0.0379 1800 57.7
2458547.561096 26.4596 0.0012 -0.0283 6.1577 40.3057 -5.0859 0.0208 1800 70.5
2458548.556934 26.4595 0.0015 -0.0190 6.1614 40.2781 -5.0799 0.0259 1800 55.3
2458549.552540 26.4565 0.0009 -0.0240 6.1554 40.3031 -5.0554 0.0135 1800 88.0
2458550.576618 26.4521 0.0009 -0.0246 6.1621 40.2942 -5.0500 0.0152 1800 88.9
2458554.664806 26.4555 0.0020 -0.0280 6.1579 40.3187 -5.0843 0.0476 1800 44.5
2458555.650955 26.4610 0.0011 -0.0202 6.1623 40.3268 -5.1202 0.0256 1800 75.4
2458562.535601 26.4532 0.0012 -0.0251 6.1541 40.1392 -5.0067 0.0142 1800 69.5
2458586.560780 26.4545 0.0012 -0.0288 6.1560 40.3136 -5.0919 0.0252 1800 72.1
2458591.490221 26.4594 0.0010 -0.0267 6.1569 40.2479 -5.0704 0.0163 1800 84.4
2458611.494962 26.4593 0.0015 -0.0273 6.1592 40.2856 -5.0685 0.0292 1800 60.8
2458728.879893 26.4661 0.0011 -0.0235 6.1538 40.2937 -5.0360 0.0131 1800 76.9
2458767.767044 26.4554 0.0012 -0.0270 6.1482 40.1839 -5.0234 0.0118 2100 65.9

Table 12: HARPS SERVAL activity indicators of TOI-220. BJD_TDB | dLW | $\sigma_{\text{dLW}}$ | CRX | $\sigma_{\text{CRX}}$ | H$\alpha$ | $\sigma_{\text{H$\alpha$}}$ | Na D | $\sigma_{\text{Na D}}$
---|---|---|---|---|---|---|---|---
$[$d] |  |  | [m s-1] | [m s-1] |  |  |  |
2458440.708866 | -0.2623 | 1.4290 | -5.8768 | 11.5422 | 0.4656 | 0.0010 | 0.2665 | 0.0012
2458440.800232 | -4.9625 | 1.5490 | 6.7761 | 11.0373 | 0.4668 | 0.0010 | 0.2670 | 0.0012
2458441.758120 | -0.3565 | 1.3821 | -1.7498 | 10.5452 | 0.4678 | 0.0011 | 0.2648 | 0.0012
2458441.778259 | 1.3307 | 1.1907 | 7.7788 | 9.8335 | 0.4675 | 0.0010 | 0.2669 | 0.0011
2458442.807269 | -0.7192 | 1.3148 | 13.7782 | 9.0388 | 0.4691 | 0.0010 | 0.2604 | 0.0011
2458442.828449 | -2.5532 | 1.2666 | 20.1963 | 9.1391 | 0.4644 | 0.0009 | 0.2596 | 0.0011
2458443.686568 | 2.2460 | 1.3634 | -7.9982 | 10.3545 | 0.4654 | 0.0010 | 0.2678 | 0.0011
2458443.775781 | 2.9989 | 1.3117 | -4.4235 | 11.2185 | 0.4667 | 0.0011 | 0.2664 | 0.0012
2458444.809444 | 3.6119 | 2.0043 | 2.4141 | 13.7423 | 0.4705 | 0.0016 | 0.2609 | 0.0018
2458446.782081 | 0.0413 | 1.0744 | 0.8902 | 9.4182 | 0.4691 | 0.0008 | 0.2610 | 0.0010
2458446.830311 | 3.3628 | 1.2715 | -7.4150 | 10.0903 | 0.4681 | 0.0008 | 0.2610 | 0.0010
2458447.738845 | 0.6403 | 1.1213 | 0.1112 | 11.5124 | 0.4648 | 0.0009 | 0.2603 | 0.0010
2458447.834355 | 0.6680 | 1.4356 | -2.1942 | 11.0709 | 0.4663 | 0.0009 | 0.2604 | 0.0011
2458451.730670 | -0.0467 | 1.1565 | 6.0690 | 8.4936 | 0.4657 | 0.0008 | 0.2607 | 0.0009
2458451.805994 | 1.0959 | 1.3075 | 10.4416 | 9.3948 | 0.4649 | 0.0009 | 0.2611 | 0.0010
2458452.702375 | -4.0832 | 1.2065 | -13.0851 | 7.1234 | 0.4647 | 0.0009 | 0.2615 | 0.0010
2458452.782399 | -2.7432 | 1.2199 | -4.6426 | 6.7290 | 0.4642 | 0.0008 | 0.2597 | 0.0009
2458453.631164 | -0.7047 | 1.0873 | -2.9315 | 8.2828 | 0.4656 | 0.0009 | 0.2620 | 0.0011
2458453.773665 | -1.1784 | 1.1849 | -11.5157 | 8.6985 | 0.4646 | 0.0009 | 0.2622 | 0.0010
2458454.627488 | -6.1300 | 1.7282 | 13.0497 | 9.5861 | 0.4664 | 0.0012 | 0.2596 | 0.0014
2458454.750359 | -1.1140 | 2.5133 | 10.3401 | 13.2155 | 0.4679 | 0.0014 | 0.2617 | 0.0017
2458455.673973 | -4.3860 | 1.6552 | 0.0656 | 9.5256 | 0.4649 | 0.0013 | 0.2591 | 0.0015
2458455.790907 | -0.4042 | 1.7392 | 8.1142 | 10.3294 | 0.4678 | 0.0012 | 0.2686 | 0.0014
2458467.755644 | 0.0746 | 1.2988 | 0.2065 | 8.0561 | 0.4688 | 0.0009 | 0.2618 | 0.0011
2458468.701619 | -1.4562 | 1.3661 | 11.2744 | 9.5247 | 0.4670 | 0.0010 | 0.2618 | 0.0012
2458469.796343 | -1.7262 | 1.4104 | -5.0228 | 10.2855 | 0.4640 | 0.0011 | 0.2618 | 0.0013
2458471.743546 | -0.8041 | 1.4308 | -4.8355 | 10.5433 | 0.4666 | 0.0011 | 0.2586 | 0.0012
2458473.769591 | 2.2120 | 0.9652 | -11.8209 | 8.3775 | 0.4665 | 0.0008 | 0.2613 | 0.0010
2458473.790575 | 1.0648 | 1.2348 | -21.6860 | 8.0858 | 0.4656 | 0.0008 | 0.2668 | 0.0009
2458475.700867 | 4.6992 | 1.3896 | 8.9426 | 9.7111 | 0.4637 | 0.0010 | 0.2592 | 0.0012
2458477.683346 | 1.4648 | 1.2915 | 7.2851 | 7.8859 | 0.4664 | 0.0010 | 0.2667 | 0.0011
2458478.764436 | -0.6453 | 1.4899 | -4.9377 | 8.2332 | 0.4655 | 0.0009 | 0.2686 | 0.0011
2458479.671230 | -0.8130 | 1.7958 | 4.7311 | 10.6195 | 0.4703 | 0.0012 | 0.2661 | 0.0013
2458480.721428 | 2.7656 | 1.0797 | -13.2663 | 8.3028 | 0.4663 | 0.0008 | 0.2659 | 0.0010
2458484.774635 | 0.3673 | 1.5322 | 0.8046 | 9.6450 | 0.4645 | 0.0010 | 0.2612 | 0.0012
2458486.707656 | -3.1221 | 1.8534 | -14.3388 | 11.9351 | 0.4633 | 0.0014 | 0.2587 | 0.0017
2458487.719322 | 1.1626 | 1.6061 | 8.9141 | 9.9225 | 0.4673 | 0.0011 | 0.2610 | 0.0013
2458488.654032 | -2.4478 | 1.6747 | 5.4204 | 9.9891 | 0.4653 | 0.0013 | 0.2635 | 0.0015
2458488.794703 | -3.6027 | 1.6175 | -3.4279 | 8.9609 | 0.4658 | 0.0011 | 0.2627 | 0.0013
2458489.695779 | -4.0812 | 3.2346 | 8.1978 | 20.4807 | 0.4661 | 0.0021 | 0.2585 | 0.0027
2458489.817157 | 1.4793 | 3.1791 | 35.1790 | 16.5534 | 0.4573 | 0.0020 | 0.2648 | 0.0026
2458490.775790 | -1.9411 | 1.9919 | 7.9932 | 11.3483 | 0.4641 | 0.0012 | 0.2607 | 0.0015
2458491.667815 | -1.8741 | 1.9072 | -27.1674 | 10.1383 | 0.4719 | 0.0012 | 0.2612 | 0.0015
2458491.787386 | -1.3321 | 2.4345 | -0.3721 | 13.7161 | 0.4666 | 0.0015 | 0.2677 | 0.0018
2458501.597810 | -2.3896 | 1.7019 | -19.7716 | 12.1489 | 0.4692 | 0.0014 | 0.2673 | 0.0016
2458501.714141 | 0.0764 | 1.8841 | -3.7394 | 10.5970 | 0.4663 | 0.0014 | 0.2596 | 0.0016
2458502.585805 | -0.1945 | 1.7044 | -6.8271 | 9.7077 | 0.4652 | 0.0012 | 0.2662 | 0.0013
2458502.714208 | -1.9466 | 1.5951 | -1.6920 | 8.8068 | 0.4656 | 0.0010 | 0.2603 | 0.0012
2458504.675128 | -3.1907 | 1.5990 | -9.1703 | 10.9906 | 0.4645 | 0.0012 | 0.2599 | 0.0014
2458505.654443 | 1.9881 | 1.5946 | -6.0949 | 8.9858 | 0.4649 | 0.0011 | 0.2605 | 0.0012
2458506.564996 | -0.4999 | 1.2270 | -4.2423 | 8.2120 | 0.4657 | 0.0009 | 0.2584 | 0.0011
2458506.726419 | 2.2123 | 1.6614 | -19.0888 | 9.1581 | 0.4646 | 0.0010 | 0.2610 | 0.0012
2458507.570571 | -0.8163 | 2.1560 | 10.4649 | 15.1414 | 0.4643 | 0.0015 | 0.2610 | 0.0017
2458507.729911 | 4.2407 | 2.0254 | -7.7070 | 10.3599 | 0.4634 | 0.0013 | 0.2596 | 0.0015
2458508.653091 | 0.6389 | 1.9808 | 35.3264 | 12.6350 | 0.4602 | 0.0014 | 0.2590 | 0.0017
2458508.673450 | 1.6420 | 1.9984 | 22.2776 | 14.2334 | 0.4580 | 0.0014 | 0.2585 | 0.0016
2458514.784388 | 7.0675 | 1.4771 | -0.6879 | 10.9105 | 0.4560 | 0.0010 | 0.2667 | 0.0013
2458515.753041 | 8.4969 | 2.3699 | -13.9389 | 13.3166 | 0.4573 | 0.0015 | 0.2661 | 0.0018
2458516.577968 | -2.3914 | 1.5421 | -24.5056 | 9.4269 | 0.4591 | 0.0010 | 0.2653 | 0.0011
2458516.748836 | 3.8234 | 2.0109 | -4.3809 | 12.7091 | 0.4593 | 0.0014 | 0.2638 | 0.0016
2458517.578103 | -2.6623 | 1.2879 | -18.1996 | 9.1335 | 0.4581 | 0.0011 | 0.2682 | 0.0013
Continued |  |  |  |  |  |  |  |
Table 13: continued

HARPS SERVAL activity indicators of TOI-220.  BJD_TDB dLW
$\sigma_{\text{dLW}}$ CRX $\sigma_{\text{CRX}}$ H$\alpha$
$\sigma_{\text{H$\alpha$}}$ Na D $\sigma_{\text{Na D}}$ $[$d] [m s-1] [m s-1]
2458519.545756 -2.7058 1.7916 -0.4067 11.4625 0.4669 0.0015 0.2652 0.0017
2458519.730269 2.1747 4.0675 -18.2779 19.2282 0.4634 0.0024 0.2696 0.0031
2458520.745206 1.2080 2.5333 -13.1655 15.8645 0.4589 0.0017 0.2636 0.0022
2458521.549624 -0.3015 1.6485 -5.2641 10.4197 0.4608 0.0013 0.2682 0.0015
2458522.730498 -0.9532 2.2842 27.7059 13.1662 0.4589 0.0013 0.2598 0.0016
2458524.738624 -1.2092 1.7960 -10.3374 11.4734 0.4593 0.0011 0.2622 0.0013
2458528.634749 -1.0433 1.9821 -8.1356 10.8765 0.4671 0.0014 0.2639 0.0017
2458529.725206 5.8613 2.6058 -5.5268 13.0208 0.4623 0.0015 0.2629 0.0018
2458530.732839 3.2712 2.0613 -26.2329 13.9351 0.4638 0.0014 0.2629 0.0016
2458531.549651 1.3428 1.2768 -6.5268 9.4249 0.4632 0.0010 0.2630 0.0011
2458535.589291 9.7591 1.3480 -3.8071 8.7267 0.4649 0.0010 0.2609 0.0011
2458537.672021 1.5254 1.2464 -3.3699 9.7638 0.4674 0.0009 0.2659 0.0011
2458538.689271 -0.6371 1.9865 15.3358 10.8076 0.4588 0.0012 0.2667 0.0013
2458539.678801 -0.8648 1.6380 -8.4122 10.2376 0.4589 0.0010 0.2644 0.0012
2458540.700230 -3.6376 1.8298 -11.8585 11.4789 0.4622 0.0012 0.2636 0.0014
2458542.669892 -2.4210 1.4654 6.2483 9.7577 0.4602 0.0010 0.2644 0.0011
2458543.677293 -1.3194 1.3547 -10.0779 10.2875 0.4590 0.0009 0.2672 0.0010
2458546.690397 -3.4933 2.0798 -16.0068 13.8284 0.4601 0.0013 0.2658 0.0016
2458547.561096 -2.6385 1.7150 18.2028 12.7411 0.4627 0.0011 0.2661 0.0013
2458548.556934 -1.0987 1.8158 6.1270 12.1296 0.4673 0.0015 0.2676 0.0017
2458549.552540 -0.2272 1.2355 -9.1661 8.6772 0.4652 0.0009 0.2668 0.0010
2458550.576618 -0.8848 1.3658 -3.7954 9.2115 0.4648 0.0009 0.2675 0.0010
2458554.664806 -1.0631 2.8411 26.3565 16.8388 0.4660 0.0018 0.2629 0.0021
2458555.650955 -2.6379 1.6708 -3.0134 12.1884 0.4660 0.0010 0.2617 0.0012
2458562.535601 11.6500 1.7232 2.8796 8.4236 0.4655 0.0012 0.2603 0.0013
2458586.560780 -2.4692 1.5497 1.8631 10.8953 0.4670 0.0011 0.2604 0.0012
2458591.490221 2.5875 1.5793 -6.1143 8.8415 0.4663 0.0010 0.2578 0.0010
2458611.494962 0.6165 2.0178 -8.6563 11.9310 0.4648 0.0013 0.2675 0.0015
2458728.879893 0.9451 1.7133 -8.4924 10.5144 0.4646 0.0011 0.2620 0.0012
2458767.767044 10.1703 1.7910 -0.4932 11.3817 0.4690 0.0013 0.2663 0.0014

##  Appendix H Affiliations

1 Aix Marseille Univ, CNRS, CNES, LAM, Marseille, France.
2 Dipartimento di Fisica, Universita degli Studi di Torino, via Pietro Giuria
1, I-10125, Torino, Italy.
3 Centre for Exoplanets and Habitability, University of Warwick, Gibbet Hill
Road, Coventry, CV4 7AL, UK.
4 Department of Physics, University of Warwick, Gibbet Hill Road, Coventry CV4
7AL, UK.
5 Departamento de Física Teórica e Experimental, Universidade Federal do Rio
Grande do Norte, Campus Universitário, Natal, RN, 59072-970, Brazil.
6 Centro de Astrobiología (CAB, CSIC-INTA), Depto. de Astrofísica, ESAC campus
28692 Villanueva de la Cañada (Madrid).
7 Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP,
Rua das Estrelas, 4150-762 Porto, Portugal.
8 Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do
Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal.
9 Leiden Observatory, Leiden University, 2333CA Leiden, The Netherlands.
10 Department of Space, Earth and Environment, Chalmers University of
Technology, Onsala Space Observatory, 439 92 Onsala, Sweden.
11 Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA.
12 NASA Ames Research Center, Moffett Field, CA 94035, USA.
13 Instituto de Astrofísica de Canarias, 38205 La Laguna, Tenerife, Spain.
14 Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna,
Tenerife, Spain.
15 Sub-department of Astrophysics, Department of Physics, University of
Oxford, Oxford, OX1 3RH, UK.
16 George Mason University, 4400 University Drive, Fairfax, VA, 22030 USA.
17 International Center for Advanced Studies (ICAS) and ICIFI (CONICET), ECyT-
UNSAM, Campus Miguelete, 25 de Mayo y Francia, (1650) Buenos Aires, Argentina.
18 Thüringer Landessternwarte Tautenburg, Sternwarte 5, 07778 Tautenburg,
Germany.
19 NASA Exoplanet Science Institute, Caltech/IPAC, Mail Code 100-22, 1200 E.
California Blvd., Pasadena, CA 91125, USA.
20 Dept. of Physics & Astronomy, Swarthmore College, Swarthmore PA 19081, USA.
21 U.S. Naval Observatory, 3450 Massachusetts Avenue NW, Washington, D.C.
20392, USA.
22 Observatoire de l’Université de Genève, Chemin des Maillettes 51, 1290
Versoix, Switzerland.
23 University of Zürich, Institute for Computational Science,
Winterthurerstrasse 190, 8057 Zürich, Switzerland
24 European Southern Observatory, Alonso de Cordova 3107,Vitacura, Santiago,
Chile.
25 Department of Physics and Kavli Institute for Astrophysics and Space
Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
26Department of Earth, Atmospheric and Planetary Sciences, Massachusetts
Institute of Technology, Cambridge, MA 02139, USA
27Department of Aeronautics and Astronautics, MIT, 77 Massachusetts Avenue,
Cambridge, MA 02139, USA
28 Hazelwood Observatory, Australia.
29 Mullard Space Science Laboratory, University College London, Holmbury St.
Mary, Dorking, Surrey, RH5 6NT, UK.
30 Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane,
Princeton, NJ 08544, USA.
31 Univ. Grenoble Alpes, CNRS, IPAG, F-38000 Grenoble, France
32 Astrophysics Science Division, NASA Goddard Space Flight Center, Greenbelt,
MD 20771, USA
33 Deutsches Zentrum für Luft- und Raumfahrt, Institut für Planetenforschung,
12489 Berlin, Rutherfordstrasse 2., Germany.
34 Center for Planetary Systems Habitability and McDonald Observatory, The
University of Texas at Austin, Austin, TX 78730, USA.
35 Noqsi Aerospace Ltd., 15 Blanchard Avenue, Billerica, MA 01821, USA
36 Rheinisches Institut für Umweltforschung an der Universität zu Köln,
Aachener Strasse 209, 50931 Köln, Germany.
37 Astronomical Institute of the Czech Academy of Sciences, Fričova 298,
Ondřejov 25168, Czech Republic
38 Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus
University, Ny Munkegade 120,DK-8000 Aarhus C, Denmark
39 Department of Astronomy, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo
113-0033, Japan.
40 Mikulski Archive for Space Telescopes.
41 NCCR/PlanetS, Centre for Space & Habitability, University of Bern, Bern,
Switzerland.
42 Astronomy Department and Van Vleck Observatory, Wesleyan University,
Middletown, CT 06459, USA
43 SETI Institute, Mountain View, CA 94043, USA.
44 Department of Astronomy, Columbia University, 550 W 120th Street, New York
NY 10027, USA