Host star metallicity of directly imaged wide-orbit planets: implications for planet formation

Existing planetary search methods are constrained by severe selection effects and detection biases (e.g. Cumming, 2004; Zakamska et al., 2011; Kipping & Sandford, 2016). However, multiple detection techniques sample different regions of the star-planet parameter space, thus providing useful insights about the rich diversity and underlying population of the planetary systems. While the transit and radial velocity methods have been successful in unraveling planet population spanning extremely close-in ($\sim$0.1 AU) to moderate orbits ($\sim$10 AU), the direct imaging is most useful for probing the planetary architecture in the outermost regions (10s-1000s AU) of stars (Winn & Fabrycky, 2015; Bowler, 2016; Baron et al., 2019). The planet population discovered by the transit technique and radial velocity largely belongs to main-sequence and post-main sequence stars. In contrast, the direct imaging method has been most effective in uncovering newly formed warm and massive planets in wider orbits around nearby young stars in the solar neighborhood (e.g. Lagrange, 2014; Bowler, 2016; Meshkat et al., 2017; Baron et al., 2019).

Following the success of the Kepler space mission, a wealth of new information has emerged about the planet population associated with main-sequence and evolved stars (Borucki et al., 2011; Howard et al., 2012; Mulders et al., 2016; Batalha, 2014; Johnson et al., 2017; Petigura et al., 2017; Narang et al., 2018; Fulton & Petigura, 2018; Petigura et al., 2018). The growing number of exoplanets from space discoveries and their follow-up studies from the ground is making planetary statistics more robust and significant. Because of their large number, the statistical properties of close-in planets ($\lesssim$ 1 AU) and their host stars are relatively better studied. A great deal of research effort has been devoted to understanding the diversity of planets and the characteristics of their primary hosts. Many useful insights have been gained by studying the interdependence of planetary properties and stellar parameters (Gonzalez, 1997; Santos et al., 2000, 2004; Fischer & Valenti, 2005; Udry & Santos, 2007a; Johnson et al., 2010; Ghezzi et al., 2010; Mulders et al., 2016; Mulders, 2018; Narang et al., 2018; Adibekyan, 2019). Stellar metallicity and planet occurrence rate, for example, is one such important correlation for testing the veracity of various planet formation mechanisms under different conditions (e.g. Udry & Santos, 2007a; Mulders, 2018; Santos et al., 2017; Narang et al., 2018). However, these results have been demonstrated only for stars with close-in ($\lesssim$ 1 AU) planets that have been detected primarily by radial velocity and transit methods.

Directly imaged planets (DIP) are located at relatively large orbital distances from their host stars ($2.6-3500$ AU), which provides a unique window to probe an entirely different planetary population. While there is a general consensus that giant planets are common around high-metallicity stars compared to the low-metallicity counterparts, a clear picture is still lacking about the role of metallicity and the exact mechanism of giant planet formation at larger distances.

The majority of the 51 planetary companions discovered so far by direct imaging technique are massive planets at larger orbital distances from the host stars. Figure 1(a) shows the confirmed exoplanets in a mass - orbital distance plane, where the segregation of planets into different populations is evident. Treating DIPs as a separate population and studying their hosts’ properties can provide vital clues about the dominant mechanism of planet formation at large orbital distances from the star. The parameter space of massive planets at long orbital periods occupied by DIPs is relatively unexplored for the correlation studies of host star-planet properties. Also, the high-mass limit of wide-orbit planets overlaps with the low-mass tail of brown-dwarfs and sub-stellar companions. Therefore, in certain cases, the limitation of low-number DIP statistics can be partly overcome by a complementary study of known brown-dwarf companions sharing the same parameter space (Ma & Ge, 2014; Vigan et al., 2017; Nielsen et al., 2019). Therefore, it is essential to investigate the role, if any, of the host-star metallicity in influencing the process of the giant planet and brown-dwarf formation over a wide range of astrophysical conditions.

We have examined the confirmed list of DIP hosted on the NASA’s Exoplanet archive (Akeson et al., 2013)¹¹1https://exoplanetarchive.ipac.caltech.edu/index.html. The available stellar and planetary parameters are compiled from the composite planet data table for known exoplanets and published literature. Each of these systems has been studied and discussed in depth by individual discovery and follow-up papers. However, there are limited instances where the DIP distribution and stellar properties are studied as separate ensemble (Neuhäuser & Schmidt, 2012; Bowler, 2016).

Out of the 45 stars hosting DIPs listed in the Table 1 taken form the NASA Exoplanet archive, we could cross-match 42 of them with the GAIA DR2 catalog of which $T_{\mathrm{eff}}$ and luminosity was available for 26 stars (for cross-matching see Viswanath et al. (2020)). The atmospheric properties of the stars hosting these wide orbit companions are not very well studied, and most notably, the metallicity is known only for 14 such systems.

In general, previous studies (Buchhave et al., 2014; Santos et al., 2017; Narang et al., 2018; Schlaufman, 2018) have shown that the average metallicity of the host star increases as a function of planetary mass. However, the trend reverses for most planetary-mass above 4-5 $M_{J}$ (Narang et al., 2018; Santos et al., 2017; Schlaufman, 2018; Maldonado et al., 2019). These results suggest the possibility of two planet formation scenarios with the Jupiter-like planets ($0.3-5M_{J}$) likely formed by the core-accretion process(e.g. Mizuno, 1980; Pollack et al., 1996; Ida & Lin, 2004; Mordasini et al., 2012) and the massive super-Jupiters ($>5M_{J}$) via the disk instability mechanism (e.g. Boss, 1997; Mayer et al., 2002; Boss, 2002; Matsuo et al., 2007; Santos et al., 2017; Narang et al., 2018; Goda & Matsuo, 2019). These findings, backed by large statistics, truly reflect the underlying metallicity-mass distribution of compact planetary systems (orbital period $\lesssim$  1 yr). This raises another important question whether or not such trends hold for planets formed at vast orbital distances from the central star. Since DIPs are found at large distances from their host stars, this planet-population motivates us to explore the mass-metallicity relationship for giant planet populations at large distances in light of various planet formation scenarios. This paper has used high-resolution spectra available from various public archives to determine the stellar parameters and metallicity of 18 stars hosting DIPs in a consistent and homogeneous way to study the various correlation among stellar and planetary properties.

The rest of the paper is organized as follows. In section 2, we give a brief overview of directly imaged planetary systems. We describe our sample and give the selection criteria in section 3. Our methodology and Bayesian approach used for the estimation of various stellar parameters is discussed in section 4. In section 5, we discuss our results and compare them with previous findings. Finally, we give our summary and conclusions in section 6.

Of the $4200+$ confirmed planets, direct imaging technique accounts for the discovery of 51 planetary-mass objects around 45 stars. Among these, 40 are in a single planetary system, and four are in multi-planetary systems -LkCa 15, TYC 8998-760-1, and PDS70 with two planets each and HR8799 with four. The majority of them are discovered from deep imaging surveys of nearby star forming regions. These planet search programs largely target young pre-main sequence stars that belong to nearby stellar associations and moving groups, all within 200 pc of the Sun (Bowler, 2016). The high luminosity of planets at early formation stage make them amenable for the direct imaging. Further, the high-resolution and high-contrast imaging of planets is facilitated by the adaptive optics technology and stellar coronagraphy. With advanced differential imaging and psf extraction techniques, new generation of instruments, e.g. Gemini Planet Imager (GPI), ScExAO on Subaru and SPHERE on VLT, are capable of probing Jupiter-mass planetary companions within a few mas separation from the central star.

Masses of self-luminous planets are inferred from hot-star evolutionary tracks and infrared fluxes, but in some cases, they are well constrained by precise astrometric measurements (Baraffe et al., 2003; Wang et al., 2018; Snellen & Brown, 2018a; Nielsen et al., 2019; Wagner et al., 2019). The onset of deuterium burning limit ($\sim 13M_{\mathrm{J}}$) is a commonly used criteria to separate a planet from a brown-dwarf (Burrows et al., 1997; Saumon & Marley, 2008; Spiegel et al., 2011). However, by taking different composition and formation scenarios into account, the upper cut-off range could be as high as $25-30\leavevmode\nobreak\ M_{\mathrm{J}}$ (Baraffe et al., 2010; Schneider et al., 2011). We acknowledge this ambiguity of overlapping mass range, but we clump all directly imaged objects up to $\sim 30M_{\mathrm{J}}$ in the DIP category for the present work.

The histogram shown in Figure 1(b) reveals that except for one case²²2CFBDSIR J145829+101343b is the closest planet at orbital distance 2.6 AU from the central star that is resolved by the direct imaging., the projected semi-major axis distance of all DIPs are larger than the Jupiter’s orbital distance. The distribution peaks at an orbital distance of 150-500 AU and extend up to $\approx 3500$ AU. The lower limit of the distribution is set by the inner working angle of the coronagraph, while the drop beyond few thousand AU is influenced by the limited sensitivity to detect the positional change of planets in long-period orbits.

The median mass of the DIP population is about $\approx 12.5\,M_{\mathrm{J}}$ with lowest mass object $2\,M_{\mathrm{J}}$ and about half the number more massive than $13\,M_{\mathrm{J}}$. Most stellar hosts of these planets are also relatively young, i.e., $\approx 75\%$ below the age of $\sim 100$ Myr and more than two-thirds of the total belonging to the late spectral types with $T_{\mathrm{eff}}\leqslant 4500$ K. From the literature, we also find evidence of circumstellar disk around 22 such systems.

The equilibrium temperature of imaged planets ranges from $300-2800$ K, though most of them are above $1600$ K. The projected angular separation between the host-star and planet varies by four orders of magnitude ranging from $\approx 10^{-2}-10^{2}$ arc-sec. A large angular separation from the central star and inherent brightness due to their high temperature make this giant planet population ideal for direct detection (Traub & Oppenheimer, 2010).

We note that the current DIP sample is not a true representative of the underlying population of planets in outer orbits. It is heavily biased towards young, hot, more-massive ($\geqslant 4M_{\mathrm{J}}$) companions of young stars. The complexity of high-contrast instruments and the limitation of observing a single object at a time also makes the discovery rate slow. Studying DIP hosts spectroscopically is a major challenge because of their wide spectral range and complexities (veiling, extinction, etc) associated with young and pre-main sequence stars. Therefore, it is also difficult to apply a strictly uniform and homogeneous methodology for the whole sample’s characterization.

The NASA Exoplanet archive has 3185 stars with confirmed planets found by various discovery methods. We found 2831 out of stars cross-matched with the GAIA DR2 catalog, which has the most accurate parallaxes and precise multi-band photometry of all-sky stellar sources down to magnitude $G\approx 21$. Figure 2 shows the location of these stars in the HR diagram with $T_{\mathrm{eff}}$, and stellar luminosity is taken from the GAIA catalog.

The archive also contains the list of 45 host stars of directly imaged planets given in Table 1. Of these, 42 are found in the GAIA DR2 catalog, and their position in the HR diagram is also shown in Figure 2. The summary of astrophysical parameters of the DIP host stars listed in Table 1 and our selection criteria for spectroscopic analysis is as follows:

• •

  We searched various public archives for the availability of high-resolution optical spectra for individual DIP hosts and also surveyed the literature on their metallicity. Based on these findings, we separated the 45 DIP host stars in Table 1 into three distinct groups demarcated by horizontal lines.

• •

  The first 18 stars in Table 1 is a subsample of DIP host stars analyzed in this paper for which the spectra are available from public archives, but literature metallicity is known only for ten targets. These stars have an effective temperature range between 4059-10690 K and G-band magnitude smaller than $\sim 13$. For this subsample, we determined the atmospheric parameters and metallicity [Fe/H] homogeneously for the first time. We obtained high-resolution, high-SNR spectra for 14 targets from the ESO science archive facility³³3http://archive.eso.org/scienceportal/ and for four targets from Keck⁴⁴4https://koa.ipac.caltech.edu/cgi-bin/KOA/nph-KOAlogin archive. The ESO’s Science Portal provides access to the already reduced and wavelength calibrated data. Details of original spectra, e.g., telescope/instrument, resolution, wavelength coverage, and SNR, are listed in Table 2.

• •

  In the 2nd group of Table 1, there are 4 DIP host stars for which the metallicity is taken from the literature. The last 23 DIP hosts belonging to the 3rd group in Table 1 are not analyzed in this paper because majority of them are fainter ($m_{v}>13$). For these stars either the spectra was not available in the public domain or the quality of the data was poor (low-SNR). This group also includes some of the hot and very rapidly rotating stars ($v\cdot\sin i>160$ Km/s), which do not have clear spectral features and reliable atmospheric models for parameter estimation.

• •

  Most stellar parameters listed in Table 1 are taken from the NASA Exoplanet Archive. Furthermore, we cross-checked the accuracy of these parameters and replaced the missing values with those from the discovery and relevant follow up papers. The log$\,g$ values marked by ‘*’ symbols are not listed in the standard archives(such as Nasa exoplanet archive), and we have calculated them from stellar mass and radius values available from the literature.

Spectral synthesis and equivalent width (EW) method are two commonly used techniques to derive the stellar parameter of interest from a high-resolution spectra of stars (Gray & Corbally, 1994; Erspamer & North, 2002; Nissen & Gustafsson, 2018; Blanco-Cuaresma, 2019; Jofré et al., 2019). Despite intrinsic differences, each method requires the proper prescription of a stellar atmospheric model, a well-characterized atomic line list, reference solar abundance, and the radiative transfer code. Most notably, the relevant model parameters in both methods are allowed to vary, and a least-squares minimization is performed to reach the convergence. For example, in the EW case, the desired parameters are those for which the correlation between abundances and equivalent widths (excitation equilibrium and ionization balance) is minimized to zero. In spectral synthesis, theoretical spectra are iteratively generated from the model atmosphere and compared with the observed spectra of the star until a best match is found. The parameters of the best-matched spectra are the closest that describe the properties of the real star. The spectral synthesis method, which we adopted for our Bayesian model, is also suitable for analyzing young and fast-rotating stars present in our sample.

In the standard paradigm for the formation of a Jupiter-like planet via core nucleated accretion (e.g. D’Angelo & Lissauer, 2018), a rocky protoplanetary core forms first, which then accretes gas and dust from the surrounding disk to become a gas giant (Boss, 1997; Bodenheimer & Pollack, 1986; Pollack et al., 1996; Ikoma et al., 2001). The critical (or minimum) core mass required to form a gas giant depends on various factors (e.g., location on the protoplanetary disk, accretion rate of solids, etc.) and generally decreases with increasing disk radius: minimum core mass drops from $\sim$ 8.5 $M_{\oplus}$ at 5 AU to $\sim$ 3.5 $M_{\oplus}$ at 100 AU (Piso & Youdin, 2014; Piso et al., 2015). If the protoplanetary disk is rich in solids, i.e., higher metallicity, then the rocky core can grow faster and reach the critical mass for gas accretion well before the disk is depleted of gas. Therefore, it is easier to form Jupiter-like gas giants in disks around higher metallicity stars (e.g., Ida & Lin, 2004; Kornet et al., 2005; Wyatt et al., 2007; Boss, 2010; Mordasini et al., 2012). Indeed, observations have shown that the frequency of Jupiter-like planets is higher around higher metallicity stars (e.g. Gonzalez, 1997; Santos et al., 2001; Fischer & Valenti, 2005; Udry & Santos, 2007b). While not as strong as that seen for gas giants, smaller planets also show a weaker tendency to occur more frequently around relatively higher metallicity stars, even though their host stars appear to have a larger spread in the metallicity (e.g., Wang & Fischer, 2015; Buchhave et al., 2014; Mulders et al., 2016). It has now been adequately established that the host star metallicity ([Fe/H]), on average, increases with increasing planet mass or radius (e.g. Buchhave et al., 2014; Petigura et al., 2018; Narang et al., 2018; Mulders, 2018). Thus the observed strong dependence of the planet mass/radius on the host star metallicity supports the core accretion model for planet formation.

However, the observed correlation of increasing host star metallicity with increasing planet mass turns over at about 4-5 $M_{J}$. For planet masses higher than this (super-Jupiters), the correlation reverses, and the average host star metallicity decreases as the mass of the planet increases (Santos et al., 2017; Narang et al., 2018). This suggests that stars hosting super-Jupiters are not necessarily metal-rich, unlike stars hosting Jupiters. This trend appears to continue for more massive companions: the average metallicity of stars with a brown-dwarf secondary is also close to solar to sub-solar, and not super-solar like stars hosting Jupiters. (Ma & Ge, 2014; Narang et al., 2018; Schlaufman, 2018).

Our sample of directly imaged planets occupy a mass range similar to that of super-Jupiters and brown-dwarfs. The fact that the average host star metallicities of brown-dwarfs and super-Jupiters are similar and that they differ from that of Jupiter-hosts perhaps indicates a similar formation scenario for them that is different from that of Jupiters. It has been suggested that massive planets and low-mass brown-dwarfs can form via gravitational fragmentation of the disk rather than core accretion (e.g. Boss, 1997; Mayer et al., 2002). This gravitational instability model of planet formation predicts no dependence between planet mass and host star metallicity (e.g., Boss, 2002; Cai et al., 2006; Matsuo et al., 2007; Boss, 2010) unlike the core accretion model that predicts such a dependence.

We further compare the directly imaged planets with the large population of giant planets and brown-dwarfs around main-sequence stars discovered by techniques other than the direct imaging. To this end, we found 637 stars hosting 746 giant planets and massive objects with mass range $1-55M_{\mathrm{J}}$ listed in NASA’s exoplanet archive. We also searched the above sample in the SWEET-CATALOG (Santos et al., 2013; Sousa et al., 2018), which provides the metallicity information for 459 stellar hosts having 494 companions. Additionally, a catalog of 58 brown-dwarfs and their stellar companions was chosen from Ma & Ge (2014). A joint sample of 552 objects was formed by combining the giant planets and brown dwarfs. This combined sample has a mass range from $1-80M_{\mathrm{J}}$ and orbital distance spanning 0.02-20 AU. Since objects in the combined sample come from RV, transits, TTV, astrometry, and microlensing observations, we have used the minimum mass ($M\cdot\sin i$) wherever the true mass was not available.

We then ran a clustering analysis on the 2D-data set of combined samples of giant planets and brown-dwarfs with host star metallicity as one parameter and orbital-distance and companion-mass as other. For clustering analysis, we considered a Gaussian mixture model and implemented using a Python library scikit-learn package (Pedregosa et al., 2011). The Gaussian mixture model optimally segregated the combined sample into three clusters in metallicity - planet mass plane, as shown in the top panel of Figure 10 and into two clusters in metallicity - orbital distance plane as shown in the bottom panel of the Figure 10.

The clustering analysis in Figure 10 at the top clearly divides the combined sample into three mass and metallicity bins. The mass boundaries roughly located at $\approx 4M_{\mathrm{J}}$ and $\approx 14M_{\mathrm{J}}$ are consistent with multiple population of giant planets (i.e., Jupiters and super-Jupiters) and brown-dwarfs, pointing to their different physical origin. Further on, the declining centroid metallicity of each group in Figure 10 at the top, i.e., $0.089\pm 0.02$, $0.023\pm 0.002$ to $0.013\pm 0.009$ dex, is also consistent with previous results. The DIP population studied in this work is also shown for comparison in Figure 10. The DIP population falls between the super-Jupiters and brown-dwarfs population, both in mass and metallicity.

The analysis of orbital-distance and stellar-metallicity shows that the combined population of close-in objects separates into two distinct groups, as shown in the bottom panel of the Figure 10. Again, the DIP sample analyzed in this work is added to the plot for comparison. In metallicity – orbital distance plane, three populations again clearly separate out. On comparing the centroid values of the metallicity, which are 0.076, 0.042, and -0.097 dex, (standard deviation in each case $\leq 10^{-6}$), we find a decreasing metallicity trend with increasing orbital distance. A similar metallicity dependence with orbital distance is also reported for the Jupiter analogs (Mulders et al., 2016; Buchhave et al., 2018; Mulders, 2018).

In Figure 11, we compare the cumulative metallicity distribution of DIP host stars with stellar companions of brown-dwarfs Ma & Ge (2014), and giant planets –both Jupiter-type and super-Jupiters. We note that the cumulative distribution of DIP host stars at the lower metallicity region clearly differs from the stellar hosts of Jupiter-type planets, whereas the distribution for super-Jupiters and brown-dwarf hosts is falling in between the two. However, there is no marked difference in the higher metallicity side beyond [Fe/H]$>0$.

Although the specific factors that influence planet formation are still not fully understood, metallicity seems to be one of the major contributing factors which determine the type of planets likely to be formed around a star. Using synthetic planet population models Mordasini et al. (2012) showed that a high-metallicity environment determines whether or not a giant planet in the mass range $1-4M_{\mathrm{J}}$ can form. But metallicity alone is not the only parameter in determining the final mass of the planet except for the very massive planets ($\geq 10M_{\mathrm{J}}$), as the critical core must form very fast before the dissipation of the gas in the disk by accretion onto the star (Hayashi et al., 1985; Matsuo et al., 2007). The prediction of Mordasini et al. (2012) that the very massive planets ($\geq$ $10M_{\mathrm{J}}$) can form only at very high metallicity conditions is contrary to our findings. Our results are indicative of the possibility of two planet formation pathways: one in which the giant planets up to $4-5M_{J}$ might are formed by core accretion process, and the other where the massive super-Jupiters and brown-dwarfs are formed via gravitational fragmentation of the protoplanetary disk.

Our results for wide-orbit (10s-1000s AU) planets are also consistent with the mass-metallicity trend observed for super-Jupiters and brown-dwarfs in close-in ($\lesssim$ 1 AU) orbits around main-sequence stars. The formation mechanism of planets in wider orbits is still unclear. However, the mixed metallicity of our DIP host star sample and its close resemblance with commutative metallicity distribution of brown-dwarf hosts make it likely that massive and young planets in wider-orbits too formed via gravitational instability. However, a larger sample is required to further validate such conclusions.

We have used high-resolution spectra to measure the atmospheric parameters of young stars that are confirmed host stars of planets detected by direct imaging technique. Our sample consists of 22 such stars selected from NASA’s Exoplanet Archive. For 18 of these targets, the stellar parameters and metallicity are determined in a uniform and consistent way. The summary of our results is as follows:

1. 1.

   We used the Bayesian analysis to estimated the atmospheric parameters and metallicity for 18 DIP host stars. The MCMC technique was used to obtain the posterior distribution of stellar using model spectra generated using the iSpec. The computed metallicity [Fe/H] of these stars spans a wide range from between $+0.3$ and $-0.65$ dex.

2. 2.

   We investigated the trend between the average host star metallicity and mass of the planet, which shows that directly imaged planets with $M_{P}\leqslant 5M_{J}$ tend to have metal-rich hosts. This is in line with the predictions of planet formation via core accretion. However, as the planet mass increases, the average metallicity of the host stars shows a declining trend, suggesting that these planets are likely formed by gravitational instability. These findings seem consistent with the results reported by Santos et al. (2017) and Narang et al. (2018). Since the metallicity of a star doesn’t change during evolution, we do not expect these trends to change significantly for the currently undetected population of cool and massive giant planets in the outstretched regions of the main sequence stars. Moreover, main sequence host stars, in general, show a trend of decreasing metallicity with increasing orbital distance of the planet (e.g., Mulders et al. (2016), Buchhave et al. (2018), Mulders (2018), Narang et al. (2018)).

3. 3.

   From clustering analysis, as discussed above in section 6, we find that the DIP host stars separate as a different class of celestial objects in stellar metallicity–orbital distance plane. Furthermore, we can see a decreasing trend in the centroids of the host-star metallicity as the star-planet separation increases.

4. 4.

   In the planetary mass- stellar metallicity plane, it is found that the Jupiter-like planets are more likely to form around a metal-rich star. It also shows a decreasing trend in average stellar metallicity as the planetary mass increases. The DIP population clusters lie in between the super -Jupiters and brown dwarf populations.

It is also important to recognize that the composition of circumstellar material from which the planets are formed needn’t necessarily be the same as the composition of the parent star. The degree of similarity or difference would depend on how and where planets are formed, what stage of evolution they are in, the disk mass and planet multiplicity. A clear picture is expected to emerge from the ongoing high contrast imaging surveys and future experiments aimed at searching planets in wider orbits.

This work has made use of (a) ESO archival data that was observed under programs 192.C-0224, 098.C-0739, 266.D-5655, 094.A-9012, 084.C-1039, 074.C-0037, and 65.I-0404; (b) the Keck Observatory Archive (KOA), which is operated by the W. M. Keck Observatory and the NASA Exoplanet Science Institute (NExScI), under contract with the National Aeronautics and Space Administration; (c) the NASA Exoplanet Database, which is run by the California Institute of Technology under an Exoplanet Exploration Program contract with the National Aeronautics and Space Administration and (d) the European Space Agency (ESA) space mission Gaia, the data from which were processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.

Some initial test observations for this work were taken with 2m Himalayan Chandra Telescope at Hanle. The facilities at IAO and CREST are operated by the Indian Institute of Astrophysics, Bangalore. Furthermore, this work has made use of the NASA Exoplanet Database, which is run by the California Institute of Technology under an Exoplanet Exploration Program contract with the National Aeronautics and Space Administration. Swastik C. would also like to thank Aritra Chakrabarty at the Indian Institute of Astrophysics for the insightful discussion on the Bayesian analysis.

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