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Issue
A&A
Volume 658, February 2022
Article Number A176
Number of page(s) 17
Section Planets and planetary systems
DOI https://doi.org/10.1051/0004-6361/202141429
Published online 18 February 2022

© N. Heidari et al. 2022

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1 Introduction

The brightness of more than 200 000 stars has been monitored by Transiting Exoplanet Survey Satellite (TESS) (Ricker et al. 2015)with two-minute cadence during its two-year primary mission. The observed stars are closer and brighter (typically 30–100 times brighter) than the stars Kepler surveyed. This offers us a unique opportunity for furthering our knowledge in planetary science with follow-up observations: those from ground-based high-precision spectrographs to confirm the planetary nature and mass measurement, which together with the radius allows us to determine the bulk composition of planets; and ground- andspace-based observations to provide atmospheric characterization, for instance, with the upcoming James Webb Space Telescope (Gardner et al. 2006).

The NASA Kepler mission (Borucki et al. 2010) has discovered a large number of planets of intermediate size, with radii between those of Earth and Neptune. They are also known as sub-Neptunes. Because the size of planets is directly dependent on the physicalmechanisms in their formation and evolution, the absence of sub-Neptunes in our Solar System and their abundance among the exoplanet population has raised numerous fundamental questions. Many theoretical and statistical studies have been made of such planets. Rogers (2015) showed that most planets with R > 1.6 RE have a low density and are inconsistent with a purely rocky composition. Fulton et al. (2017) demonstrated that the sub-Neptunes’ distribution of radii is bimodal, with two peaks centered at 1.2 RE and 2.4 RE. This reveals a gap in planet radii between 1.5–2.0 RE. While this bimodal distribution can be explained by photoevaporation (Owen & Wu 2013, 2017; Lopez & Fortney 2014) and core-powered mass loss (Ginzburg et al. 2016, 2018), the composition and origin of close-in sub-Neptunes are not yet clear. Additional detections and precise characterizations are the keys to progress in answering our questions about their nature. One of the primary goals of TESS is to measure the mass of at least 50 transiting planets with a radius smaller than 4 Earth radii (Ricker et al. 2015). As of 22 April 2021, TESS has found more than 750 candidates1 (so-called TESS objects of interest, or TOI) with radii smaller than 4 RE. To date, 122 of them have been confirmed and have a mass measurement (e.g., Dragomir et al. 2019; Günther et al. 2019; Nielsen et al. 2020).

Here, we announce the detection and characterization of a sub-Neptune orbiting a bright (V = 8.4) K0 star using TESS photometric data and SOPHIE, Automated Planet Finder (APF), and HIRES RVs. In Sect. 2 we describe the variety of observations that were used to characterize the HD 207897 (TOI-1611) system, including photometric, spectroscopic, and high-resolution imaging data. In Sect. 3 we analyze the data and present the characterization of the host star and planet, combining models on RVs and transit data. Finally, we present our discussion and conclude in Sect. 4.

2 Observations

In this section, we provide a summary of all observations of HD 207897 taken by TESS and ground-based facilities.

2.1 TESS photometry

TESS planned to observe 80% of the sky in 26 sectors for 2 yr. Each sector lasts for approximately 27 days, and the sectors partially overlap2. Because HD 207897 is located near the north ecliptic pole where sectors overlap, it appears in many sectors. As reported in the Web TESS Viewing Tool (WTV)3, HD 207897 observations were taken in five sectors divided into two continuous periods from sectors 18–20 and 25–26, with a total time span of 131 days. After observations of sector 18 were completed, the MIT Quick Look pipeline (QLP; Huang et al. 2020a,b) detected the signature of two transits of HD 207897 b at a period of 16.20 d, and an alert was issued on 19 December 2019 by the TESS Science Office. No transits occurred during sector 19 as the sole transit fell in the data gap between the two orbits. After observations of sector 20 were downlinked, the Science Processing Operations Center (SPOC; Jenkins et al. 2016) at NASA Ames Research Center conducted a transit search (Jenkins 2002; Jenkins et al. 2010) and detected two transits of HD 207897 b at a signal-to-noise ratio (S/N) of 23.3. A limb-darkened transit model was fitted to the transit signature (Li et al. 2019), which passed all the diagnostic tests presented inthe Data Validation report (Twicken et al. 2018), including the odd-even transit depth test, the ghost diagnostic test, and the difference-image centroiding test, which located the source of the transit signatures within 0.42 ± 2.5 arcsec of the targetstar HD 207897. Two additional transits were observed and detected in sector 25, and one more transit occurred in sector 26. A multisector search of sectors 18–26 by the SPOC detected 7 transit events of HD 207897 b in total at an S/N of 34.3 and an average depth of 913.7 ± 21.1 ppm. No additional transiting-planet signatures were detected in any of the SPOC or QLP runs.

We used the short-cadence (2 min) observations of TESS data from these five sectors in our photometric analysis, which we present in Sect 3.2. These data were reduced by the SPOC Pipeline and are publicly available on Mikulski Archive for Space Telescopes (MAST)4.

2.2 High-resolution spectroscopy

2.2.1 SOPHIE

Before TESS observations, HD 207897 had been monitored by the SOPHIE spectrograph (Perruchot et al. 2008; Bouchy et al. 2013) between 2012 and 2015. The star measurements were conducted as a part of the Recherche de Planètes Extrasolaires (RPE) subprogram dedicated to detecting Neptunes and Super-Earths orbiting nearby and bright solar-type stars (Bouchy et al. 2009; Courcol et al. 2015; Hara et al. 2020). The observations were performed using high-resolution mode (resolution power of λ∕Δλ ≈ 75 000) with a simultaneous thorium-argon (Th-Ar) calibration lamp, allowing us to monitor the instrumental drift. We collected 44 high-resolution spectra with an RV root mean square (RMS) of 6.9 m s−1 (see Sect. 3.3.1 for more details about the derivation of the RVs). A first analysis of the data in 2015 showed a periodicity close to 16.3 d. However, our preliminary analysis based on an erroneous estimate of the rotational period of the star caused us to attribute the 16.3 d signal to stellar spot modulation at Prot /2, and observations of the star were stopped. After the release of the TESS data, we resumed SOPHIE observations to gather more data to better separate the activity signal and planetary RV variation, and also to search for other possible planets. The star was observed again in 2020 with a simultaneous Fabry-Perot (FP) reference spectrum. Twenty-four additional high-resolution spectra with an RV RMS of 4.43 m s−1 were gathered.

Our final SOPHIE dataset includes 68 spectra. With an exposure time ranging from 1000 to 1500 s, we achieved a median S/N of 97.7 per pixel at 550 nm. The mean RV uncertainty, computed using the quadratic sum of photon noise and wavelength calibration error, is 1.7 m s−1. The RV data set are presented in Table A.1 after the corrections described in Sect. 3.3.1 were applied.

2.2.2 HIRES

From the summit of Maunakea, we first observed HD 207897 using the Keck I telescope and HIRES spectrometer (Vogt 1994) from 2003 July 7 as part of the California Planet Search, and additional RVs were collected for 11 months beginning on 2020 January 21. Thirty-seven RVs were collected using the B5 decker (0.87″ × 5.0″), resulting in a resolution of 50 000. The median exposure time was 231 s, the average S/N per pixel was 220, and the internal uncertainty was 1.04 m s−1. The Doppler pipeline and observing setup follows the California Planet Search procedure outlined in Howard et al. (2010). The RV data set are presented in Table A.2. We note that data before 2004 July 9 (three data points) used a different CCD detector. For the sake of simplicity, we only used them in our RV periodogram by applying an offset term (Fig. 1).

2.2.3 APF

From the summit of Mt. Hamilton at the Lick Observatory, we collected 23 RVs of HD 207897 using the Levy Spectrograph (Burt et al. 2014) on the APF from 2020 June 2 until 2021 February 28. Twenty-three RVs were collected. Their median exposure time was 1200s, the S/N per pixel was 86, and the internal uncertainty was 3.0 m s−1. With a resolution of 100 000, this slit-fed spectrograph uses the iodine-cell technique to calculate RVs according to Butler et al. (1996). For additional details on the instrumental setup and data reduction, see Fulton et al. (2015). The full list of corrected RVs can be found in Table A.3.

thumbnail Fig. 1

Normalized periodograms of RVs and activity indexes for HD 207897. From top to bottom: RVs, residual of RVs after a Keplerian fit on 16.20 d, residuals of the fit on the planet and stellar rotation signal, CRX, bisector, FWHM, and Hα index. Thevertical cyan line marks the position of the highest peak in the RV periodogram at 16.20 d and shows no corresponding peak in the stellar activity periodograms. Horizontal lines indicate the 0.1, 1, and 10% FAP level from top to bottom. The vertical gray strip highlights the position of the rotational stellar period as estimated in Sect. 3.3.2.

2.2.4 FIES

From the Roque de los Muchachos Observatory in La Palma, Spain, we observed with the FIbre-fed Échelle Spectrograph (FIES; Telting et al. 2014) at the 2.56 m Nordic Optical Telescope and obtained four spectrabetween 2019 December 27 and 2020 January 15. We used the high-resolution fibre (R ~67 000) and extracted the spectra following Buchhave et al. (2010). The S/N per resolution element at 550 nm ranges between 62 and 127. We used theFIES data for stellar classification (see Sect. 3.1) and refrained from including them in the RV analysis because all the observations were acquired near phases 0.25 and 0.75.

2.2.5 TRES

From the Fred Lawrence Whipple Observatory (FLWO) at the top of Mt. Hopkins, Arizona, USA, we observed with the 1.5 m Tillinghast Reflector Telescope using the Tillinghast Reflector Echelle Spectrograph (TRES; Fűrész 2008; Mink 2011) to obtain one spectrum (S∕N ~ 36) on UT 31 December 2019. TRES is a fiber-fed optical spectrograph with a resolving power of R ~ 44 000. The spectrum was extracted following the procedures outlined in Buchhave et al. (2010) and was used to derive stellar parameters as described in Sect. 3.1.

2.3 High spatial resolution imaging

We used theAstraLux high spatial resolution camera (Hormuth et al. 2008) at the 2.2 m telescope of the Calar Alto Observatory (CAHA, Almeria, Spain) to unveil possible close companions to HD 207897. This instrument applies the lucky-imaging technique to retrieve diffraction-limited images from point source objects by acquiring thousands of short-exposure frames that freeze atmospheric variations and thus produce diffraction-limited images. We observed this target on 2020 February 26 under good weather conditions and a mean seeing of 0.9 arcsec. The brightness of this target allowed us to obtain 11 000 frames with an individual exposure time of 10 milliseconds. We used the Sloan Digital Sky Survey z filter (SDSSz), which is best suited for obtaining the highest possible resolution with AstraLux. We also used a field of view windowed to 6 × 6 arcsec. All frames were reduced by the instrument pipeline (Hormuth et al. 2008), which performs the basic reduction (bias subtraction and flat field correction), aligns all frames, and measures the Strehl ratio (Strehl 1902) of the individual images. This metric was then used to select the best images to perform the final stacking. We used the best 10% of the frames to produce the final high-resolution image. The final image does not show signs of close companions. We performed a dedicated search by removing the instrumental point spread function scaled to the target peak flux. No additional sources were present in the image. We then followed the procedures described in Lillo-Box et al. (2012, 2014) by using our own developed astrasens package5 to obtain the sensitivity of our image by performing an injection or retrieval of artificial sources. The sensitivity curve is shown in Fig. 2.

By using this sensitivity curve, we additionally estimated the probability of an undetected blended source in our high-spatial resolution image (BSC, see the procedure described in Lillo-Box et al. 2014). We use a python implementation of this approach (bsc, by J. Lillo-Box), which uses the TRILEGAL6 galactic model (v1.6 Girardi et al. 2012) to retrieve a simulated source population of the region around the corresponding target7. This simulated population is used to compute the density of stars around the target position (radius r = 1°) and to derive the probability of chance alignment at a given contrast magnitude and separation. In this case, given the AstraLux high-resolution image, we obtained a probability of an undetected blended source of 0.041%. We consider this probability low and the odds that such an undetected source might be an appropriate binary capable of mimicking the transit signal to be negligible. In addition, by using tpfplotter code8 (Aller et al. 2020), we plotted the target pixel file from TESS for HD 207897 b (see Fig. 3). We searched for possible light contamination by considering the nearby stars TIC 264678535 (Tmag = 13.3), TIC 264678538 (Tmag = 15.69) and TIC 264678529 (Tmag = 14.39), which all lie inside the selected apertures analyzed by PDC-SAP. Because the Gaia G bandpass is quite similar to the TESS bandpass, we used the Gaia fluxes of these stars and estimated the level of contamination. The total flux due to nearby stars was only 0.8% of the HD 207897 flux, which is automatically corrected by SPOC. Because the probability of undetected blended sources from the AstraLux high-resolution image is low, the amount of light contamination due to nearby stars is negligible, and because similar Keplerian amplitudes were derived with different masks (see Sect. 3.3.1), we conclude that the transit and RV variations originate from the main target within the TESS TPF (HD 207897) and are of planetary origin.

thumbnail Fig. 2

Blended source confidence curve from the AstraLux SDSSz image (solid black line). The color in 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 the TRILEGAL model (see Sect. 2.3). 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 unexplored regime in the high-spatial resolution image. The BSC corresponds to the integration of Paligned over this shaded region.
thumbnail Fig. 3

Target pixel file of TESS for HD 207897 corresponding to sector 18, created with tpfplotter (Aller et al. 2020). The red square is related to the SPOC aperture mask, and red circles indicate the Gaia DR2 magnitude of nearby stars with the size depending on their brightness. HD 207897, number 1, has a Gaia(mag) = 8.1, while the nearest star, TIC 264678535, number 2, has a Gaia(mag) = 13.8.

3 Analysis and results

3.1 Stellar parameters

To obtain the stellar atmospheric parameters, we first summed the 66 spectra of SOPHIE after correcting for RV variations of the star, for barycentric Earth radial velocity, and correcting for the background of the calibration lamps (Hobson 2019). This resulted in a high S/N per pixel spectrum of 772 at 550 nm.

The Teff and [Fe/H] were calculated following the procedure described in Santos et al. (2013) and Sousa et al. (2018). The procedure is based on the equivalent width of the Fe I and Fe II lines and assumes a balance in excitation and ionization of iron lines in local thermal equilibrium. The abundances of Mg and Si were derived by closely following the curve-of-growth analysis methods described in our previous works (Adibekyan et al. 2012, 2015). The abundances of C and O are very difficult to determine for stars cooler than about 5200 K (Delgado Mena et al. 2010; Bertran de Lis et al. 2015). We estimated the abundances of these elements empirically by using a machine-learning algorithm (we used the estimator RandomForestRegressor) from the Python Scikit-learn package (Pedregosa et al. 2011). The estimation of C and O was based on the abundance of Mg and Fe (Delgado Mena et al. 2017). Our initial sample was based on the HARPS sample, for which abundances of Mg and Fe are available (Adibekyan et al. 2012). Then we derived the O abundance for 535 stars and the C abundance for 758 stars following the method described in our previous works (Delgado Mena et al. 2010; Bertran de Lis et al. 2015). These samples were used as training and test datasets. The resulting abundances and other stellar parameters of HD 207897 are presented in Table 1.

As an independent stellar classification analysis, we used the FIES and TRES data following (SPC; Buchhave et al. 2012, 2014). The FIES analysis uses five spectral orders spanning a wavelength range from 5065 to 5320 Å, and the TRES analysis uses three spectral orders spanning the range from 5060 to 5300 Å. The spectra were compared to a library of synthetic templates to measure the effective temperature Teff, surface gravity log g, projected rotational velocity vsini, and metallicity [m/H] (a solar mix of metals). We analyzed the spectra individually and calculated a weighted average of each parameter. The results were Teff = 5085 ± 50K, log g = 4.48 ± 0.10, v sin i < 2 km s−1, and [m/H] = −0.23 ± 0.08, which agrees with the results of the other methods.

We also performed an analysis of the broadband spectral energy distribution (SED) of the star together with the Gaia EDR3 parallax (with no systematic offset applied; see, e.g., Stassun & Torres 2021), in order to determine an empirical measurement of the stellar radius, following the procedures described in Stassun & Torres (2016); Stassun et al. (2017a,b). We pulled the BT VT magnitudes from Tycho-2, the JHKS magnitudes from 2MASS, the W1–W4 magnitudes from WISE, the GGBPGRP magnitudes from Gaia, and the NUV magnitude from GALEX. Together, the available photometry spans the full stellar SED over the wavelength range 0.2–22 μm (see Fig. 4).

We performed a fit using Kurucz stellar atmosphere models, with the effective temperature (Teff), metallicity ([Fe/H]), and surface gravity (logg) adopted from the spectroscopic analysis. We also fixed the extinction AV ≡ 0 based on the proximity of the stars (see Table 1). The resulting fit (Fig. 4) has a reduced χ2 of 1.1, excluding the GALEX NUV flux, which indicates a moderate level of activity. When the (unreddened) model SED is integrated, the bolometric flux at Earth is Fbol = 1.401 ± 0.016 × 10−8 erg s−1 cm−2. The Fbol and Teff together with the Gaia parallax results in the stellar radius, R⋆ = 0.785 ± 0.014 R⊙. In addition, we can estimate the stellar mass from the empirical relations of Torres et al. (2010), giving M⋆ = 0.84 ± 0.05 M⊙. Additionally, we cross-checked these values with a different method by EXOFASTv2 in Sect 3.4.

Table 1

Stellar properties of HD 207897.

thumbnail Fig. 4

Spectral energy distribution of HD 207897. Red symbols represent the observed photometric measurements, where the horizontal bars represent the effective width of the passband. Blue symbols are the model fluxes from the best-fit Kurucz atmosphere model (black).

3.2 Photometry data analysis

The photometry was extracted with the pre-search data-conditioned simple aperture photometry (PDC-SAP) pipeline (Stumpe et al. 2012; Stumpe et al. 2014; Smith et al. 2012) provided by the TESS team. We removed nans and flagged low-quality data and 5σ outliers. We then normalized and detrended the light curve with a spline-robust iterative sigma-clipping method (Schoenberg 1946) using the Wotan package (Hippke et al. 2019)9. This method detrends the light curve by fitting the spline through minimizing the sum of squared residuals along with iteratively sigma-clipping. This step is one of the most important steps in the photometric analysis as it reduces the number of false-positive signals by removing instrumental and stellar noise. On the other hand, these detrending algorithms always include the risk of changing the transit depth or even fully remove shallow transits. For this reason, we tested different values of knots and chose the value of 0.7, which was the highest value that appeared suitable for removing the light-curve variabilities. The resulting light curve is shown in Fig. 5, and the transit events are marked with red triangles.

To search for any periodic signals in the data, we used the transit least-squares (TLS) algorithm (Hippke & Heller 2019), a method for investigating planetary transits that takes the stellar limb-darkening (Mandel & Agol 2002) and the effects of planetary ingress and egress into account. This method is publicly available10 and has been optimized for the signal detection efficiency (SDE) of small planets. We searched for periodic signals in the range 0.6–122 d and sampled 28607 periods within this range. The result showed a prominent periodic signal that occurred every 16.20 d with an S/N of 43, an SDE of 76.2 and a false-alarm probability (FAP) lower than 0.01% (see Fig. B.1). After masking the signal at 16.20 d, we ran the TLS again and did not see any periodic signals. A search for a long period beyond 122 d did not show any significant signals either.

thumbnail Fig. 5

TESS light curves and EXOFASTv2 best-fit models for RVs and phometric data. Top panel: full PDC-SAP (two-minute) TESS light curve after detrending, taken from sectors 18, 19, 20, 25, and 26. The red triangles indicate the transit events, and the green vertical lines indicate the momentum dumps of the spacecraft, which occur every 2.5 days. None of the transit events occurred during momentum dumps. Bottom left: phase-folded SOPHIE, APF, and HIRES RVs of HD 207897 b at the period of 16.20 d. Bottom right: TESS phase-folded light curve.

3.3 Radial velocity data analysis

3.3.1 RVdata reduction on SOPHIE

The SOPHIE data were reduced with the SOPHIE data reduction pipeline (DRS, Bouchy et al. 2009), which extracts the RV by cross-correlating spectrum with a binary mask and then fits a Gaussian of the cross-correlation function (CCF) (Pepe et al. 2002). We tested different masks, including G2, K0, and K5. Because they showed similar Keplerian amplitude variations, it is unlikely that these variations are produced by blend scenarios composed of stars of different spectral types (Bouchy et al. 2008). We finally adopted the RV data derived with the K5 mask because it presented a smaller RV dispersion.

We subsequently excluded six RV points that did not reach the required quality: three points with a lower S/N than required S∕N550 > 50, two points with moonlight pollution, and one point that was an outlier and resulted from an observation performed without simultaneous calibration. We corrected the remaining points for the charge transfer inefficiency (CTI) effect (Santerne et al. 2012). This correction ranged from 1.4 to 6 m s−1 with a mean RV correction of2.1 m s−1. We then removed the nightly drift of the telescope measured from the simultaneous Th-Ar or FP reference spectra. This correction also falls within the 0.1 to 9 m s−1 range, with a mean RV of 2.1 m s−1.

The next step was to remove a long-term drift of the zeropoint due to the instrumental effect identified in SOPHIE RV data (Courcol et al. 2015; Hobson et al. 2018). To track this offset, so-called ’constant’ stars were monitored each night. We combined these observations to build a time series of the RV master constant (see Courcol et al. 2015 for more details of the method). We then estimated the long-term zeropoint drift as a function of time for each observation night and subtracted it from the HD 207897 RV data. This correction is in the 0.2–6 m s−1 range with a mean value of 3.3 m s−1. Because we saw the effects of the long-term drift of the zeropoints on the bisector span of constant stars, we applied the same processes to the bisector of HD 207897 as well. The correction for bisector was between 4 and 11 m s−1 with a mean value of 2 m s−1. After these corrections were applied, the HD 207897 RVs were reduced from an original RMS of 6.2 m s−1 to a final RMS of 4.9 m s−1.

3.3.2 Stellar rotation and activity

To investigate the activity of the star, we used several indicators such as bisector span, CCF FWHM, chromatic RV index (CRX), Hα, and from SOPHIE spectra. We also used the S-index from the HIRES spectra.

We obtained the bisector span and CCF FWHM from the SOPHIE data reduction system. The CRX was extracted using the SERVAL (Zechmeister et al. 2018) code. To compute the Hα index, which measures the flux in the Hα line, we followed the definitions of Boisse et al. (2011). To do this, we also applied background correction to the data as appropriate for the two different calibration lamps (for further details, see Hobson 2019).

We derived the S-index from HIRES spectra following Baliunas et al. (1995) and Paulson et al. (2002). We also computed the index on SOPHIE spectra following the method of Noyes et al. (1984), but the S/N is low in all first (bluest) orders, where Ca H&K lines are located, with one exception in 2020 (S∕N = 33). We decided to sum the bluest order of spectra with S/N > 20 to reach better S/Ns and then calculated . We first did this for the 2012–2015 spectra, of which 22 had an S∕N > 20, giving a value of . Only one 2020 spectrum presents an S∕N > 20, so that no summation was possible. This spectrum yields a value of , indicating that the star may have a similar level of activity as during the 2012–2015 period. Our value of for 2012-2015 is consistent with reported by Brewer et al. (2016). This value indicates a modest activity level of HD 207897.

To confirm our value, we used the GALEX near-ultraviolet (NUV) flux excess of the star (Fig. 4). The observed NUV excess implies a chromospheric activity of through the empirical relations of Findeisen et al. (2011), consistent with the value obtained spectroscopically. Moreover, the NUV-estimated activity implies an age of τ⋆ = 4.4 ± 0.9 Gyr according to the empirical relations of Mamajek & Hillenbrand (2008).

We estimated a stellar rotation period of 37 ± 7 d with the method proposed in Noyes et al. (1984), which agrees well with an estimated period of d following Mamajek & Hillenbrand (2008). These estimates are consistent with the value of 38 days from Isaacson & Fischer (2010).

We sought to constrain the Prot of the star with RVs and activity indicators. We subtracted a linear drift in the CCF FWHM, CRX, and RVs time series, and a cubic drift in the S-index. Moreover, an offset term was fit on Hα data between the two different calibration lamp background corrections (before and after BJD = 57284.4185). Then, we computed the periodogram of RVs, the RV-residuals of Keplerian models, and the activity indicators (Fig. 1). The RV residuals of planet b show two peaks at 35.9 and 37.6 days near the 10% FAP.

We ran an ℓ1 periodogram on the RVs (see Fig. 6) for comparison. This was obtained with the same procedure as in Hara et al. (2020): we considered alternative noise models characterized by an autocovariance function that is a sum of white, correlated, and quasi-periodic components with different amplitudes and timescales and ranked them with cross-validation. The correlated component is a Gaussian kernel characterized by its timescale and amplitude, and the quasi-periodic component is a Gaussian kernel as in Haywood et al. (2014), characterized by its decay timescale, period, and amplitude. The amplitudes of the white, correlated, and quasi-periodic terms were taken on a grid (0 to 3 m s−1 with a 0.5 m s−1 step), the timescales 0, 3, and 6 days for the correlated term, 30, 60, and 90 days for the quasi-periodic term, and 37.6 days for the period of the quasi-periodic component. We also included one offset per instrument in the base model. Figure 6 corresponds to the highest-ranked noise model. We found a significant signal at the planet period (FAP of 2 × 10−9) and found a signal at 37.6 d with an FAP of 0.5. The signal at 37.6 d very likely corresponds to a stellar signal.

While the periodogram of the CCF FWHM and Hα activity indicators does not exhibit any significant signals, CRX shows a peak near to 10% FAP at 36.5. The S-index periodogram shows several peaks at thelong periods, but no correlation (R = 0.16) is found between the S-index and HIRES RVs. We note that given the relatively low value of vsini (2 ± 1 km s−1), we did not detect any correlations between the RVs and its residuals and bisector.

We searched the SAP and PDC-SAP light curves for a signal of the rational period of the star in the photometry. For this, we applied the systematics-insensitive periodogram (SIP) method11 (Angus et al. 2016; Hedges et al. 2020) for SAP and the Gaussian process (GP) model on PDC-SAP light curves. The SIP method detrends the SAP light curve (see Fig. B.2 bottom) from TESS instrument systematics and also calculates the Lomb-Scargle periodogram and without requiring a predetrending of the light curves as other methods (e.g., the autocorrelation function, ACF, by McQuillan et al. 2013). This method was initially used for the Kepler mission and has recently been successfully applied for TESS data such as TOI-1259A (Martin et al. 2021) and TOI-700 (Hedges et al. 2020). The SIP periodogram (see Fig. B.2 top) does not exhibit any significant signal for HD 207897 b. We also applied a GP model on PDC-SAP light curves, but it did not display any convincing signal either.

To examine the origin of the 37.6 d signal further, following Hara et al. (2022), we investigated the phase and amplitude consistency of the 37.6-day signal in the SOPHIE RVs. We used the statistic defined in Eq. (14) of Hara et al. (2022). We fit an offset and a linear trend as well as a sinusoidal model for the 16.2-day planet. Adopting a value of the RV jitter of 3.16 m s−1, we find that the hypothesis that the phase and amplitude of the 37.6-day signal is constant is rejected at 2σ. This further supports the hypothesis that this signal is due to activity.

Based on the estimated stellar rotational period value and the signal at the CRX activity indicator, it is likely that the signals at 35.9 and 37.6 days are due to the stellar rotation period. We take these peaks in our joint model analysis with EXOFASTv2 in Sect. 3.4 into account.

thumbnail Fig. 6

ℓ1 periodogram of SOPHIE RVs for HD 207897 b following Hara et al. (2017). The main peaks of the periodogram are indicated with orange circles.

3.3.3 Radial velocity results

The combined RV data of HD 207897 are plotted in Fig. 7 after fitting a zeropoint offset for each RV dataset (see Table 2). We removed a linear trend of − 0.28 ± 0.11 m s−1 yr−1 from RVs. We note that no notable differences were found in our results when this linear drift was included or excluded. However, because we saw a clear linear drift in the activity indicators such as the CCF FWHM and CRX, we decided to keep the drift.

We investigated the footprints of the planet in RVs by searching for periodic signals. To do this, we used the website of the Data and Analysis Center for Exoplanets (DACE, Delisle et al. 2016)12 and computed periodograms for the RVs (Fig. 1).

The RV periodogram displays a clear peak at 16.20 d with a value lower than the 0.1% FAP (Baluev 2008). Moreover, the periodogram of activity indicators shows no corresponding peak. This shows that this periodic signal is likely due to a planet and not to stellar activity. See Fig. 1.

Figure 6 shows that the ℓ1 periodogram confirms that the most prominent signal appears at 16.20 days with an FAP of 2 × 10−9. The value of the second-highest peak at 37.7 days agrees with the estimated rotational period of the star (see Sect. 3.3.2).

thumbnail Fig. 7

Radial velocities of HD 207897 from SOPHIE, APF, and HIRES before correction for the linear trend.

3.4 Joint modeling of RV and photometry

To explore all the parameters of the system, including the host star and the planet, we simultaneously and self-consistently modeled the photometric observations of the star from five sectors of TESS and the RV observations from SOPHIE, HIRES, and APF using the fast exoplanetary fitting package (EXOFASTv213, Eastman et al. 2013, 2019; Eastman 2017). This global modeling software uses a differential evolution Markov chain coupled with a Metropolis-Hastings Monte Carlo sampler that uses error scaling to explore the system parameters.

EXOFASTv2 fits a total of 33 free parameters for the HD 207897 system, which can be divided into the following categories:

  • Twelve parameters related to the planet and activity period: the mid-transit time TC, planet orbital period P, the ratio of the planet to star radius Rp ∕Rstar (only for the planet), the orbital inclination i (only for the planet), the RV semi-amplitude K, and two more free parameters related to the eccentricity e.

  • Two parameters for each RV instrument: instrumental offset and jitters. One free parameter is also fit for drift on RVs.

  • Two limb-darkening coefficients for TESS photometric bandpasses, along with baseline flux and variance are fit for the transit light curve.

  • Elevenstellar parameters: Stellar mass M*, stellar radius R*, and effective temperature Teff by the MIST model, stellar radius R*,SED and effective temperature Teff, SED by the SED model, observed metallicity [Fe∕H], theoretical metallicity at the star’s birth by the MIST model, age, equivalent evolutionary point EPP, V-band extinction Av, and distance d.

Before running EXOFASTv2, we set a Gaussian prior on Teff and [Fe/H] from our spectral analysis results, presented in Sect. 3.1. We also imposed a prior on the Gaia DR2 parallax after applying the offset correction as described in Lindegren et al. (2018). The broadband photometry presented inTable 1 is also included. We enforced the upper limit for the V-band extinction (Av) from Schlegel et al. (1998) and Schlafly & Finkbeiner (2011). The broadband photometry, the Gaia parallax, and Av allowed us to model the stellar spectral energy distribution, which is key to constraining the stellar radius. EXOFASTv2 interpolates a precompiled 4D grid of bolometric corrections (log g, Teff, [Fe/H], and reddening) to directly compute the broadband photometry flux. We did not set the limb darkening to let EXOFASTv2 constrain the best parameters of a quadratic limb darkening through the Claret (2017) tables for the TESS bands and the stellar atmosphere parameters (Teff, [Fe/H] index, and log g*). We used the Mesa isochrones and stellar tracks evolutionary model (MIST, Dotter 2016; Choi et al. 2016) to derive the full stellar parameters by combining our data. We also allowed the fitting of a linear slope on the original RVs as part of our joint analysis.

EXOFASTv2 considers the chains to be well mixed when the Gelman-Rubin statistic (Gelman et al. 2004, 1992; Ford 2006) decreases below 1.01. The Gelman-Rubin statistic describes how similar the chains are; a value under 1.01 shows that the chains are well mixed. The list of our priors and final median values of the posterior distributions together with their 1σ confidence intervals of the full system parameters are reported in Table 2.

As we showed in Sect. 3.3.2, HD 207897 has a moderate stellar activity and the signals at 35.9 and 37.6 d are likely to be due to the stellar rotation periods. Because these signals affect the mass estimate of the planet slightly, we considered them as an additional Keplerian fit in our global analysis. A more ideal solution to take activity into account is detrending the RVs using activity indicators (e.g., the S-index or the FWHM), but this is currently not possible with EXOFASTv2. Furthermore, we did not have the same activity indicators for all RVs for a detrending. As an independent analysis, we used only SOPHIE data and trained GP against CRX. The results agreed completely with the EXOFASTv2 global modeling. When we used two Keplerian models in EXOFASTv2, we did not fix the period and let EXOFASTv2 find the best activity period between the 35.9 and 37.6 d signals. After EXOFASTv2 converged, we saw a bimodality in the posterior distribution for the stellar activity periods (see Fig. 8, top). We therefore present the final median posterior distribution values of the two most probable solutions in Table 2. We also report their calculated probabilities based on the area of the posterior distributions. The probability of the most likely values is 54%, and that of the less likely values is 46%.

HD 207897 is a main-sequence K0 dwarf star. We found that its most likely values for mass is , for the radius, this value is , and for Teff it is K. These values agree well with the result of our stellar analysis in Sect. 3.1 and also with the stellar parameters from Gaia Data Release 2, such as Teff= K and a radius of (Brown et al. 2018).

We also show that the planet has a period of 16.20 d, a radius of 2.5 ± 0.08 RE and a mass of either 14.4 ± 1.6 ME or 15.9 ± 1.6 ME with nearly equal probability. These two solutions correspond to two possibilities for the stellar activity period. Hence, the density is either 5.1 ± 0.7 g cm−3 or g cm−3. The two values agree with each other inside their error bars.

The Keplerian solution and transit model for HD 207897 b based on the most likely values are shown in Fig. 5 (bottom). The Keplerian model based on the most likely activity period of 37.6 d is illustrated in Fig. 8.

Table 2

Median values and 68% confidence interval for HD 207897 b and its host star.

4 Internal structure

In order to characterize the internal structure of HD 207897 b, we performed a Markov chain Monte Carlo (MCMC) Bayesian analysis (Dorn et al. 2015) using the interior composition model introduced in Brugger et al. (2017), Mousis et al. (2020), and Acuña et al. (2021), which comprises three layers: a Fe-rich core, a silicate-rich mantle, and a water layer. With an input equilibrium temperature of 637 K, assuming an albedo of zero, the irradiance that HD 207897 b received is enough to present vapor and supercritical phases if water is found on its surface. Therefore we coupled an atmosphere-interior model that calculates the surface conditions and the contribution of the atmosphere to the total radius.

We considered two scenarios to obtain the interior structure of HD 207897 b: scenario 1, in which only the mass and radius of the planet are considered as inputs to the MCMC analysis (shown in Table 2), and scenario 2, in which the planetary mass and radius and the stellar Fe/Si and Mg/Si mole ratios (see Table 1) are the input data. To compute the Fe/Si and Mg/Si mole ratios with the stellar abundances, we followed the approach depicted in Brugger et al. (2017) and Sotin et al. (2007). We obtained Fe/Si = 0.74 ± 0.09 and Mg/Si = 1.11 ± 0.20. The outputs of the MCMC analysis are the posterior distributions functions (PDF) of the core mass fraction (CMF), the water mass fraction (WMF), and the atmospheric parameters, which are the temperature at 300 bar, the planetary albedo, and the atmospheric thickness from transit pressure to 300 bar. We assume a water-rich atmosphere. Table 3 shows the 1D, 1σ confidence intervals of the MCMC output parameters.

In the most general case (scenario 1), up to 31% of the mass of HD 207897 b can be in the form of a hydrosphere. It reaches supercriticalor superionic phases at its base (Mazevet et al. 2019) with the most likely value of the mass. This value increases slightly with the less likely value, although both cases are consistent with a water-rich planet with a water mass fraction of 20–30%. The 1σ confidence interval limits the maximum CMF to 0.50 (see Fig. 9). In addition, a Fe-depleted planet (CMF = 0) is possible but unlikely. Assuming a pure silicate interior, the WMF is found to be 2.2 × 10−5 in HD 207897 b, which corresponds to a pressure at the base of the hydrosphere of approximately 300 bar.

When we take the stellar abundances into account to constrain the planetary Fe/Si and Mg/Si mole ratios, the CMF is calculated to be 0.21, which is lower than the Earth’s CMF (0.32). In this scenario, the WMF would be below 0.16, implying that HD 207897 b can be considered a water-rich planet. If the temperature and pressure of the hydrosphere are high enough to sustain a supercritical regime, then the atmosphere is extended and constitutes approximately 20% of the total planetary radius.

5 Discussion and summary

We detected and characterized a sub-Neptune orbiting HD 207897 with a period of 16.202161 ± 0.000083 d. We used TESS photometry data along with SOPHIE, HIRES, and APF RVs observations. We found that the planet has a radius of 2.5 ± 0.08 RE and a mass of either 14.4 ± 1.6 ME with a probability of 56% or 15.9 ± 1.6 ME with a probability of 46% based on bimodal results of the stellar activity period. The density accordingly translates into a high density of either 5.1 ± 0.7 g cm−3 or g cm−3. We used the same mass and radii bounds as Otegi et al. (2020) from the NASA Exoplanet Data Archive14 (December 5, 2020) and plot all the sub-Neptune-sized planets (2 < R/RE < 4) with a determined semimajor axis and luminosity in Fig. 10. This plot shows that HD 207897 b joins the group of dense sub-Neptunes such as HD 119130 b ( g cm−3; Luque et al. 2019), GJ143 b ( g cm−3; Dragomir et al. 2019), Kepler-10 c (ρP = 7.1 ± 1 g cm−3; Dumusque et al. 2014), TOI-849 b ( g cm−3; Armstrong et al. 2020), Kepler-538 b (ρP = 5.4 ± 1.3 g cm−3; Mayo et al. 2019), Kepler-411 b (ρP = 9.9 ± 1.3 g cm−3; Sun et al. 2019), K2-110 b (ρP = 5.2 ± 1.2 g cm−3; Osborn et al. 2017), and K2-263 b ( g cm−3; Mortier et al. 2018). These planets are relatively close to their host stars and may have a similar formation history.

The question now is how HD 207897 b and other similar planets with such a high density can exist at a close distance to their host star. One possibility is that the planet has lost most of its volatile elements by evaporation, but for the case of HD 207897 b with an orbital period of 16.20 d and receiving an incident flux of F = 26.3 FE, this is not a satisfactory answer. Even when we consider an extreme evaporation process (Lecavelier Des Étangs 2007), the mass loss of the planet would be just 0.1 ME during the entire lifetime of the star, which cannot account for its high density. HD 207897 b is unlikely to have formed in situ. According to Schlichting (2014), the maximum isolation mass that can form at a distance of a = 0.12 AU is only ~0.06 ME assuming a minimum mass solar nebula (MMSN). A disk surface density ~41 times higher than that of the solar nebula would be required to form a planet as massive as HD 207897 b at this distance. Two possible scenarios can be considered that are both consistent with the MMSN, however: Either the material from the outer region migrated and formed the planet HD 207897 b (e.g., Chatterjee & Tan 2013), or the formation of HD 207897 b occurred far away from the disk and the planet subsequently migrated to its current location (e.g., McNeil & Nelson 2010; Kley & Nelson 2012). The second scenario could have been triggered by another planet in this system. The hint of a long-term trend on RVs allows for the presence of another planet. The high occurrence rate of long-period giant planets (mass >0.3 MJ) in systems harboring small planets (planets with masses or radii between those of Earth and Neptune) (Zhu & Wu 2018; Schlecker et al. 2021) can also support this scenario. In the case of HD 119130 b, Luque et al. (2019) suggested a migration scenario triggered by other planets to explain the linear drift in their RV data. However, more photometry and radial velocity observations are still needed to understand the planetary system HD 207897.

Furthermore, the brightness (K = 6.3 mag) of HD 207897, its relatively small stellar radius, and its quite nearby distance (28 pc) would make HD 207897 b a good target for atmospheric characterization. Similarly, the close distance and high brightness for a transiting planet host,make HD 207897 b an excellent target for studying the architecture of the system through ground-based observations. For example, measuring the host star spin-orbit alignment (obliquity) using the Rossiter-McLaughlin (RM, Rossiter 1924; McLaughlin 1924) anomaly can provide us with important information about planetary migration and evolution.

Table 3

1σ confidence intervals of the interior and atmosphere MCMC output parameters in the two different compositional scenarios (see text).

thumbnail Fig. 8

Bimodality in the posterior distribution for the stellar activity periods (top) and two-Keplerian model solution on the activity signal at 37.6 d with the initial period at 16.2 d (bottom).
thumbnail Fig. 9

2D 1σ confidence regions of HD 207897 b for the mass estimation with activity period on 37.6 d (blue) and with activity period on 35.9 d (red). Solid lines indicate the confidence intervals of scenario 1, and dashed lines correspond to scenario 2, in which the stellar abundances are also included as input data in the MCMC interior structure analysis. The MMF is defined as MMF = 1 - CMF - WMF. The green dot and brown square indicate the position of Earth and Mercury in the ternary diagram, respectively.
thumbnail Fig. 10

Density semimajor-axis diagram for HD 207897 b and other sub-Neptune-sized planets (2 < RE < 4) with known semimajor axes, luminosity, and accurate mass and radius (Otegi et al. 2020). Dots are colored with planet insolation in Earth units . The mentioned planets have a density higher than 5 g cm−3.

Acknowledgements

We warmly thank the OHP staff for their support on the observations. X.B., I.B. and T.F. received funding from the French Programme National de Physique Stellaire (PNPS) and the Programme National de Planétologie (PNP) of CNRS (INSU). We also acknowledge the financial support of French embassy in Tehran. N.H. acknowledges F. Vakili for his constant academic and administrative support. N.H. warmly thanks Ph. Stee, J. L. Beuzit, E. T. Givenchy for all their help. N.H also thanks Jason D. Eastman and Michael Hippke who have written EXOFASTv2 and TLS package, respectively, for their guides. This publication makes use of 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. The DACE platform is available at https://dace.unige.ch. J.L-B. acknowledges financial support received from “la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648, with fellowship code LCF/BQ/PI20/11760023. This work has been carried out in the frame of the National Centre for Competence in Research “Planets” supported by the Swiss National Science Foundation (SNSF). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project SPICE DUNE, grant agreement No 947634). This work was supported by FCT – Fundação para a Ciência e Tecnologia (FCT) through national funds and by FEDER through COMPETE2020 – Programa OperacionalCompetitividade e Internacionalização by these grants: UID/FIS/04434/2019; UIDB/04434/2020; UIDP/04434/2020; PTDC/FIS-AST/32113/2017 and POCI-01-0145-FEDER-032113; PTDC/FIS-AST/28953/2017 and POCI-01-0145-FEDER-028953. V.A., E.D.M, N.C.S., and S.G.S. also acknowledge the support from FCT through Investigador FCT contracts nr. IF/00650/2015/CP1273/CT0001, IF/00849/2015/CP1273/CT0003, IF/00169/2012/CP0150/CT0002, and IF/00028/2014/CP1215/CT0002, respectively, and POPH/FSE (EC) by FEDER funding through the program “Programa Operacional de Factores de Competitividade – COMPETE”. O.D.S.D. is supported in the form of work contract (DL 57/2016/CP1364/CT0004) funded by FCT. A.C. et P.C. acknowledge funding from the French National Research Agency (ANR) under contract number ANR-18-CE31-0019 (SPlaSH). N.A.D. acknowledges the support of FONDECYT project 3180063. S.H. acknowledges CNES funding through the grant 837319. X.D. and G.G. acknowledge funding in the framework of the Investissements d’Avenir program (ANR-15-IDEX-02), through the funding of the ”Origin of Life” project of the Univ. Grenoble-Alpes. This work was supported by Fundação para a Ciência e a Tecnologia (FCT) and Fundo Europeu de Desenvolvimento Regional (FEDER) via COMPETE2020 through the research grants UIDB/04434/2020, UIDP/04434/2020, PTDC/FIS-AST/32113/2017 and POCI-01-0145-FEDER-032113, PTDC/FIS-AST/28953/2017 and POCI-01-0145-FEDER-028953. O.D.S.D. is supported in the form of work contract (DL 57/2016/CP1364/CT0004) funded by FCT. 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. 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. This paper includes data collected by the TESS mission that are publicly available from the Mikulski Archive for Space Telescopes (MAST). D.D acknowledges support from the TESS Guest Investigator Program grant 80NSSC19K1727 and NASA Exoplanet Research Program grant 18 − 2XRP182 − 0136. T.D acknowledges support from MIT’s Kavli Institute as a Kavli postdoctoral fellow. E.A.P. acknowledges the support of the Alfred P. Sloan Foundation. L.M.W. is supported by the Beatrice Watson Parrent Fellowship and NASA ADAP Grant 80NSSC19K0597. A.C. is supported by the NSF Graduate Research Fellowship, grant No. DGE 1842402. D.H. acknowledges support from the Alfred P. Sloan Foundation, the National Aeronautics and Space Administration (80NSSC19K0379), and the National Science Foundation (AST-1717000). I.J.M.C. acknowledges support from the NSF through grant AST-1824644. P.D. acknowledges support from a National Science Foundation Astronomy and Astrophysics Postdoctoral Fellowship under award AST-1903811. A.B. is supported by the NSF Graduate Research Fellowship, grant No. DGE 1745301. R.A.R. is supported by the NSF Graduate Research Fellowship, grant No. DGE 1745301. C.D.D. acknowledges the support of the Hellman Family Faculty Fund, the Alfred P. Sloan Foundation, the David and Lucile Packard Foundation, and the National Aeronautics and Space Administration via the TESS Guest Investigator Program (80NSSC18K1583). J.M.A.M. is supported by the NSF Graduate Research Fellowship, grant No. DGE-1842400. J.M.A.M. and P.C. acknowledge the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining Grant No. 1829740, the Brinson Foundation, and the Moore Foundation; their participation in the program has benefited this work. This paper is partially based on observations made with the Nordic Optical Telescope, operated by the Nordic Optical Telescope Scientific Association at the Observatorio del Roque de los Muchachos, La Palma, Spain, of the Instituto de Astrofisica de Canarias.

Appendix A RV time series

Table A.1

SOPHIE RVs for HD207897 b

Table A.2

HIRES RVs for HD207897 b

Table A.3

APF RVs for HD207897 b

Appendix B Figures

thumbnail Fig. B.1

TLS periodogram for the TESS light curve of HD207897 b. The blue line shows the highest peak at 16.20 d with SDE=76.2. The dashed blue lines indicate the aliases of this period.
thumbnail Fig. B.2

Systematics-insensitive periodogram and SAP TESS data for HD207897. Top: The SIP periodogram is generated for HD207897. Bottom: Raw SAP TESS light curves in red and detrended data against instrument systematics by SIP in black. The SIP periodogram does not exhibit any significant signal for HD207897 b because the highest peak in this periodogram has a power of only 0.0006 at 66.6 d.

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7

This is done in python by using the Bhatti et al. (2020) implementation by Bhatti et al. (2020).

12

Available at https://dace.unige.ch

13

EXOFASTv2 is available at https://github.com/jdeast/EXOFASTv2

All Tables

Table 1

Stellar properties of HD 207897.

In the text
Table 2

Median values and 68% confidence interval for HD 207897 b and its host star.

In the text
Table 3

1σ confidence intervals of the interior and atmosphere MCMC output parameters in the two different compositional scenarios (see text).

In the text
Table A.1

SOPHIE RVs for HD207897 b

In the text
Table A.2

HIRES RVs for HD207897 b

In the text
Table A.3

APF RVs for HD207897 b

In the text

All Figures

thumbnail Fig. 1

Normalized periodograms of RVs and activity indexes for HD 207897. From top to bottom: RVs, residual of RVs after a Keplerian fit on 16.20 d, residuals of the fit on the planet and stellar rotation signal, CRX, bisector, FWHM, and Hα index. Thevertical cyan line marks the position of the highest peak in the RV periodogram at 16.20 d and shows no corresponding peak in the stellar activity periodograms. Horizontal lines indicate the 0.1, 1, and 10% FAP level from top to bottom. The vertical gray strip highlights the position of the rotational stellar period as estimated in Sect. 3.3.2.
In the text
thumbnail Fig. 2

Blended source confidence curve from the AstraLux SDSSz image (solid black line). The color in 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 the TRILEGAL model (see Sect. 2.3). 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 unexplored regime in the high-spatial resolution image. The BSC corresponds to the integration of Paligned over this shaded region.
In the text
thumbnail Fig. 3

Target pixel file of TESS for HD 207897 corresponding to sector 18, created with tpfplotter (Aller et al. 2020). The red square is related to the SPOC aperture mask, and red circles indicate the Gaia DR2 magnitude of nearby stars with the size depending on their brightness. HD 207897, number 1, has a Gaia(mag) = 8.1, while the nearest star, TIC 264678535, number 2, has a Gaia(mag) = 13.8.
In the text
thumbnail Fig. 4

Spectral energy distribution of HD 207897. Red symbols represent the observed photometric measurements, where the horizontal bars represent the effective width of the passband. Blue symbols are the model fluxes from the best-fit Kurucz atmosphere model (black).
In the text
thumbnail Fig. 5

TESS light curves and EXOFASTv2 best-fit models for RVs and phometric data. Top panel: full PDC-SAP (two-minute) TESS light curve after detrending, taken from sectors 18, 19, 20, 25, and 26. The red triangles indicate the transit events, and the green vertical lines indicate the momentum dumps of the spacecraft, which occur every 2.5 days. None of the transit events occurred during momentum dumps. Bottom left: phase-folded SOPHIE, APF, and HIRES RVs of HD 207897 b at the period of 16.20 d. Bottom right: TESS phase-folded light curve.
In the text
thumbnail Fig. 6

ℓ1 periodogram of SOPHIE RVs for HD 207897 b following Hara et al. (2017). The main peaks of the periodogram are indicated with orange circles.
In the text
thumbnail Fig. 7

Radial velocities of HD 207897 from SOPHIE, APF, and HIRES before correction for the linear trend.
In the text
thumbnail Fig. 8

Bimodality in the posterior distribution for the stellar activity periods (top) and two-Keplerian model solution on the activity signal at 37.6 d with the initial period at 16.2 d (bottom).
In the text
thumbnail Fig. 9

2D 1σ confidence regions of HD 207897 b for the mass estimation with activity period on 37.6 d (blue) and with activity period on 35.9 d (red). Solid lines indicate the confidence intervals of scenario 1, and dashed lines correspond to scenario 2, in which the stellar abundances are also included as input data in the MCMC interior structure analysis. The MMF is defined as MMF = 1 - CMF - WMF. The green dot and brown square indicate the position of Earth and Mercury in the ternary diagram, respectively.
In the text
thumbnail Fig. 10

Density semimajor-axis diagram for HD 207897 b and other sub-Neptune-sized planets (2 < RE < 4) with known semimajor axes, luminosity, and accurate mass and radius (Otegi et al. 2020). Dots are colored with planet insolation in Earth units . The mentioned planets have a density higher than 5 g cm−3.
In the text
thumbnail Fig. B.1

TLS periodogram for the TESS light curve of HD207897 b. The blue line shows the highest peak at 16.20 d with SDE=76.2. The dashed blue lines indicate the aliases of this period.
In the text
thumbnail Fig. B.2

Systematics-insensitive periodogram and SAP TESS data for HD207897. Top: The SIP periodogram is generated for HD207897. Bottom: Raw SAP TESS light curves in red and detrended data against instrument systematics by SIP in black. The SIP periodogram does not exhibit any significant signal for HD207897 b because the highest peak in this periodogram has a power of only 0.0006 at 66.6 d.
In the text

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