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A&A
Volume 671, March 2023
Article Number A10
Number of page(s) 28
Section Planets and planetary systems
DOI https://doi.org/10.1051/0004-6361/202244238
Published online 28 February 2023

© The Authors 2023

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.

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1 Introduction

Thousands of brown dwarfs (BDs) have been discovered so far, many from all-sky infrared surveys (e.g. Martín et al. 1999; Tsvetanov et al. 2000; Cruz et al. 2007; Lodieu et al. 2007, 2012; Kirkpatrick et al. 2011; Deacon et al. 2014; Carnero Rosell et al. 2019), such as the Two-Micron All-Sky Survey (2MASS; Skrutskie et al. 2006), the Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010), the Deep Near-Infrared Survey of the Southern Sky (DENIS; Epchtein et al. 1997), the UKIRT Infrared Deep Sky Survey (UKIDSS; Lawrence et al. 2007), and the VISTA Hemisphere Survey (VHS; McMahon et al. 2013). Additional discoveries have come from large-scale optical surveys, such as the Dark Energy Survey (DES; Abbott et al. 2018), the Sloan Digital Sky Survey (SDSS; York et al. 2000), and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS; Chambers et al. 2016).

Most of the discovered BDs are free-floating. Only a small fraction of them are confirmed as wide co-moving companions to stars (Deacon et al. 2014). However, the recent study by Dal Ponte et al. (2020) provides almost 300 new candidate co-moving BDs using data from DES data release (DR) 1 and Gaia DR2 (Gaia Collaboration 2018b). Dal Ponte et al. (2020) observed a wide binary fraction of BDs, about 2–4%, over most of the spectral types (L0–T8.5); particularly for L dwarf companions that had better statistics. We should also mention the rising number of transiting BDs (e.g. Persson et al. 2019; Šubjak et al. 2020; Carmichael et al. 2020, 2021; Palle et al. 2021) discovered lately mainly thanks to space missions, such as the Convection, Rotation and planetary Transits (CoRoT) mission (Auvergne et al. 2009), the Kepler/K2 mission (Borucki et al. 2010), and the ongoing Transiting Exoplanet Survey Satellite (TESS) mission (Ricker et al. 2015). The updated list of known transiting BDs can be found in Šubjak et al. (2020). Brown dwarfs are also commonly found in binaries. Tens of them are listed in Liu et al. (2010). Two unique young systems with BDs in an eclipsing binary were reported by Stassun et al. (2006) and Triaud et al. (2020). Another unique structure involves systems of two BDs orbiting a primary star, such as HIP 73990 (Hinkley et al. 2015) and υ Oph (Quirrenbach et al. 2019). We can hence find BDs in systems with different structures, which creates opportunities to study different kinds of processes and interactions.

From this point of view, particularly interesting systems are those with wide BD companions around planet-host stars. To date, only nine such systems have been reported. If the mass of a companion is close to the stellar–substellar boundary, we included only a companion confirmed as a BD based on spectroscopic observations. The confirmed systems are: HD 3651 (e.g. Fischer et al. 2003; Mugrauer et al. 2006; Luhman et al. 2007; Burgasser 2007; Brewer et al. 2020), HIP 70849 (Ségransan et al. 2011; Lodieu et al. 2014), HD 168443 (Marcy et al. 2001; Pilyavsky et al. 2011), HD 65216 (Mayor et al. 2004; Mugrauer et al. 2007), HD 89744 (Korzennik et al. 2000; Mugrauer et al. 2004), HD 4113 (Tamuz et al. 2008; Ednie et al. 2018; Cheetham et al. 2018), GJ 229 (Geißler et al. 2008; Tuomi et al. 2014; Feng et al. 2020), HD 41004 (Santos et al. 2002; Zucker et al. 2003, 2004), and elndi (Scholz et al. 2003; McCaughrean et al. 2004; Feng et al. 2019). However, HD 65216, HD 41004, and ϵ Indi have different architectures (see Appendix C).

Planets can be significantly affected by wide BD companions through different processes, such as gravitational instability, accretion, velocities of colliding planetesimals, dissipation, or Lidov-Kozai effects (e.g. Boss 2006; Nelson 2003; Moriwaki & Nakagawa 2004). Regarding multiple stellar systems with planets, possible peculiarities in parameter distributions of inner planets have been searched for by many teams (e.g. Butler et al. 1997; Mugrauer et al. 2005; Desidera & Barbieri 2007; Bonavita & Desidera 2007). We can highlight the peculiarities in the mass-period and eccentricity-period distributions (e.g. Eggenberger et al. 2004; Zucker & Mazeh 2002). Such peculiarities reflect the interaction between inner planets and wide companions, placing constraints on various scenarios proposed for their formation and evolution (Eggenberger et al. 2004). Thus, it is reasonable to search for peculiarities in systems with wide BD companions that host planets.

Such systems offer great potential and opportunities to enrich our knowledge about both groups of objects and test our planetary formation and evolution concepts. A large sample of these systems is needed to reveal possible peculiarities and enable a detailed discussion. Such a sample would help answer fundamental questions such as: what the fraction of systems with wide BD companions that host planets is; whether they are common; and if there is any process that disfavours this scenario. In this paper we focus on a sub-sample of six stars with confirmed co-moving wide BD companions using high-resolution spectroscopic data. These systems are GJ 504 (Kuzuhara et al. 2013), HD 46588 (Loutrel et al. 2011), HD 203030 (Metchev & Hillenbrand 2006), HD 3651 (Mugrauer et al. 2006), HN Peg (Luhman et al. 2007), and HD 118865 (Burningham et al. 2013). We describe the target selection process in Sect. 2. We present new observations in Sect. 3 and make use of archival datasets in Sect. 4. We derive the physical parameters of our targets in Sect. 5 and investigate the nature of radial velocity (RV) signals to search for planets in Sect. 6. In Sect. 7, we compare the sample of systems with confirmed planets and wide BD companions previously published in the literature with single-planet-host stars and planet-host stars with wide stellar companions to discuss possible peculiarities in their parameter distributions. Finally, we summarise our final conclusions in Sect. 8.

2 Target justification

Following the discovery of a T4.5 dwarf companion at 6.3′ (~9000 au) from HIP 70849 (Lodieu et al. 2014), a K7V star that hosts a 9 MJup planet with an eccentric orbit (Ségransan et al. 2011), we searched the literature for other wide co-moving systems with one substellar component and a bright (V ≤ 6 mag) host suitable for intensive spectroscopic follow-up with the 1 m robotic Stellar Observations Network Group (SONG) telescope (Fredslund Andersen et al. 2019). Among the brightest primaries of wide substellar companions visible from the Northern Hemisphere, we recovered HD 3651 (Mugrauer et al. 2006). The other targets suitable for our project were at that time: HD 46588 (Loutrel et al. 2011), HN Peg (Luhman et al. 2007), GJ504 (Kuzuhara et al. 2013; Janson et al. 2013; Skemer et al. 2016). We subsequently added HD 203030 (Metchev & Hillenbrand 2006) when the magnitude limit of the SONG guiding was increased to V = 8.5 mag as well as HD 118865 (Burningham et al. 2013) to gauge the performance of the STELLar Activity (STELLA) 1.2 m robotic telescopes (Strassmeier et al. 2004). These six sources constituted our sample when we started the project in 2015. The parameters of the observed sample of stars are listed in Table 1. We emphasise that the population of wide L and T dwarf companions has increased significantly over the past decade, as compiled in Deacon et al. (2012) and Dal Ponte et al. (2020). Hence, this work can be considered as a pilot programme and the statistical results should be considered as preliminary.

3 Spectroscopic observations

We performed high-resolution spectroscopy with several telescopes and instruments whose observations are described below.

3.1 SONG spectroscopy

We observed our sample of stars with the robotic SONG Hertzsprung telescope (Fredslund Andersen et al. 2019) through a dedicated programme with nightly observations, weather permitting, for 2 yr (≥4 semesters) in most cases. The time interval of the observations, together with the number of acquired spectra, are reported in Table 2. We used the slit of 1.2 arcsec, yielding a spectral resolution of 90 000. To ensure sufficient count over the full wavelength range of SONG spectra, we employed exposure times between 360 and 600 s, leading to a S/N of at least 50 per resolution element for all observations. The numbers of gathered spectra for each system, together with the range of dates of observations, are in Table 2.

SONG is a 1m telescope located in the Observatorio del Teide in Tenerife, Canary Islands. It is equipped with a high-resolution echelle spectrograph operating in the visible band between 440 and 690 nm with an average dispersion of 0.002 nm pixel−1. The detector is an Ikon-L commercial charged-coupled device camera developed by Andor with a 2k × 2k chip size. The SONG spectra and the RVs have been kindly provided by the SONG team as derived by the iSONG software (Antoci et al. 2013) following the procedure described in Grundahl et al. (2017).

3.2 Calar Alto/CARMENES spectroscopy

We collected visible and near-infrared spectra for each system with the Calar Alto high-resolution search for M dwarfs with Exoearths with Near-infrared and optical Echelle Spectrographs (CARMENES; Quirrenbach et al. 2014). The time interval of the observations, together with the number of acquired spectra, are reported in Table 2. All observations were conducted in queue mode by the staff of the Calar Alto observatory, satisfying the requested conditions: seeing better than 2 arcsec and clear skies. We set the exposure times between 250 and 900 s depending on the star’s brightness, targeting the minimum signal-to-noise ratio (S/N) of 150 based on the estimates of the exposure time calculator.

CARMENES consists of two independent high-resolution échelle spectrographs in the visible (520–960 nm; R = 93 400) and near-infrared (960–1710 nm; R = 81 800), which are simultaneously fed through fibres. The data were reduced using CARACAL (Caballero et al. 2016), and the visible and near-infrared RVs were obtained with SERVAL (Zechmeister et al. 2018). SERVAL determines RV by co-adding all available spectra of the target with an S/N higher than 10 and creating a high-quality template of the star used as a reference spectrum. The RVs were corrected for barycentric motion, secular perspective acceleration, instrumental drift, and nightly zero points (Trifonov et al. 2018).

Table 1

System parameters for stars in our sample.

3.3 STELLA spectroscopy

We observed HD 118865 system with the two STELLA 1.2 m robotic telescopes located at Izaña Observatory in Tenerife (Strassmeier et al. 2004). The fibre-fed Echelle Spectrograph of STELLA with an e2v 2k×2k CCD detector covers the wavelength range between 390–880 nm and has the resolving power of R = 55 000. The spectra were automatically reduced using the STELLA data-reduction pipeline (Weber et al. 2008) based on the Image Reduction and Analysis Facility (IRAF; Tody 1993), and RVs were kindly provided by the STELLA team. The time interval of the observations, together with the number of acquired spectra, are reported in Table 2.

4 Supporting observational data

We searched for archival spectroscopic observations, which we used as supplemental data in our analyses. In addition, we also downloaded photometric data from TESS (Ricker et al. 2015) available for the stars from our sample.

4.1 Archival spectroscopy

GJ 504, HD 3651, HN Peg, and HD 203030 are systems that were already observed spectroscopically. We downloaded public archival data to complement our own observational datasets.

For GJ 504, we checked the HARPS-N archive and noticed that additional spectra had been collected with the High Accuracy Radial velocity Planet Searcher for the Northern hemisphere (HARPS-N; Cosentino et al. 2012) by the GAPS team between 9 June 2016 and 1 April 2018, amounting to a total of 106 spectra. We re-processed all HARPS-N spectra with the SERVAL pipeline to get RV measurements and activity indicators. Additionally, we found 58 spectra (Fischer et al. 2014) collected with the Hamilton Echelle Spectrometer at the LICK observatory (Vogt 1987); however, their relatively low cadence over the long baseline do not make them very useful as the star shows a high level of activity (we do not see any significant signal in the periodograms). For the same reason, we did not use 38 RVs (Bonnefoy et al. 2018) collected with the Spectrographe pour l’Observation des Phénomènes des Intérieurs stellaires et des Exoplanètes (SOPHIE; Bouchy & Sophie Team 2006). In their periodogram, we only see peaks close to the rotation period of the stars visible in all used datasets.

For HD 3651, we also used RVs published in Brewer et al. (2020). These authors report 61 spectra from the Extreme PREcision Spectrometer (EXPRES; Jurgenson et al. 2016) mounted on the 4.3 m Lowell Observatory Discovery Channel Telescope (DCT). We also included an additional 161 archival data obtained with the High Resolution Echelle Spectrometer (HIRES; Vogt et al. 1994) mounted on the 10m Keck Telescope with the 17-yr time baseline (Butler et al. 2017), 155 archival LICK RVs (Fischer et al. 2014), 35 archival RVs obtained with the High Resolution Spectrograph (HRS; Tull 1998) mounted on the 9.2 m Hobby–Eberly Telescope (HET; Wittenmyer et al. 2009), and four archival RVs obtained with the Tull spectrograph (Tull et al. 1995) at the 2.7 m Harlan J.Smith Telescope (Wittenmyer et al. 2009).

For HD 203030, we found 17 Keck HIRES RVs (Butler et al. 2017). However, with the 17-yr time baseline and the star’s level of activity, these data are not helpful, and we do not observe any significant signal in the periodogram.

Finally, for HN Peg, we found 37 LICK RVs (Fischer et al. 2014) and 22 HARPS RVs. However, because of the RV scatter caused by the stellar activity, such small datasets are also not helpful compared to the SONG dataset. The complete list of available archival data is reported in Table 2.

Table 2

Spectroscopic observations for our sample of stars.

4.2 TESS photometry

TESS observed each of our targets except HN Peg at least in one sector at a two-minute cadence mode during its prime mission. The full list of observations is summarised in Table 3. We used the lightkurve package in Python (Lightkurve Collaboration 2018) to download TESS target pixel files from the Mikulski Archive for Space Telescopes (MAST)1. We then selected optimal aperture masks to extract light curves (LCs) for each system, which we corrected for outliers and normalised. On them, we performed the pixel level de-correlation method (Deming et al. 2015) to remove systematics. The final TESS LCs are shown in the middle of Fig. 1. None of our targets is recognised as a TESS object of interest, meaning that no obvious transit-like feature has been identified in the LCs.

We used Tpfplotter (Aller et al. 2020) to overplot the Gaia DR2 catalogue to the TESS target pixel file (tpf) to investigate possible diluting sources in TESS photometry with the limiting difference in magnitude of 10. Tpf images for our sample of stars created with tpfplotter can be seen on the left-hand side of Fig. 1. There is only one additional source between TESS pixels used in SAP in the case of GJ 504. This star has identification Gaia ID 3732539649257672704 and Gaia G magnitude of 14. According to Gaia colour bands, we classify this object as K7–K9 spectral type, with G – RP = 0.89 mag corresponding to K8–K9, and BP – RP = 1.72 mag corresponding to K7–K8. To compute the spectral type, we used the up-to-date version2 of the dwarf colour sequence from Pecaut & Mamajek (2013). For HD 203030, there are five additional sources within the aperture of the TESS pixels. The full list of these sources with relevant information is displayed in Table 4. We conclude that these sources are too faint compared to GJ 504, HD 203030, respectively, to yield any significant dilution. We did not find any diluting sources in the TESS apertures for the rest of the systems in our sample.

Table 3

Dates of TESS observations for our sample of stars.

5 Stellar and brown dwarf parameters

In this section, we derive the stellar parameters of stars in our sample as well as the ages of individual systems, which are then used to infer the ages of wide companions and derive their parameters. We need to know the parameters of the host stars if we want to derive parameters of potential planets, and if we want later discuss peculiarities in the parameter distributions of these planets, it is crucial to describe every known object in these systems. We did this for all studied systems regardless of whether we found any planetary candidate.

thumbnail Fig. 1

Analysis of rotation periods. Left: Gaia DR2 catalogue overplotted on the TESS tpf images. Middle: LCs observed by TESS. Right: Marginalised posterior distributions of the rotation period from GP modelling. From top to bottom, we show GJ504/TIC 397587084, HD 3651/TIC 434210589, HD 46588/TIC 141523112, HD 118865/TIC 365224537, and HD 203030/TIC 25559430.

5.1 Stellar parameters with iSpec and VOSA

We used the iSpec framework (Blanco-Cuaresma et al. 2014; Blanco-Cuaresma 2019) to derive the parameters of the host stars from the co-added CARMENES spectra, iSpec determines stellar parameters by minimisation of the χ2 value between the calculated synthetic spectrum and observed spectrum. To determine the effective temperature Teff, metallicity [Fe/H], surface gravity log g, and the projected stellar equatorial velocity υ sin i, we followed the same procedure as in Fridlund et al. (2017). The whole procedure is described in detail in Appendix A.1, and we report the stellar parameters for the stars of our sample in Table 5.

As a sanity check, we also analysed the spectral energy distribution (SED) with the Virtual Observatory SED Analyser (VOSA3; Bayo et al. 2008). VOSA performs the χ2 minimisation procedure to compare theoretical models with the observed photometry. For our SED fitting, we use the Strömgren-Crawford uvbyβ (Paunzen 2015), Tycho (Høg et al. 2000), Gaia DR2 (Gaia Collaboration 2018b), Gaia early data release 3 (eDR3; Gaia Collaboration 2021), 2MASS (Cutri et al. 2003), AKARI (Ishihara et al. 2010), and WISE (Cutri et al. 2021) photometry. The whole procedure is described in detail in Appendix A.2, and we report the stellar parameters for the stars of our sample in Table 5.

Table 4

Additional sources within the TESS apertures for our sample of stars.

5.2 Analysing the surface rotation

To determine the rotation period from the TESS LCs, we apply generalised Lomb–Scargle (GLS) periodograms (Zechmeister & Kurs ter 2009) investigating the most dominant signals. Plots of periodograms for individual stars can be found in Fig. 1. GJ 504 and HD 203030 show clear variations with the periods of 3.4 days and 6.7 days, respectively, which we interpret as the rotation periods. HD 3651 does not show clear variations but only a long trend; hence we interpret the rotation period to be larger than the TESS data baseline. It is consistent with the period of 44.5 days derived through the calibration from the value of log RHK′$R_{{\rm{HK}}}^\prime $ by Fischer et al. (2003). Brewer et al. (2020) then searched for photometric variations using 1192 photometric observations collected over the period of 25,yr with the 0.75 m Automatic Photoelectric Telescope (APT) at Fair-born Observatory in southern Arizona. However, they did not find any significant variability within any observing season. Finally, after we removed long trends in the HD 46588 and HD 118865 datasets, we could identify variations with the periods of 10.3 days and 6.2 days that we interpret as the rotation periods. The variations in the HD 118865 LC are not so clear as for other objects; however, we used this period only to derive the bottom limit for the age, as can be seen in the next section. We did not find any contradictions with the rotation periods reported in the literature. For example, in the catalogue of rotation periods by Wright et al. (2011) we can see the rotation period of 6.67days for HD203030, 4.86days for HN Peg and 48 days for HD 3651. Donahue et al. (1996) then reported the rotation period of 3.33 days for GJ 504.

5.3 Age analysis

To determine the age of the sample stars, we provide an extensive analysis of several complementary age indicators. We include stellar isochrones fitting, gyrochronology analysis, lithium equivalent width (EW), X-ray luminosity, and membership to young associations. Our effort is to examine each age indicator separately to provide the age intervals for each of them and to determine the final age as an overlap between these intervals. A detailed description of each age indicator can be found in Appendix B, and the results are listed in Table 6.

We found that all age indicators for our sample of stars are quite consistent with each other. Two inconsistencies are that the gyrochronology predicts a slightly lower age of HD 203030 and the isochrone fitting for the GJ 504, HD 203030, and HD 46588 gives older ages than the rest of the indicators. However, we found agreement in most cases when considering 95% confidence intervals from isochrone fitting. The GJ 504 age is intensively discussed in the literature. Kuzuhara et al. (2013) estimated the age of GJ 504 to be 160−60+350$160_{ - 60}^{ + 350}$ Myr using gyrochronology and chromosphere activity of the star. Fuhrmann & Chini (2015); D’Orazi et al. (2017) have found that the isochrones comparison suggests an older age between 1.8 and 3.5 Gyr. Authors speculated that the recent merging of hot Jupiter companion could explain the star’s high activity level. Bonnefoy et al. (2018) have recently revisited the system parameters. Instead of using an effective temperature as an input to isochrone fitting, they used an interferometric radius of R⋆ = 1.35 ± 0.04 R⊙ for GJ 504. However, the fact that we got, as an output from isochrone fitting, the radius with similar uncertainty as these authors measured suggests that both analyses should be equivalent in terms of age determination. They found two isochronal age scenarios: the young one with an age of 21 ± 2 Myr and the old one with an age of 4 ± 1.8 Gyr.

We confirm that most age indicators lead towards the relatively young age of several hundred megayears. Similarly to Bonnefoy et al. (2018), we also found that isochrone fitting gives two possible age scenarios. It can be seen in Fig. 2, where we plot GJ 504’s luminosity from the SED analysis and effective temperature, together with the MIST stellar evolutionary tracks (Choi et al. 2016). We also note that the age depends on the isochrone model used. Using the PARSEC isochrones (Bressan et al. 2012) we found the age of 3.8−1.1+1.5$3.8_{ - 1.1}^{ + 1.5}$ Gyr, while for the MIST isochrones we found 2.6−1.3+1.2$2.6_{ - 1.3}^{ + 1.2}$ Gyr. Similarly to other stars in our sample, in Table 6, we provide an age for GJ 504 as an overlap of most of the activity indicators. However, we do not consider this age final, and we are open to both younger and older scenarios. That is why we keep this system in our sample as a system with a potential wide BD companion.

If we consider that BDs cool down with age, their detection becomes more challenging as they get older. In this context, it is not surprising that a lot of the stars in our sample are relatively young (i.e. 1 Gyr or lower). Nonetheless, we found a few systems older than 2.5 Gyr.

thumbnail Fig. 2

Luminosity versus effective temperature plot. Curves represent MIST isochrones for ages: 10 Myr (blue), 20 Myr (orange), 30 Myr (green), 50 Myr (red), 100 Myr (purple), 1 Gyr (pink), 3 Gyr (grey), 6Gyr (chartreuse), and 10 Gyr (celeste), and for [Fe/H] = 0.25. The brown point represents the parameters of GJ 504 with their error bars.
Table 5

Physical parameters for stars in our sample.

Table 6

Age intervals for stars in our sample from different indicators together with the final adopted intervals.

5.4 Revised parameters of the wide BD companions

We used the SpeX Prism Library Analysis Toolkit (SPLAT; Burgasser & Splat Development Team 2017) to derive the parameters of the wide BD companions in our sample. SPLAT is a python-based package designed to interface with the SpeX Prism Library (SPL; Burgasser 2014), which is an online repository of over 2000 low-resolution, near-infrared spectra of stars and BDs. The package enables a conversion between the observable (temperature, luminosity, surface gravity) and physical parameters (mass, radius, age) of BDs using published evolutionary model grids. A more detailed description can be found in Appendix A.3, and results are summarised in Table 7.

According to the derived mass intervals, we confirm all companions except GJ 504b to be BDs. Using the adopted age from Table 3, we find GJ 504b in the planetary regime. However, as previously discussed, we do not exclude older ages from isochrone fitting, which places the companion in the BD regime.

6 Frequency analysis and stellar activity

We performed a frequency analysis using GLS periodograms of RV measurements for each target to look for possible companions. We note that TESS LCs do not reveal obvious transits during the 27 days of observations per sector, implying that we cannot confirm any short-periodic Keplerian signal. Instead, we investigate various stellar activity indicators to discuss the nature of the most significant signals found in periodograms. The SONG, STELLA, and CARMENES RV measurements for all stars in our sample are available at the CDS.

The SONG datasets create the core of our project. The timescales and frequencies of observations make them the most suitable for frequency analysis. Unfortunately, we cannot provide many stellar activity indicators for SONG data as spectra are calibrated using the iodine cell technique, whose lines contaminate the spectrum. Furthermore, the SONG spectrograph’s wavelength coverage does not cover the Ca H&K doublet below 400 nm (393.366 & 396.847 nm). However, we modified an in-house python pipeline designed to measure activity indicators in STELLA spectra (Weber et al. 2008) to be usable on SONG datasets. The pipeline corrects spectra for RVs, computes fluxes in selected wavelength regions, and compares the flux of the continuum with the flux in selected spectral features to track the changes in line profiles. We considered windows around well-known spectral features (e.g. Hα at 656.281 nm, NaD at 589.592 & 588.995 nm, and He at 587.564nm) and continuum regions from the literature (e.g. Cincunegui et al. 2007; Boisse et al. 2009), or set them manually. We also check the results with CARMENES activity indicators to verify the method. Based on the observed signals and the comparison with CARMENES activity indicators, the Hα line appears to be the most reliable stellar activity tracker.

Additionally, we used archival HARPS-N observations for GJ504, which we reduced with the SERVAL pipeline (Zechmeister et al. 2018) to derive RVs and measure different activity indicators (Ha, chromatic index, differential line width, and NaD). We also collected CARMENES RVs for each star, also reduced with SERVAL. These observations complement the SONG datasets despite the small number of epochs over a short baseline.

Table 7

Parameters of wide companions around the stars from our sample.

thumbnail Fig. 3

GLS periodograms of the SONG RVs (blue) and the Hα activity indicator (red) of HD 3651: (a) SONG RVs, (b) SONG RVs minus the 62-day model, and (c) Hα. The vertical green line represents the orbital period of the confirmed planet, and the black line the 1-yr window function. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.

6.1 HD3651

In the SONG periodogram of RVs, we observe the strongest signal at the period of the confirmed planet (see Fig. 3). The periodogram of RVs shows a forest of peaks with a maximum at ~62 days, consistent with the orbital period of the existing planet (Fischer et al. 2003; Brewer et al. 2020). To explore further the origin of this signal, we investigated the Hα activity indicator derived specifically for the SONG dataset, whose periodograms are displayed in Fig. 3. A similar forest as in the periodogram of RVs is also seen in the periodogram of Hα. However, there is no peak at ~62 days, and we found only a weak correlation between RVs and Ha. These peaks can be linked with stellar rotation, which Fischer et al. (2003) derived from the Ca II H and K line emission to be ~44.5days. Fitting the orbital solution using SONG observations, we obtained a residual root-mean-square (RMS) of 5.87 m s−1, using the CARMENES dataset of 2.32 m s−1, and only of 58 cm s−1 using the EXPRES dataset (Brewer et al. 2020), suggesting a low level of activity.

After subtracting the Doppler reflex motion of this planet, we can see significant peaks close to 1 yr. We interpret this signal as the 1-yr window function of the SONG dataset. We used a sinusoidal fit to derive the semi-amplitude of about 3 m s−1, much smaller than those discussed below.

We recovered the RV signal with LICK, KECK, SONG, CARMENES, and EXPRES using the Monte Carlo-Markov chain (MCMC) method implemented in the Exo-Striker package (Trifonov 2019). We set 20 walkers and ran 1000 burning phase steps and 10 000 MCMC phase steps in our analysis. We consider velocity offsets as the free parameters to fit simultaneously datasets originating from different spectrographs. We summarise the updated planetary parameters in Table 8. The orbital solution is plotted in Fig. 4 and the correlations between parameters together with the derived MCMC posterior probability distributions are presented in Fig. D.2.

In summary, we confirm the presence of a planet in this system. We agree with previous studies that the low levels of stellar activity (Wright et al. 2004) and photometric variability, along with the low scatter in RV measurements, make it very unlikely that the RV variations are caused by stellar activity. We did not find evidence of an additional companion in the system. Wittenmyer et al. (2013) proposed a two-planet solution for HD3651, with the second planet in 2:1 resonance. We can rule out such a solution and confirm that the solution with a single eccentric planet also leads to the lowest fitted χ2 value. We also checked if the transit would be visible in the TESS data. Unfortunately, transits are just outside of the observing window in both sectors 17 and 57.

Table 8

Planetary parameters.

thumbnail Fig. 4

Orbital solution for HD3651, with the Exo-Striker RV model shown in black. The orbital solution is derived by simultaneously fitting RVs from LICK (grey), KECK (orange), SONG (blue), visual CARMENES (green), near-infrared CARMENES (cyan), and EXPRES (red).
thumbnail Fig. 5

GLS periodograms of RVs and activity indicators of GJ 504: (a) SONG RVs, (b) SONG Hα indicator, (c) HARPS-N RVs, (d) HARPS-N RVs after fitting a sinusoid of P = 3.7 days, and (e) HARPS-N Hα indicator. Vertical green lines represent the stellar rotation period and its 1-day alias. The vertical orange line represents the most significant signal in the SONG RVs at 292.74 days. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1%.

6.2 GJ 504

The GLS periodogram of the SONG data shows a significant peak at 3.67 days and another at 1.39 days (Fig. 5), which we assign to the rotation period and its 1-day alias. These two peaks also stand out in the periodograms of the HARPS-N and CARMENES datasets. In Sect. 5.2, we derive a rotation period of 3.4 days from the TESS LC.

The signal of the rotational period is not the most significant in SONG data. The highest peak is found at ~300 days. We can see a similar peak even in the HARPS-N dataset despite the shorter timescale of observations. The short timescale makes the CARMENES dataset unsuitable for interpreting such a long signal; however, the observed trend looks to agree with the period of ~300 days. To investigate this signal in more detail, we used the SONG Hα activity indicator together with the HARPS-N Hα activity indicator (Fig. 5). In the SONG Hα we see the signal at ~300 days, and a similar peak can also be seen in the HARPS-N Hα, suggesting that this signal is most likely associated with the stellar activity.

We plot the fit of the signal at ~300 days for SONG, HARPS-N and CARMENES RVs in Fig. 6. Such a short activity cycle was previously observed for F-type stars (see Sect. 6.4); however, it was not observed for a G-type star.

thumbnail Fig. 6

SONG RVs of GJ504 (blue), HARPS-N RVs (green), and CARMENES RVs (orange) together with the inferred RV model of the 292.74-day signal (solid black line). The nominal error bars are in blue and red and are hardly visible for the HARPS-N dataset. Bottom panel: Residuals of the RV model.

6.3 HN Peg

The GLS periodogram of the SONG RVs shows the most significant peak at 5.1 days and another peak at 1.24 days (Fig. 7), which is a 1-day alias of the 5.1-day signal. The periodogram of RVs also shows a peak at 2.54 days and its 1-day alias at 1.64 days. The periodogram of the CARMENES data does not reveal any significant signal.

TESS did not observe this target yet; however, Messina & Guinan (2003) determined the rotation period of the star. They performed photometric observations with three different Automatic Photoelectric Telescopes at Fairborn Observatory in southern Arizona and inferred a variable stellar rotation between 4.59 and 5.17 days. Hence, we interpret the 5.10-day signal in RVs as a rotational period of the star and the 2.54-day signal to be the first harmonic of the rotation period. We plot the fit of the 5.1-day signal in Fig. 8.

We can see the peak at 5.1 days with its 1-day alias in the Hα activity indicator. This signal becomes more significant after removing a 420-day signal, which we interpret as systematic due to the window function. We confirm that the 5.1-day signal is linked with stellar activity. To conclude, we interpreted all signals to be linked to the stellar activity and did not find any evidence of a planetary companion.

6.4 HD 46588

The most dominant peak in the GLS periodogram of the SONG RVs is at 127 days (Fig. 9). In the CARMENES VIS RVs, we also detect a peak close to 127 days but poorly defined because of the short baseline. We find a strong correlation of 0.79 between the chromatic index (CRX) and the CARMENES RVs at 127 days, suggesting that this peak is associated with the stellar activity. This interpretation is corroborated by the SONG Hα indicator of the SONG dataset. We interpret this signal as the magnetic cycle of the star. We plot the fit of this signal for the SONG and CARMENES RVs in Fig. 10.

In the SONG periodogram, we observe two other significant peaks at 224 days and 1 yr. The 1-yr peak is visible in the Hα indicator, representing the 1-yr window function of the SONG dataset. However, this is not the case for the peak at 224 days; hence, there might be a chance it might have a Keplerian origin. We computed the statistical significance of the peak at ~224 days via the bootstrap randomisation process with 106 realisations (Murdoch et al. 1993). We found a false-alarm probability (FAP) lower than 1%, which suggests that it is unlikely that this peak is due to random noise. However, we cannot say whether this signal is due to a planetary companion or connected to the stellar magnetic cycle, as the SONG data does not always behave as the simple sinusoidal model predicts, making the magnetic activity more complex. Further monitoring is needed to understand this system better; however, we report this system to have a possible planetary candidate. Fitted planetary parameters are summarised in Table 8. The fit was performed on the RV residuals after the removal of the activity cycle with a period of 127 days. The orbital solution is plotted in Fig. 11, and the correlations between parameters together with the derived MCMC posterior probability distributions are presented in Fig. D.3. We also performed a multidimensional GP approach (Rajpaul et al. 2015) to characterise the stellar and planetary signals in the SONG data using the PYANETI code (Barragán et al. 2022). We used the Hα indicator to constrain the stellar signal. We set wide priors for planet parameters based on the periodogram and the initial fit (see Fig. 11). We found planetary parameters consistent in 1er with the previous fit. Derived planetary parameters are summarised in Table 8. The plot of Hα and RV time series and inferred stellar and planetary models is shown in Fig. D.1. We can see that the stellar+planetary model can describe the observed RVs quite well.

HD 46588 is extremely interesting in terms of stellar activity. The Sun has a 22-yr magnetic cycle. However, the physics underlying this phenomenon is still not well understood, similarly to activity cycles in other Sun-like stars. Long-term observations and monitoring of stars’ chromospheric activity can be used to study activity cycles and determine their periods (Wilson 1978; Baliunas et al. 1995; Hall et al. 2007; Isaacson & Fischer 2010; Hempelmann et al. 2016). Baliunas et al. (1995) measured activity cycles for more than 40 stars, with periods ranging between 2.5 and 20 yr.

Baliunas et al. (1995) observed the star τBoo (HD 120136), which first appears to have a typical chromospheric cycle of 11.6+0.5 yr. τBoo is an F7 spectral type star with an M2 type companion on a close orbit of 3.3 days. The rotation period is determined to be close to this value, indicating synchronisation. However, what makes this star interesting is evidence of additional variability in the Call line with a significantly shorter period than the original chromospheric cycle. Baliunas et al. (1997) determined a period of 116 days, later confirmed by Mengel et al. (2016) and Mittag et al. (2017) investigating the S-index with the NARVAL and TIGRE instruments, respectively. Mittag et al. (2017) also showed that the X-ray data support a periodicity of about 120 days, addressing an interesting question of whether the fast activity period of τBoo is representative of main-sequence F stars. Mittag et al. (2019) used analysis of S-index time series of F-type stars taken with the TIGRE telescope to discuss this question. They detect three more short-term cycles and one candidate between 0.5 and 1 yr. They do not provide the number of investigated F-type stars, preventing us from discussing the statistics. However, τBoo is still the star with the fastest magnetic cycle ever observed.

In this context, HD 46588 is a twin of τBoo. The star has the same F7 spectral type and hosts an L9 type companion at the projected physical separation of 1420 au (Loutrel et al. 2011). We found evidence for a chromospheric cycle at 127 days. New discoveries indeed support that short-term activity cycles can be typical in F-type stars. Furthermore, we derived the age of HD 46588 about 2.5 Gyr, which indicates that such short-term activity cycles can cause strong RV variations also for relatively old stars. HD 118865 is the other F7 star in our sample. Our observations are only about 150 days for HD 118865, and we observe just a linear trend in RVs (Sect. 6.6). Further monitoring of F stars will bring more light to the discussion. However, the population of such stars with short-term activity cycles is starting to grow.

thumbnail Fig. 7

GLS periodograms of RVs (blue) and activity indicators (red) of HN Peg: (a) SONG RVs, (b) SONG RVs after fitting a sinusoid with a period of 5.1 days, (c) SONG Hα indicator, and (d) SONG Hα indicator after fitting a sinusoid with P = 420 days. Vertical green and orange lines represent the star’s rotation period and the first harmonic of the rotation with their 1-day alias, respectively. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.
thumbnail Fig. 8

SONG RVs of HN Peg (blue) together with the inferred RV model of the 5.1-day signal (solid black line). The nominal error bars are in the same colours.
thumbnail Fig. 9

GLS periodograms oſ SONG RVs (blue) and activity indicators (red) and CARMENES RVs and CRX (green) of HD 46588: (a) SONG RVs, (b) SONG RVs after removing the model with the period of 127 days, (c) SONG Hα activity indicator, (d) SONG Hα indicator after fitting a sinusoid with P = 365 days, (e) SONG window function, (f) CARMENES RVs, and (g) CARMENES CRX. The vertical green line represents the short-term activity cycle, the orange line represents the possible planetary candidate, and the black line represents the 1-yr window function. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.
thumbnail Fig. 10

SONG RVs of HD 46588 (blue) and CARMENES RVs (red and green) together with the inferred RV model of the 127-day and 224-day signals (solid black line). The nominal error bars are in the same colours.
thumbnail Fig. 11

Orbital solution for HD 46588 showing the RV model in black. Blue points represent the SONG RVs, and red and green points represent the CARMENES RVs. The nominal error bars are in the same colours.
thumbnail Fig. 12

GLS periodograms oſ SONG RVs (blue) and Hα activity indicator (red) of HD 203030: (a) SONG RVs, (b) SONG RVs after fitting sinusoid with P = 2.23 days, (c) SONG Hα indicator. Vertical orange lines represent the star’s rotation period and its 1-day alias, and green lines represent the planetary candidate of the rotation period with its 1-day alias. Horizontal dashed lines show the theoretical FAP levels of 10%, 1% and 0.1% for each panel.

6.5 HD 203030

In the periodogram of the TESS LC (Fig. 12), we observed two strong peaks at 6.5 and 13 days. Typically we would attribute peaks to be the rotation period with the first harmonic. However, visual investigation of the LC reveals strong variations at 6.5 days and the gap in the data so that the middle period is missing. Hence, the 13-day peak is an artefact of data sampling. We can confirm such a hypothesis with the vsini value derived from spectra. Assuming an inclination of 90 degrees, we can derive the upper limit for the rotation period, which is 7.2 days, close to 6.5 days but much lower than 13 days.

The GLS periodograms for the SONG RVs show a significant peak at 2.23 days, with its 1-day alias at 1.81 days. After fitting this signal with a simple sinusoidal (Fig. 13), we observe a peak at 6.5 days, representing the stellar rotation. We found an RMS scatter due to activity to be about 35 m s−1, higher than the semi-amplitude of signals in the periodogram of HD 203030 and much higher than 5.87 m s−1 inferred for the quiet star HD 3651. Hence, we conclude that stellar activity plays a dominant role in RVs, and the 2.2-day signal is probably just the second harmonic of the rotation period. In the periodogram of CARMENES RVs, we do not see any significant peak. SONG Hα indicator reveals a signal at 7.14 days, while the CARMENES Hα and S-index indicators both reveal a signal at 6.62 days, confirming the star’s rotation period. We can also see a peak close to 2.23 days in S-index. All in all, we report that the variations in RVs are probably associated with the stellar activity.

thumbnail Fig. 13

SONG RVs of HD 203030 (blue) together with the inferred RV model of the 2.23-day signal (solid black line). The nominal error bars are in the same colours.

6.6 HD 118865

In the STELLA RVs, we observe a decreasing trend, which is not observed in the CARMENES dataset. It leads to a variety of possible solutions. In Fig. 14 we illustrate one solution at a period of ~575 days. We observe a similar trend in the STELLA He activity indicator (He I line at 587.56nm; Fig. 15). Hence, we prefer the stellar activity scenario over the planetary companion even though the relatively large semi-amplitude and the fact that the star has an age of about 1 Gyr or older. The star has an F spectral type, and as we discussed above, the magnetic cycle with a period of hundreds of days would not be surprising even for relatively old stars. Further spectroscopic monitoring is needed to constrain the period of this signal.

7 Discussion

7.1 The role of wide companions in planet formation and evolution

Wide stellar companions can significantly affect the physical parameters of inner planets. Peculiarities in their parameter distributions were predicted (e.g. Mayer et al. 2005; Kraus et al. 2012; Kaib et al. 2013) and observed (e.g. Zucker & Mazeh 2002; Eggenberger et al. 2004; Fontanive & Bardalez Gagliuffl 2021). Eggenberger et al. (2004) compared orbital period, minimum planetary mass, and eccentricity for a sample of planets in systems with and without a wide stellar companion. They discussed two possible peculiarities identified in the distributions of short periodic planets. First, planets with periods below 40 days appear to have lower eccentricities when part of multi-stellar systems compared to planets around single stars. Second, the most massive short-periodic planets in their sample all belong to multi-stellar systems. However, at that time, only about a dozen multiple stellar systems with an exoplanet were known. Fontanive & Bardalez Gagliuffi (2021) performed an extensive search for visual co-moving binary companions to exoplanethost stars using Gaia DR2 data in addition to known systems from literature. They compiled 938 stars, from which 186 are binaries, and 32 belong to hierarchical triples. They used all systems to study peculiarities in their parameter distributions similarly to Eggenberger et al. (2004). Specifically, they studied the mass and RV semi-amplitudes of planets, masses of primaries, and masses and separations of wide companions in these systems. To highlight some of their results, they found that (i) more massive planet-host stars are more often in multi-stellar systems, (ii) only close binaries (< 1000 au) seem to influence the formation or evolution of inner planets, and (iii) the mass of the stellar companions has no significant effect on planetary properties.

We did not find any planets in our sample of stars with wide BD companions (only one planetary candidate in HD 46588), so we used a different approach to discuss possible peculiarities in parameter distributions. We downloaded the catalogues of systems of single planet-host stars and planet-host stars with wide stellar binaries from Fontanive & Bardalez Gagliuffi (2021) to produce similar plots as in Eggenberger et al. (2004) and Fontanive & Bardalez Gagliuffi (2021). We also consider the planet’s eccentricity distribution as it was not discussed in Fontanive & Bardalez Gagliuffi (2021). To these plots, we added for comparison the HD 3651 planet, HD 46588b planetary candidate and the four planets from systems with known wide BD companions from the literature (red points in Fig. 16) discussed in detail in Appendix C. We excluded HD 65216, HD 41004, and elndi, as these systems have different architectures. We also excluded GJ 229 because we are sceptic about the planetary nature of the reported signals.

To better understand our data, we may firstly compare the separations and masses of wide BD companions from the sample of the systems with known planets (discussed in Appendix C) and our sample of five systems (we put HD 3651 to the first group). Both samples are small; however, we did not notice any crucial differences. The first sample spans separations from 3 au up to 9000 au (3, 23, 476, 2500, 9000) while the second from 487 au to 9200 au (487, 784, 1420, 9200). With the current mass uncertainties, both samples practically span companion masses through the whole range typical for BDs.

The plot of the minimum planetary mass versus the orbital period of planets can be seen in Fig. 16. We also divided systems of single planet-host stars into two categories: Group 1 contains systems with one planet orbiting a star (black points in Fig. 16), and Group 2 is made of systems with multiple planets orbiting a star (grey points)4. Similarly, we divided multi-stellar systems into two categories: Group 3 contains systems with one planet and a stellar companion orbiting a primary star (blue points in Fig. 16), and Group 4 is made of systems with a stellar companion and multiple planets (green points). The final sample consists of 504 systems in Group 1, 479 systems in Group 2, 173 systems in Group 3, and 103 systems in Group 4.

We do not see many planets more massive than 0.1 MJ from Group 2 and Group4 at close orbital periods. Multi-planetary systems with a planet’s orbital periods below ~ 100 days mostly host less massive planets. The inward migration of more massive planets would disrupt the orbits of inner planets, which would lead to collisions or their ejection (Mustill et al. 2015; Saffe et al. 2017). We can also see that the upper end of the minimum planetary mass actually represents the population of BDs. While this paper focuses on the wide BD companions, here, we can also see BDs in closer orbits. Most of the systems in this mass region are from Group 1 and Group 3; hence, no additional planets are detected, suggesting that close BDs might prevent their existence. However, one would need to check how many of these systems were spectroscopically followed up with sufficient precision to detect planets. We also observe that the most distant companions in the plot are BDs, which is not so surprising because they are brighter than planets and, hence, easier to detect by direct imaging.

As the majority of planets in systems with wide BDs lies in the mass region of Jovian planets between 0.1 and 15 MJ (Mordasini 2018; Spiegel et al. 2011), we took only planets from this region to create kernel density estimates (KDEs) of the distributions of planet period. We chose a Gaussian kernel and used the cross-validation approach to derive the KDE band-widths providing good insights into potential underlying trends. The only planetary system with a wide BD that does not lie in this mass region is GJ 229, and we reported the RV signal in GJ 229 as a planetary candidate rather than a confirmed planet (Appendix C). We created the KDEs for three groups: planets in systems with a one star (Group 1 + Group 2), planets in systems with multiple stars (Group 3 +Group 4), and planets in systems with known wide BD companions. The distributions of the planetary period can be seen in Fig. 17. We observe the bimodal distribution of giant planets in the first two groups, which have two maxima around ~ 5 days and ~ 1000 days. However, both maxima are slightly shifted, and we observe an enhancement of short periodic planets in systems with a wide stellar companion. Giant planets are thought to form via core accretion in a protoplanetary disk at larger distances from stars than are often observed. Subsequent inward migration thus plays an important role in the existence of planets across a large variety of observed orbital periods (e.g. Lin et al. 1996; Bodenheimer et al. 2001). Hence, enhanced migration seems to work for a large number of short-period planets. We do not observe such bimodal behaviour in the distribution of planets in the systems with a wide BD, as no short periodic planet with an orbital period below ten days is known so far. Our survey is sensitive to such planets, so we should have easily detected them (Sect. 7.2). To investigate the significance of these results, we performed two-sided Kolmogorov-Smirnov tests comparing each sub-population of planets using the python package Scipy, specifically the scipy.stats.ks_2samp5 function. In other words, we tested the null hypothesis that the samples are drawn from the same distribution and used a p-value to support or reject this hypothesis. Comparing the distribution of planets around single stars with planets around stars with a stellar companion, we obtained the p-value of 0.029. However, comparing the group of planets around stars with a wide BD with planets around single stars, we obtained a p-value of 0.59, and with planets around stars with a stellar companion, we obtained a p-value of 0.41. Hence, we cannot confirm that the group of planets around stars with a wide BD follows its own distribution.

The distribution of minimum planetary mass can be seen in Fig. 18. Here we used all planets and divided them into the same three groups. Except for the population of planets around stars with a wide BD, we observe the bimodal distributions with two maxima around ~0.01 MJ and ~1 MJ. Using the two-sided Kolmogorov-Smirnov test, we obtained a p-value of 0.08 comparing the planets around stars with a BD companion to planets around single stars and a p-value of 0.34 comparing the planets around stars with a BD companion to planets around stars with a stellar companion. It can suggest that a wide BD influences the mass distribution of planets in a similar way as a wide stellar companion, and these planets follow a similar distribution. Or there may even be a gap against low-mass planets in systems with a wide BD. However, these results can be affected by several factors. As BDs cool in time and become less luminous, their detection is easier when the system is young. The stellar activity of such young stars then influences the detection limits of RV campaigns and can cause bias in the non-detection of low-mass planets. In Sect. 7.2 we show our detection limits, which are often not sufficient to detect such low-mass planets. These insufficient detection limits are also caused by typically relatively massive primary stars in systems with a wide BD. We also observe that sub-Jovian planets (MPsini ≤ 0.1 MJ) are more often around single stars than around stars with a stellar companion, the trend already mentioned in Fontanive & Bardalez Gagliuffi (2021). The trend is probably caused by the fact that low-mass planets are easier to detect around low-mass M stars causing deeper transits and larger RV semi-amplitudes, and such stars have a lower rate of multiplicity in comparison to more massive stars (Salama et al. 2022).

The plot of the eccentricity versus the orbital period of planets can be seen in Fig. 19. Colours represent the previous division into four groups plus planets around stars with a wide BD companion (red). To compare different groups, we used the same approach as before, creating KDEs for each group (see Fig. 20). Group 1 has visually a slightly different distribution than Group 3 with an enhancement of small (≤0.1) and high (≥0.8) eccentricities. Comparing these two samples, we obtained a p-value of 0.012 from the two-sided Kolmogorov-Smirnov test, which means that these differences have a relatively high confidence level. Such enhancement of low eccentric planets is not surprising if we link it with the enhancement of short-period planets in systems with a wide stellar companion discussed above. We also compared Group 1 with Group 2 and found a p-value of 0.0008, which mean that planets in multi-planetary systems have a different distribution than single planets. We can see that planets in multi-planetary systems have lower eccentricities, and we observe only a few planets with an eccentricity larger than 0.5. Comparing Group 2 with Group 4, we obtained a p-value of 0.28; hence, we cannot rule out that these groups follow the same distribution.

As the planets in systems with wide BDs have periods larger than 50 days, we took only planets from this region to create KDEs of the distributions of planet eccentricity (Fig. 21). We obtained the p-value of 0.0007 comparing this population to the Group 1 (black line in Fig. 21), 0.00002 comparing to the Group 2 (grey line), 0.002 comparing to the Group 3 (blue line) and 0.0001 comparing to the Group 4 (green line). It means that these planets, with a high confidence level, follow their own distribution with a maximum at ~0.65. All of these planets in Fig. 19 have periods larger than 40 days and eccentricities larger than 0.4. One planet that does not meet these criteria is GJ 229 b. We reported in Appendix C the RV signal in GJ 229 as a planetary candidate rather than a confirmed planet. So far, systems with wide BD companions do not follow the trend of the decreasing number of systems towards higher eccentricities observed for the other groups. It can suggest that wide BDs significantly affect planetary systems or that the formation mechanisms differ.

thumbnail Fig. 14

STELLA RVs (blue), CARMENES VIS RVs (green), and CARMENES near-infrared RVs (red) oſ HD 118865 together with the inferred RV model of the ~590-day signal (solid black line). The nominal error bars are blue, red, and green. Bottom panel: residuals of the RV model.
thumbnail Fig. 15

GLS periodograms of STELLA RVs (blue) and the He activity indicator (red) of HD 118865: (a) STELLA RVs, (b) STELLA He activity indicator. Horizontal dashed lines show the theoretical FAP levels of 10%, 1% and 0.1% for each panel.
thumbnail Fig. 16

Planetary minimum mass versus orbital period for the known single planet-host stars (black and grey points), planet-host stars with one planet and one stellar companion (blue points), planet-host stars with one stellar companion but more than one planet (green points), and finally, planet-host stars with wide BD companion (red points).
thumbnail Fig. 17

KDEs of planetary orbital period comparing planets around single stars (black), planets around stars with a stellar companion (blue), and planets around stars with a BD companion (red).
thumbnail Fig. 18

KDEs of minimum planetary mass comparing planets around single stars (black), planets around stars with a stellar companion (blue), and planets around stars with a BD companion (red).

7.2 Frequency of planets in our sample

We estimate individual detection limits before drawing any conclusions about the fraction of planets orbiting stars with wide BD companions. First, we used RV observations to measure the RMS scatter caused by stellar activity/error bars of observations for each star. Before the procedure, we subtracted signals observed in periodograms, which we linked to the activity to reduce the RMS scatter as much as possible (see Sect. 6). Specifically, we subtracted the best fit sinusoidal function with the given period. Each star shows a different level of activity, mainly due to age differences, from the less active star HD 3651 with RMS of 6 m s−1 consistent with error bars of SONG data, GJ 504 with RMS of 19 m s−1, up to HD 118865 with RMS of 63.5 m s−1 from STELLA observations. Second, we simulated the data with the same cadence and baseline as our observations and added Gaussian noise with a sigma equal to the RMS scatter. These data simulate our observations taking into account their error bars and the activity level of each star. Then, we inserted a sinusoidal signal into these data (higher eccentricity with sufficient phase coverage would further improve our detection limits). On such prepared datasets, we used the Exo-Striker to perform the Keplerian fit of the inserted signal and ran an MCMC analysis with 20 walkers, 1,000 burning phase steps, and 10 000 MCMC phase steps to compute the 3cr error bars for the semi-amplitude of this signal, hence the 3cr detection limits. We note that such detection limits would drop for specific periods based on the cadence or gaps in individual datasets; however, the cadences and timescales of our observations would enable us to detect most of the signals from several days up to several hundreds of days, so it is a reasonable simplification. Finally, we transformed the semi-amplitudes into minimum masses for all periods, as shown in Fig. 22. HD 3651 is the less active star, so the detection limit derived for the star is equal to the instrumental limit of the SONG spectrograph for a given number of observations. We see that the activity in other systems significantly affects our detection limits. The HD 118865 system observed with STELLA has lower RV precision than the targets observed with SONG. Based on our detection limits, we can often exclude more massive planets than Neptune for orbital periods of a few days and Saturn for orbital periods longer than hundreds of days, respectively. For quiet stars, we would be able to detect all planets from the literature.

Before driving any conclusion about the frequency of planets orbiting stars with wide BD companions, we need to decide whether to include the HD 3651 system in the statistical analysis. Our decision will greatly impact the results as it is the only system with a confirmed planet. One can argue that we should exclude HD 3651b because this planet was known prior to our project. However, our target selection process was based on the starting criteria that this system fulfils; hence, we would include it regardless of the presence of a known planet. However, the discovery of the wide BD companion (Mugrauer et al. 2006) was actually triggered by the known planet companion as authors studied the multiplicity of exoplanet-host stars. It is making it no longer independent from the presence of the planet in the system. However, Luhman et al. (2007) later independently presented the discovery of the wide BD companion observing a large number of stars in the solar neighbourhood with the Spitzer Space Telescope. It suggests that the wide BD companion would probably be discovered regardless of the presence of a known planet; hence we decided to include HD 3651 in our statistical analysis. In any case, we provide the frequency of planets also for the case we do not include HD 3651.

Based on our sample of six systems, the frequency of planets orbiting stars with wide BD companions is between 17 ± 23% (without the planetary candidate in the HD 46588 system included) and 33 ± 37%6 (with the planetary candidate included). If we do not include HD 3651b, then the frequency of planets orbiting stars with wide BD companions is between 0 and 20 ± 29%. The study by Bonavita & Desidera (2020) compares the frequency of giant planets around binaries and single stars, including different observable biases. The study did not reveal statistically significant difference with 5.1 ± 1.57% occurrence rate for binaries and 6.3 ± 1.36 % occurrence rate for single stars. Given the small sample of studied systems, comparing the frequency of planets orbiting stars with wide BD companions to these frequencies has no informative value.

thumbnail Fig. 19

Eccentricity versus orbital period for the known single planet-host stars (black and grey points), planet-host stars with one planet and one stellar companion (blue points), planet-host stars with one stellar companion but more than one planet (green points), and finally, planet-host stars with wide BD companion (red points).
thumbnail Fig. 20

KDEs of eccentricity comparing planets around single stars (black and grey) and planets around stars with a stellar companion (blue and green).
thumbnail Fig. 21

KDEs of eccentricity comparing planets with periods larger than 50 days around single stars (black and grey), planets around stars with a stellar companion (blue and green), and planets around stars with a BD companion (red).
thumbnail Fig. 22

Detection limits for stars in our sample. Cyan stars are confirmed planets in systems with a wide BD companion, and a circle represents a planetary candidate. Planets from the Solar System are also plotted.

8 Summary

We have characterised a sample of five systems with a wide BD companion and searched for exoplanets using the RV technique. One additional system with a known exoplanet, HD 3651, was used as a benchmark to test our detection capabilities; we recovered its orbital solution and improved the precision of its planet parameters.

We used spectroscopic observations and available photometry to derive a complete list of physical parameters for the systems in our sample. We focused on deriving the age of the systems, using complementary age techniques. We find our sample to be relatively young. We used ages to improve the physical parameters of the wide companions using several substellar evolutionary models.

In our sample of five stars, only one planetary candidate was identified in the HD 46588 system, with the other signals attributed to stellar activity. Our lower sensitivity limit is for Neptune-mass planets at short periods of a few days and Saturn-mass planets at longer periods of hundreds of days. For less active systems such as HD 3651, we are sensitive to Neptune-mass planets at all periods up to 300 days, while for HD 118865, we are sensitive only to Jupiter-mass planets at all periods. With one planetary candidate and one confirmed planet in six observed systems, we derive the frequency of planets orbiting stars with wide BD companions to be below 70%, with the uncertainties included.

We have summarised the properties of known planets orbiting five stars with wide BD companions. We considered planets in these systems together with the full sample of planet-host stars with and without wide stellar companions to identify potential peculiarities in their parameter distributions. We detected the enhancement of planets with short periods below six days in systems with wide companions. We interpret this as a consequence of enhanced migration inwards towards the host star. We also observe a break at the eccentricity of 0.5, with a small number of planets with higher eccentricities in multi-planetary systems. Finally, planets in systems with wide BD companions follow their own eccentricity distribution, with a maximum at ~0.65, and have periods longer than 40 days, masses higher than 0.1 MJ, and eccentricities greater than 0.4.

Acknowledgements

J.S. and P.K. would like to acknowledge support from MSMT grant LTT-20015. J.S. and P.K. acknowledge a travel budget from ERAS MUS + grant 2020-1-CZ01-KA203-078200. J.S. would like to acknowledge support from the Grant Agency of Charles University: GAUK No. 314421. N.L. was financially supported by the Ministerio de Economia y Competitividad and the Fondo Europeo de Desarrollo Regional (FEDER) under AYA2015-69350-C3-2-P. We thank warmly Matthias Zechmeister for running the SERVAL pipeline and sending us the CARMENES radial velocities. Tʼnis research has made use of the Simbad and Vizier databases, operated at the centre de Données Astronomiques de Strasbourg (CDS), and of NASA’s Astrophysics Data System Bibliographic Services (ADS). This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. We acknowledge the use of public JESS data from pipelines at the TESS Science Office and at the TESS Science Processing Operations Center. 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. Tʼnis paper includes data collected with the TESS mission, obtained from the MAST data archive at the Space Telescope Science Institute (STScI). Funding for the TESS mission is provided by the NASA Explorer Program. STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. This publication makes use of VOSA, developed under the Spanish Virtual Observatory project supported by the Spanish MINECO through grant AyA2017-84089. VOSA has been partially updated by using funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n° 776403 (EXOPLANETS-A). The SONG data were obtained over several semesters through programme numbers P02-10, P03-08, P04-02, and P05-02 (PI Lodieu). The Danish SONG telescope in Tenerife, the Hertzsprung SONG telescope, is owned and operated by Aarhus University and the University of Copenhagen in collaboration with the Astrophysics Institute of the Canary Islands (IAC). It is financed by the Villum Kann Ras-mussen Foundation, Carlsberg Foundation, the Danish Council for Independent Research, Natural Sciences (FNU), European Research Council, Danish National Research Foundation, Aarhus University, University of Copenhagen and Instituto de Astrofísica de Canarias. Based on observations collected at the Centra Astronómico Hispano-Alemán (CAHA) at Calar Alto, operated jointly by Junta de Andalucía and Consejo Superior de Investigaciones Científicas (IAA-CSIC). The CARMENES dataset was obtained as part of programme number F19-3.5-011 (PI Lodieu). CARMENES is an instrument for the Centra Astronómico Hispano-Alemán de Calar Alto (CAHA, Almeria, Spain). CARMENES is funded by the German Max-Planck-Gesellschaft (MPG), the Spanish Consejo Superior de Investigaciones Científicas (CSIC), the European Union through FEDER/ERF FICTS-2011-02 funds, and the members of the CARMENES Consortium (Max-Planck-Institut für Astronomie, Institute de Astrofísica de Andalucía, Landessternwarte Königstuhl, Institut de Ciencies de l’Espai, Insitut für Astrophysik Göttingen, Universidad Complutense de Madrid, Thüringer Landessternwarte Tautenburg, Institute de Astrofísica de Canarias, Hamburger Sternwarte, Centra de Astrobiología and Centra Astronómico Hispano-Alemán), with additional contri-butions by the Spanish Mnistry of Economy, the German Science Foundation through the Major Research Instrumentation Programme and DFG Research Unit FOR2544 “Blue Planets around Red Stars”, the Klaus Tschira Stiftung, the states of Baden-Württemberg and Niedersachsen, and by the Junta de Andalucía. Based on observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica) at the Spanish Observatorio del Roque de los Muchachos of the Institute de Astrofisica de Canarias. Part of the HARPS-N data used in this work have been downloaded from the TNG archive. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programmes 072.C-0488, 183.C-0972, 085.C-0019, 087.C-0831, 183.C-0972, 089.C-0732, 090.C-0421, 091.C-0034, 093.C-0409, 095.C-0551, 096.C-0460, 196.C-1006, 098.C-0366, 099.C-0458, 0100.C-0097, 0101.C-0379, 0102.C-0558, 0103.C-0432.

Appendix A Stellar and brown dwarf parameters

Appendix A.1 Stellar parameters with iSpec

We used the iSpec framework (Blanco-Cuaresma et al. 2014; Blanco-Cuaresma 2019) to derive the parameters of the host stars. We used the Spectroscopy Made Easy radiative transfer code (SME; Valenti & Piskunov 1996; Piskunov & Valenti 2017) incorporated into the iSpec framework, and complementary to it, we use the MARCS atmosphere models (Gustafsson et al. 2008), and version 5 of the GES atomic line list (Heiter et al. 2015). The spectral fitting technique minimises the χ2 value between the calculated synthetic spectrum and the observed spectrum.

We used SERVAL to co-add all CARMENES spectra to the very high signal-to-noise final spectrum. We then used these final spectra for each system from our sample to determine the effective temperature, Teff, metallicity, [Fe/H], surface gravity, logy, the projected stellar equatorial velocity, υ sin i, and the lithium EW, eqwLi, of the Li I line at 670.8 nm following the same procedure as in Fridlund et al. (2017). In our analysis, we computed values for the micro-turbulence and macro-turbulence velocities (Vmic, Vmac) from empirical relations incorporated into the iSpec framework. To determine Teff, we fit the wings of Hα Banner line (Cayrel et al. 2011). We then used this temperature to fit the line wings of the Ca I triplet (610.27 nm) to derive a value of log g. We also used a large sample of clean and unblended Fe I lines in the interval from 597 nm to 643 nm to derive [Fe/H] and υ sin i. We report the stellar parameters for the stars of our sample in Table 5.

To estimate stellar mass and radius, we used the Bayesian parameter estimation code PARAM 1. 57 (da Silva et al. 2006; Rodrigues et al. 2014, 2017) based on the PARSEC isochrones. As input parameters, we set Gaia eDR3 parallaxes, Gaia DR2 magnitudes, luminosities from V0SA, and Teff with [Fe/H] derived from i Spec. We report all derived parameters in Table 5.

Appendix A.2 SED analysis with VOSA

As an independent check, we used VOSA8 (Bayo et al. 2008) to determine stellar parameters. To model the SED of the stars in our sample, we used grids of five different models: BT-Settl-AGSS2009 (Barber et al. 2006; Asplund et al. 2009; Allard et al. 2012), BT-Settl-CIFIST (Barber et al. 2006; Caffau et al. 2011; Allard et al. 2012), BT-NextGen GNS93 (Grevesse et al. 1993; Barber et al. 2006; Allard et al. 2012), BT-NextGen AGSS2009 (Barber et al. 2006; Asplund et al. 2009; Allard et al. 2012), and the Coelho Synthetic stellar library (Coelho 2014) and performed the χ2 minimisation procedure to compare theoretical models with the observed photometry. We used the available photometric measurements; specifically, the Strömgren-Crawford uvbyβ (Paunzen 2015), Tycho (Høg et al. 2000), Gaia DR2 (Gaia Collaboration 2018b), Gaia eDR3 (Gaia Collaboration 2021), 2MASS (Cutri et al. 2003), AKARI (Ishihara et al. 2010), and WISE (Cutri et al. 2021) photometry. We set priors for the Teff = 4000–7000 K, log(g) = 4.0–5.0 dex, and [Fe/H] = −0.5–0.5 based on results from iSpec. For each model, we take only results with the lowest χ2, and use them to create the final intervals of derived parameters. We report the final intervals in Table 5. In Table 5, we also compare the stellar radii computed from stellar isochrones with ones from VOSA determined via the Stefan–Boltzmann law.

Appendix A.3 Revised parameters of the wide BD companions

We used SPLAT (Burgasser & Splat Development Team 2017) to derive the parameters of the wide BD companions in our sample. SPLAT is a python-based package designed to interface with the SPL (Burgasser 2014), which is an online repository of over 2000 low-resolution, near-infrared spectra of stars and BDs. The package enables a conversion between the observable (temperature, luminosity, surface gravity) and physical parameters (mass, radius, age) of BDs using published evolutionary model grids. First, we input the age of the stars in our sample as derived in Sect. 5.3. We used the BD luminosities published in the literature and compiled them in Table 7. The SPLAT output parameters include mass, temperature, surface gravity, and radius. We considered different BD evolutionary models from Burrows et al. (2001); Baraffe et al. (2003); Saumon & Marley (2008) incorporated in the package. The models of Burrows et al. (2001) and Baraffe et al. (2003) models are only for the solar metallicity, while models of Saumon & Marley (2008) incorporate the solar metallicity and −0.3, +0.3 dex. As several stars in our sample have metallicities of ~0.2 dex, we provide two solutions for them: solar metallicity and +0.3 dex based on the Saumon & Marley (2008) models. We do not consider the metallicity of −0.3 dex because none of our targets has metallicity below solar (the ones with slightly negative values are still consistent with solar in terms of error bars). The results are summarised in Table 7. The minimum and maximum values for each parameter (temperature, gravity, mass, radius) take into account the full interval of errors in age and luminosities as well as the discrepancies between models The ranges of the physical parameters of the BDs quoted in Table 7; hence, our conclusions do not strongly depend on the models. According to the derived mass intervals, all companions are BDs, except GJ 504B, whose mass estimates place it in the planetary mass rather than the substellar regime. Bonnefoy et al. (2018) discussed that two possible age scenarios (21 ± 2 Myr and 4.0 ± 1.8 Gyr) make that companion either a BD or a planet. Our analysis favours the young case over the older option and, hence, the lowest mass.

Appendix B Age analysis

Appendix B.1 Stellar isochrones

We used the PARAM 1. 5 code (da Silva et al. 2006; Rodrigues et al. 2014, 2017) code to infer stellar ages. It is based on the PARSEC and MIST stellar evolution tracks (Bressan et al. 2012; Choi et al. 2016). PARAM 1. 5 derives stellar parameters by comparing a variety of observational inputs, such as photometric colours, spectroscopic properties or asteroseismic parameters, to interpolated model values. We use the PARSEC isochrones, and as inputs for modelling, we use Gaia eDR3 parallax, the Gaia DR2 colours, luminosities derived from VOSA modelling, together with Teff, log g, and [Fe/H] derived from iSpec modelling from Table 5. Results are listed in Table 6.

Appendix B.2 Gyrochronology

As described in Angus et al. (2019), the gyrochronology relation used in the stardate code is derived based on the Praesepe cluster fitting a broken power law to observed rotation periods of stars from this cluster in the form logProt=calog(t)+∑n=04cn[ log(GBp−GRp) ]n,$ log{P_{rot}} = {c_a}log\left( t \right) + \sum\limits_{n = 0}^4 {{c_n}{{\left[ {log\left( {{G_{Bp}} - {G_{Rp}}} \right)} \right]}^n},} $(B.1)

where t defines the age of a cluster. To study the ages of the stars in our sample, we used this empirical relation, with coefficients derived on the Praesepe cluster, to compute curves for ages 100, 400, 650, and 2500 Myr and plot them together with the members of the well-defined clusters studied in Godoy-Rivera et al. (2021): Pleiades cluster (~120 Myr), M37 cluster (~400 Myr), Praesepe cluster (~650 Myr), NGC 6811 cluster (~1 Gyr), together with the Ruprecht 147 + NGC 6819 clusters studied in Curtis et al. (2020). We calculated reddening E(B–V) for each star in the clusters using the dustmaps code (Green 2018) and three-dimensional Bayestar dust maps (Green et al. 2019). We then followed the approach from Gaia Collaboration (2018a) to compute reddening in the Gaia colours. In Fig. B.1, we over-plot our sample highlighted with cyan star symbols, specifically, rotation periods derived from TESS LCs in Sect. 5.2, and Gaia eDR3 GBp, GRp magnitudes. Using empirical relations together with cluster members, we are able to make assumptions for the ages of our systems.

thumbnail Fig. B.1

Colour-period diagram of the stars from our sample (magenta stars) together with members of well-studied clusters: Pleiades cluster, M37 cluster, Praesepe cluster, NGC 6811 cluster, Ruprecht 147 cluster and NGC 6819 cluster. Lines represent the 100, 400, 650, and 2500 Myr curves compute from the empirical relation from Angus et al. (2019).

We conclude that HD 3651 is older than Ruprecht 147. HD 46588 looks to have an age between NGC 6811 and Ruprecht 147. HD 118865 has an age between Praesepe and NGC6811. HN Peg, and HD 203030 are probably younger than Praesepe and have ages consistent with M37. Finally, GJ 504, has an age between Pleiades and M37. It looks like the youngest system in our sample; however, we cannot exclude the older scenario previously discussed.

Appendix B.3 Lithium EW

We used the lithium line at 6708 Å to measure the EW with iSpec. We fitted the line with a Gaussian profile, and the EW corresponds to the area within the gaussian fit. Similarly, as with the rotation period, we compare the EW of Li versus colour to members of well-studied clusters. We use the Tuc-Hor young moving group (~45 Myr; Mentuch et al. 2008), the Pleiades (~120 Myr; Soderblom et al. 1993b), M34 (~220 Myr; Jones et al. 1997), Ursa Major Group (~400 Myr; Soderblom et al. 1993c), Praesepe (~650 Myr; Soderblom et al. 1993a), Hyades (~650 Myr; Soderblom et al. 1990), and M67 clusters (~4 Gyr; Jones et al. 1999). If needed, we de-reddened clusters using E(B-V) values from Gaia Collaboration (2018a). According to Li EW, two of our systems look younger than the rest. They are HN Peg, and GJ 504, with ages between the M34 and Praesepe. HD 46588 and HD 118865 are consistent with Praesepe or older. HD 203030 is consistent with Praesepe. Finally, in HD 3651, we plot the upper limit as we did not detect any lithium, setting a minimum age of 220 Myr (age of M34).

thumbnail Fig. B.2

Colour versus EW of lithium line Li 6708 Å of the stars from our sample (gold stars) together with members of well-studied clusters: Tuc-Hor young moving group (~45 Myr; Mentuch et al. 2008), the Pleiades (~120 Myr; Soderblom et al. 1993b), M34 (~220 Myr; Jones et al. 1997), Ursa Major Group (~400 Myr; Soderblom et al. 1993c), Praesepe (~650 Myr; Soderblom et al. 1993a), Hyades (~650 Myr; Soderblom et al. 1990), and M67 clusters (~4 Gyr; Jones et al. 1999).

Appendix B.4 X-ray luminosity

We used clusters listed in Jackson et al. (2012) and ROSAT observations9 (Voges et al. 1999) of our systems to compare the X-ray luminosity of our sample with clusters of known ages. We found ROSAT data available for all systems except for HD 118865, which is missing in this analysis. The X-ray luminosities are listed in Table 5. The final plot can be found in Fig. B.3. According to this plot, systems HD 3651 and HD 46588 are older than the Praesepe and Hyades. HD 203030 seems to have an age similar to the Praesepe and Hyades. HN Peg can have any age between the Pleiades and Praesepe included, while GJ 504 is probably younger than the Praesepe.

thumbnail Fig. B.3

X-ray luminosity versus colour of the stars from our sample (gold stars) together with members of well-defined clusters from Jackson et al. (2012).

Appendix B.5 Membership to young associations

We used the BANYAN code (Gagné et al. 2018) to derive membership probabilities for our sample of stars. BANYAN includes 27 young associations with ages between 1–800 Myr. As an independent check, we also used the LocAting Constituent mEmbers In Nearby Groups code (LACEwING; Riedel et al. 2017). LACEwING includes 13 young moving groups (YMGs) and three open clusters within 100 pc. All YMGs are in common with Gagné et al. (2018). The Gaia eDR3 astrometric data, which can be found in Table 1, were used as input parameters. BANYAN code does not confirm membership to any association and derives that all stars in our sample are field stars. The LACEwING code found a 23% probability for HD 203030 and a 10% probability for HN Peg of being a member of the Argus association (~50 Myr; Zuckerman 2019). Given the age indicators from previous subsections, we consider these stars to be older than the Argus association and hence unlikely members of this YMG The results for the rest of the stars are in agreement with the BANYAN code, and they appear to be field stars belonging to the Thin disk (Leggett 1992; Bensby et al. 2003). Gaidos (1998) discovered that HN Peg is a member of the Her–Lyr moving group, which is not included in BANYAN and LACEwING.

In Fig. B.4, we plot the 1-sigma position of young stellar associations in space velocities U, V, W taken from Gagné et al. (2018) together with our sample of stars. To determine U, V, W velocities for our systems used in this figure, we used the python package PyAstronomy, specifically the gal_uvw10 function.

thumbnail Fig. B.4

Membership to young associations. Ellipses represent the 1-sigma position of young stellar associations in space velocities U, V, and W taken from Gagné et al. (2018). Our sample of stars is plotted as magenta stars.

Appendix C The family of planet-host stars with BD companions

Besides HD 3651, eight systems with exoplanet-host stars and wide BD companions are known: HIP 70849, HD 89744, HD 168443, GJ229, HD 4113, HD 65216, HD 41004, and ϵ Indi. We looked at original discoveries papers, and in this section, we summarised the parameters derived by other authors. For HIP 70849, we have revised stellar parameters and updated orbital parameters as we found a large number of available HARPS spectra not previously reported, which significantly improved the parameters of the system.

Appendix C.1 HIP 70849

We processed all 54 HARPS archival spectra observed between April 2006 and August 2019 with SERVAL (Zechmeister et al. 2018) to derive stellar parameters, refine the orbital solution of the planet, and discuss the star’s activity level. We co-added all HARPS spectra to produce a very high signal-to-noise final spectrum input in the iSpec/PARAM 1.5 tools to determine a stellar mass of 0.53±0.04 M⊙, a radius of R⋆ =0.47±0.04 R⊙, an effective temperature of Teff = 4112±72 K, and a metallicity of −0.31±0.08 dex. Ségransan et al. (2011) reported an age of 3±2 Gyr, while we derived an age of 0.6–3.0 Gyr (Sect. 5.3). A T4.5 dwarf companion orbits the star at the separation of 6.3arcmins (~ 9000 au; Lodieu et al. 2014). Ségransan et al. (2011) reported an additional long-period companion with a period between 5 and 75 yr, a minimum mass of msini between 3.5–15 MJ, and an eccentricity of 0.4–0.98 using data from the HARPS Echelle spectrograph. The large uncertainties of the derived parameters are due to the (1) small number of RV measurements with only one observation close to the periastron and (2) large eccentricity, causing the period to be insufficiently covered. Hence, we downloaded the 18 archival HARPS spectra used in Ségransan et al. (2011) as well as the additional spectra obtained since then, not yet reported in the literature.

With this enhanced dataset, we observe an RVs signal at 3648±12 days in the periodogram. To confirm the planetary nature of this signal, we used SERVAL to derive various activity indicators. We cannot see any counterpart at this period in any periodogram of activity indicators supporting the planetary origin of the signal. We used Exo-Striker to fit the orbital solution with the revised stellar parameters. We set 14 walkers and ran 1,000 burning phase steps and 10,000 MCMC phase steps. Two more observations were obtained close to the periastron, significantly improving the orbital solution given HARPS precision and low RMS scatter. We summarise the updated planetary parameters in Table C.1. The orbital solution is plotted in Fig. C.1 and the plot of correlations between parameters together with the derived posterior probability distributions from MCMC is in Fig. D.4 in Appendix. We do not detect additional signals in RVs.

Table C.1

HIP 70849b: Updated parameters

thumbnail Fig. C.1

Orbital solution for HIP 70849 showing the HARPS RVs (blue points) and the RV model in black.

Appendix C.2 HD 89744

HD 89744 is an F7V star with a mass of M⋆ = 1.56±0.05 M⊙, radius of R⋆ = 2.14±0.20 R⊙, and age of 1.9 ± 0.2 Gyr (Takeda et al. 2007). The star has an effective temperature of Teff = 6300±30K, and a metallicity of 0.24±0.03 dex (Tsantaki et al. 2014). Wilson et al. (2001) reported a wide massive BD candidate of spectral type L0V based on spectroscopic observations. Mugrauer et al. (2004) then confirmed this companion at a separation of 63 arcsec (~2500 au) with the mass between 0.072–0.081 M⊙, and temperature of ~2200K at the stellar/substellar boundary. Korzennik et al. (2000) earlier reported a massive planet using the Advanced Fiber-Optic Echelle spectrograph at the Whipple Observatory. The solution was later revised by Wittenmyer et al. (2019) using four different instruments to msini = 8.4±0.2 MJ with the period of P = 256.78±0.02 days and eccentricity of e = 0.677±0.003. The discovery paper and later papers about this system agree that the semi-amplitude of 270m/s is too large to be solely associated with the stellar activity of a late-F star.

Appendix C.3 HD 168443

HD 168443 is an G6V star with a mass of M⋆ = 1.00±0.02 M⊙, radius of R⋆ = 1.52±0.07 R⊙, and age of 11.1 ± 0.7 Gyr (Takeda et al. 2007). The star has an effective temperature of Teff = 5530±97 K, and a metallicity of 0.08±0.06 dex (Rosenthal et al. 2021). Marcy et al. (2001) reported two companions observed in 4.4 yr long period of the Keck/HIRES observations. The wide BD companion has msini = 18.0±1.8 MJ, the period of P= 1753.1±0.8 days and eccentricity of e = 0.210±0.003. The giant planet has msini = 7.6±0.6 MJ, the period of P = 58.1119±0.0002 days and eccentricity of e = 0.530±0.002.

Appendix C.4 GJ 229

GJ 229 is an M1.5V dwarf with a mass of M⋆ = 0.58 M⊙, a radius of = 0.46 R⊙, and a temperature of Teff = 3564K (Tuomi et al. 2014). The star hosts a BD companion detected through direct imaging (Nakajima et al. 1995). In a new analysis of the system, Brandt et al. (2020) derived a mass of 70±5 MJ for the BD with a semi-major axis of 34.7±1.9 au, and eccentricity of 0.846±0.015 combining Keck/HIRES RVs, Hipparcos and Gaia DR2 astrometry, and HiCIAO–Subaru and the Hubble Space Telescope imaging.

Tuomi et al. (2014) reported a two-sigma detection of a possible additional planet with msini = 0.1 MJ, a period of 471 days, and an eccentricity of 0.1 using the HARPS and UV-Visual Echelle Spectrograph (LIVES) observations. However, Brandt et al. (2020) did not find evidence for this planet in 47 Keck/HIRES RVs. Feng et al. (2020) discuss the system using all data available: 47 Keck/HIRES, 74 UVES, and 200 HARPS RVs. They report two planets in the system, one with mass msini = 0.023 MJ, the period of P = 122 days and eccentricity of e = 0.19 and the second with msini = 0.027 MJ, P = 526 days and e = 0.10. They also provide different activity indicators for each instrument besides UVES (see Fig. 10 in Feng et al. (2020)).

We have visually investigated the plots and results of the work by Feng et al. (2020). The periodograms of HARPS activity indicators with the largest number of observations reveal significant signals close to the 526-day peak reported as a planet. The authors also reported activity signal at ~278 days, which can be just the first harmonic. Hence, we argue that the 526-day peak seen in RVs might be associated with stellar activity. The signal with a period of 122 days has a better chance of being the planet; however, it can also be the higher-order harmonics. For example, this peak is visible in the HARPS RHK activity indicator. Furthermore, the semi-amplitudes of both signals are below 2m/s, smaller than the RMS scatter of both datasets. Because of our scepticism regarding the planetary nature of these signals, we decided not to include them in our analyses.

Appendix C.5 HD 4113

HD 4113 is an G5V star with a mass of M⋆ = 1.05±0.10 M⊙, a radius of R⋆ = 1.09±0.09 R⊙, a temperature of Teff = 5646±70 K, and a metallicity of 0.19±0.05 dex (Ghezzi et al. 2010). Tamuz et al. (2008) reported a massive planet in the system with msini= 1.56±0.04 MJ, a period of P = 526.6±0.3 days, and an eccentricity of e = 0.903±0.005 using the CORALIE spectrograph. These authors also observed a long trend in RVs, predicting a possible second companion with a minimum mass of 10 MJ and minimum semi-major axis of 8 au. Mugrauer et al. (2004) later reported a wide M-dwarf companion at a separation of 49 arcsec (~2000 au) with the mass of 0.56 M⊙, too far away to explain the long trend in RVs. Cheetham et al. (2018) finally detected a third companion responsible for this trend, using CORAL IE and KECK/HIRES RVs, and high-contrast imaging with the Spectro-Polarimetric High-contrast Exoplanet REsearch instrument (SPHERE): it is a BD with a mass of 66±5 MJ, period of 105±29 yr, and an eccentricity of 0.38±0.08.

Appendix C.6 HD 65216, HD 41004, and ϵ Indi

All three systems have different architectures from the previous ones. HD 65216 is a G5V star with a mass of M⋆ = 0.88 ± 0.04 M⊙, a radius of R⋆ = 0.88 ± 0.01 R⊙, an effective temperature of Teff = 5645±20 K, and a metallicity of −0.16±0.02 dex (Stassun et al. 2017). The star forms a hierarchical triple system with the binary companion at a separation of 253 au. The two wide components, HD65216BC, are separated by 6 au and consist of an M2−M3+L2−L3 pair (Mugrauer et al. 2007). The star also hosts a planet with a period of 613 days and an eccentricity of 0.41 (Mayor et al. 2004) using 52 spectra obtained with CORAL IE spectrograph. Another 24 HARPS spectra were added to the analysis by Wittenmyer et al. (2019) to report a second potential companion with a period of 5370 days and eccentricity 0.17, which would refine the orbital parameters of the inner planet to P = 578 days and e = 0.27.

HD 41004 A is a K1V star with a mass of M⋆ = 0.95±0.10 M⊙, a radius of R⋆ =0.85±0.07 R⊙, an effective temperature of Teff = 5310±65 K, and a metallicity of 0.23±0.04 dex (Ghezzi et al. 2010). This star hosts an exoplanet and is the primary of a system with a wide companion hosting a BD. Zucker et al. (2004) analysed 149 CORAL IE spectra to derive the parameters of the system by separating the RVs of the two stellar components. The primary star host an exoplanet with msini = 2.5±0.7 MJ, a period of 963±38 days, and an eccentricity of 0.74±0.20. The secondary, HD 41004 B (M2), is separated by 0.5 arcsec (~21 au) from HD 41004 A has a mass of 0.4 M⊙, and host the BD companion with msini = 18.37±0.22 MJ, a period of 1.328300±0.000012 days, and eccentricity of 0.081±0.012 (Zucker et al. 2004).

ϵ Indi is a nearby triple system with a K5V spectral type primary exoplanet-host star and wide BD binary at a separation of 402.3 arcsec, whose components have a projected separation of 0.7 arcsec (Scholz et al. 2003; McCaughrean et al. 2004). The primary star has a mass of M⋆= 0.73±0.09 M⊙, a radius of R⋆ =0.74±0.07 R⊙, an effective temperature of Teff = 4611 ± 157 K, and a metallicity of −0.13±0.03 dex (Stassun et al. 2019). Dieterich et al. (2018) determined dynamical masses of the BD binary, which consists of T1.5 dwarf with a mass of 75.0±0.8 MJ and a T6 secondary with a mass of 70.1±0.7 MJ. Both objects have masses very close to the transition between low-mass stars and BDs. Endl et al. (2002) reported a linear trend in RVs of the primary star using the Coude Echelle Spectrometer (CES) at ESO La S ilia. Feng et al. (2019) used spectroscopic data from CES, HARPSpre, HARPSpost, and UVES together with astrometric data from Hipparcos and Gaia to derive the parameters of the planet to MP = 3.25 MJ with a period of 45.2 yr and e = 0.26.

Appendix D Additional material

thumbnail Fig. D.1

Hα and RV time series of HD 46588. The top plot shows the inferred stellar model (black). The bottom panel shows the inferred stellar model (blue), planetary model (red) and stellar+planetary model (black).
thumbnail Fig. D.2

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HD 3651. At the end of each row is shown the derived posterior probability distribution.
thumbnail Fig. D.3

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HD 46588. At the end of each row is shown the derived posterior probability distribution. Index b represents a stellar activity signal, and index c is a planetary candidate.
thumbnail Fig. D.4

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HIP 70849. At the end of each row is shown the derived posterior probability distribution.

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4

We need to note that such a division reflects our current information about these systems. For example, systems from Group 1 can in fact be members of Group 2 with an undetected additional companion(s).

6

The uncertainty of the frequency was estimated as σf=(Nplanets−1/2+Nstars−1/2)*(NplanetsNstars),$ {\sigma _f} = \left( {N_{{\rm{planets}}}^{ - 1/2} + N_{{\rm{stars}}}^{ - 1/2}} \right)*\left( {{{{N_{{\rm{planets}}}}} \over {{N_{{\rm{stars}}}}}}} \right), $(1)

following Bonavita & Desidera (2007).

All Tables

Table 1

System parameters for stars in our sample.

In the text
Table 2

Spectroscopic observations for our sample of stars.

In the text
Table 3

Dates of TESS observations for our sample of stars.

In the text
Table 4

Additional sources within the TESS apertures for our sample of stars.

In the text
Table 5

Physical parameters for stars in our sample.

In the text
Table 6

Age intervals for stars in our sample from different indicators together with the final adopted intervals.

In the text
Table 7

Parameters of wide companions around the stars from our sample.

In the text
Table 8

Planetary parameters.

In the text
Table C.1

HIP 70849b: Updated parameters

In the text

All Figures

thumbnail Fig. 1

Analysis of rotation periods. Left: Gaia DR2 catalogue overplotted on the TESS tpf images. Middle: LCs observed by TESS. Right: Marginalised posterior distributions of the rotation period from GP modelling. From top to bottom, we show GJ504/TIC 397587084, HD 3651/TIC 434210589, HD 46588/TIC 141523112, HD 118865/TIC 365224537, and HD 203030/TIC 25559430.
In the text
thumbnail Fig. 2

Luminosity versus effective temperature plot. Curves represent MIST isochrones for ages: 10 Myr (blue), 20 Myr (orange), 30 Myr (green), 50 Myr (red), 100 Myr (purple), 1 Gyr (pink), 3 Gyr (grey), 6Gyr (chartreuse), and 10 Gyr (celeste), and for [Fe/H] = 0.25. The brown point represents the parameters of GJ 504 with their error bars.
In the text
thumbnail Fig. 3

GLS periodograms of the SONG RVs (blue) and the Hα activity indicator (red) of HD 3651: (a) SONG RVs, (b) SONG RVs minus the 62-day model, and (c) Hα. The vertical green line represents the orbital period of the confirmed planet, and the black line the 1-yr window function. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.
In the text
thumbnail Fig. 4

Orbital solution for HD3651, with the Exo-Striker RV model shown in black. The orbital solution is derived by simultaneously fitting RVs from LICK (grey), KECK (orange), SONG (blue), visual CARMENES (green), near-infrared CARMENES (cyan), and EXPRES (red).
In the text
thumbnail Fig. 5

GLS periodograms of RVs and activity indicators of GJ 504: (a) SONG RVs, (b) SONG Hα indicator, (c) HARPS-N RVs, (d) HARPS-N RVs after fitting a sinusoid of P = 3.7 days, and (e) HARPS-N Hα indicator. Vertical green lines represent the stellar rotation period and its 1-day alias. The vertical orange line represents the most significant signal in the SONG RVs at 292.74 days. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1%.
In the text
thumbnail Fig. 6

SONG RVs of GJ504 (blue), HARPS-N RVs (green), and CARMENES RVs (orange) together with the inferred RV model of the 292.74-day signal (solid black line). The nominal error bars are in blue and red and are hardly visible for the HARPS-N dataset. Bottom panel: Residuals of the RV model.
In the text
thumbnail Fig. 7

GLS periodograms of RVs (blue) and activity indicators (red) of HN Peg: (a) SONG RVs, (b) SONG RVs after fitting a sinusoid with a period of 5.1 days, (c) SONG Hα indicator, and (d) SONG Hα indicator after fitting a sinusoid with P = 420 days. Vertical green and orange lines represent the star’s rotation period and the first harmonic of the rotation with their 1-day alias, respectively. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.
In the text
thumbnail Fig. 8

SONG RVs of HN Peg (blue) together with the inferred RV model of the 5.1-day signal (solid black line). The nominal error bars are in the same colours.
In the text
thumbnail Fig. 9

GLS periodograms oſ SONG RVs (blue) and activity indicators (red) and CARMENES RVs and CRX (green) of HD 46588: (a) SONG RVs, (b) SONG RVs after removing the model with the period of 127 days, (c) SONG Hα activity indicator, (d) SONG Hα indicator after fitting a sinusoid with P = 365 days, (e) SONG window function, (f) CARMENES RVs, and (g) CARMENES CRX. The vertical green line represents the short-term activity cycle, the orange line represents the possible planetary candidate, and the black line represents the 1-yr window function. Horizontal dashed lines show the theoretical FAP levels of 10%, 1%, and 0.1% for each panel.
In the text
thumbnail Fig. 10

SONG RVs of HD 46588 (blue) and CARMENES RVs (red and green) together with the inferred RV model of the 127-day and 224-day signals (solid black line). The nominal error bars are in the same colours.
In the text
thumbnail Fig. 11

Orbital solution for HD 46588 showing the RV model in black. Blue points represent the SONG RVs, and red and green points represent the CARMENES RVs. The nominal error bars are in the same colours.
In the text
thumbnail Fig. 12

GLS periodograms oſ SONG RVs (blue) and Hα activity indicator (red) of HD 203030: (a) SONG RVs, (b) SONG RVs after fitting sinusoid with P = 2.23 days, (c) SONG Hα indicator. Vertical orange lines represent the star’s rotation period and its 1-day alias, and green lines represent the planetary candidate of the rotation period with its 1-day alias. Horizontal dashed lines show the theoretical FAP levels of 10%, 1% and 0.1% for each panel.
In the text
thumbnail Fig. 13

SONG RVs of HD 203030 (blue) together with the inferred RV model of the 2.23-day signal (solid black line). The nominal error bars are in the same colours.
In the text
thumbnail Fig. 14

STELLA RVs (blue), CARMENES VIS RVs (green), and CARMENES near-infrared RVs (red) oſ HD 118865 together with the inferred RV model of the ~590-day signal (solid black line). The nominal error bars are blue, red, and green. Bottom panel: residuals of the RV model.
In the text
thumbnail Fig. 15

GLS periodograms of STELLA RVs (blue) and the He activity indicator (red) of HD 118865: (a) STELLA RVs, (b) STELLA He activity indicator. Horizontal dashed lines show the theoretical FAP levels of 10%, 1% and 0.1% for each panel.
In the text
thumbnail Fig. 16

Planetary minimum mass versus orbital period for the known single planet-host stars (black and grey points), planet-host stars with one planet and one stellar companion (blue points), planet-host stars with one stellar companion but more than one planet (green points), and finally, planet-host stars with wide BD companion (red points).
In the text
thumbnail Fig. 17

KDEs of planetary orbital period comparing planets around single stars (black), planets around stars with a stellar companion (blue), and planets around stars with a BD companion (red).
In the text
thumbnail Fig. 18

KDEs of minimum planetary mass comparing planets around single stars (black), planets around stars with a stellar companion (blue), and planets around stars with a BD companion (red).
In the text
thumbnail Fig. 19

Eccentricity versus orbital period for the known single planet-host stars (black and grey points), planet-host stars with one planet and one stellar companion (blue points), planet-host stars with one stellar companion but more than one planet (green points), and finally, planet-host stars with wide BD companion (red points).
In the text
thumbnail Fig. 20

KDEs of eccentricity comparing planets around single stars (black and grey) and planets around stars with a stellar companion (blue and green).
In the text
thumbnail Fig. 21

KDEs of eccentricity comparing planets with periods larger than 50 days around single stars (black and grey), planets around stars with a stellar companion (blue and green), and planets around stars with a BD companion (red).
In the text
thumbnail Fig. 22

Detection limits for stars in our sample. Cyan stars are confirmed planets in systems with a wide BD companion, and a circle represents a planetary candidate. Planets from the Solar System are also plotted.
In the text
thumbnail Fig. B.1

Colour-period diagram of the stars from our sample (magenta stars) together with members of well-studied clusters: Pleiades cluster, M37 cluster, Praesepe cluster, NGC 6811 cluster, Ruprecht 147 cluster and NGC 6819 cluster. Lines represent the 100, 400, 650, and 2500 Myr curves compute from the empirical relation from Angus et al. (2019).
In the text
thumbnail Fig. B.2

Colour versus EW of lithium line Li 6708 Å of the stars from our sample (gold stars) together with members of well-studied clusters: Tuc-Hor young moving group (~45 Myr; Mentuch et al. 2008), the Pleiades (~120 Myr; Soderblom et al. 1993b), M34 (~220 Myr; Jones et al. 1997), Ursa Major Group (~400 Myr; Soderblom et al. 1993c), Praesepe (~650 Myr; Soderblom et al. 1993a), Hyades (~650 Myr; Soderblom et al. 1990), and M67 clusters (~4 Gyr; Jones et al. 1999).
In the text
thumbnail Fig. B.3

X-ray luminosity versus colour of the stars from our sample (gold stars) together with members of well-defined clusters from Jackson et al. (2012).
In the text
thumbnail Fig. B.4

Membership to young associations. Ellipses represent the 1-sigma position of young stellar associations in space velocities U, V, and W taken from Gagné et al. (2018). Our sample of stars is plotted as magenta stars.
In the text
thumbnail Fig. C.1

Orbital solution for HIP 70849 showing the HARPS RVs (blue points) and the RV model in black.
In the text
thumbnail Fig. D.1

Hα and RV time series of HD 46588. The top plot shows the inferred stellar model (black). The bottom panel shows the inferred stellar model (blue), planetary model (red) and stellar+planetary model (black).
In the text
thumbnail Fig. D.2

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HD 3651. At the end of each row is shown the derived posterior probability distribution.
In the text
thumbnail Fig. D.3

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HD 46588. At the end of each row is shown the derived posterior probability distribution. Index b represents a stellar activity signal, and index c is a planetary candidate.
In the text
thumbnail Fig. D.4

Correlations between the free parameters of the RV model from the MCMC analysis using the Exo-Striker package for the HIP 70849. At the end of each row is shown the derived posterior probability distribution.
In the text

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