Determination of stellar parameters for Ariel targets: a comparison analysis between different spectroscopic methods

Brucalassi, Anna; Tsantaki, M.; Magrini, L.; Sousa, S. G.; Danielski, Camilla; Biazzo, K.; Casali, G.; Swaelmen, M. Van der; Rainer, M.; Adibekyan, V.; Delgado-Mena, E.

doi:10.1007/s10686-020-09695-4

Cited by 8 publications

(10 citation statements)

References 65 publications

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“…These are a small representation of the statistical studies performed focusing on the potential correlations between the star's proprieties and its hosted planets. Detailed knowledge of the nature of indi-vidual stars is crucial for the thorough understanding of planetary systems currently being characterized by CHEOPS (Benz et al 2021) and ESPRESSO (Pepe et al 2021), and for preparing the selection of targets for future missions such as ARIEL (Tinetti et al 2018;Brucalassi et al 2021), and PLATO (Rauer et al 2014). SWEET-Cat is a catalog with homogeneous spectroscopic parameters for planet hosts, with near-full completeness for the RV detected planets; it was introduced by Santos et al (2013).…”

Section: Introductionmentioning

confidence: 99%

SWEET-Cat 2.0: The Cat just got SWEETer

Sousa

Adibekyan

Delgado-Mena

et al. 2021

A&A

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Aims. The catalog of Stars With ExoplanETs (SWEET-Cat) was originally introduced in 2013. Since then many more exoplanets have been confirmed, increasing significantly the number of host stars listed there. A crucial step toward a comprehensive understanding of these new worlds is the precise and homogeneous characterization of their host stars. Better spectroscopic stellar parameters along with new results from Gaia eDR3 provide updated and precise parameters for the discovered planets. A new version of the catalog, whose homogeneity in the derivation of the parameters is key to unraveling star-planet connections, is available to the community. Methods. We made use of high-resolution spectra for planet-host stars, either observed by our team or collected through public archives. The spectroscopic stellar parameters were derived for the spectra following the same homogeneous process using ARES and MOOG (ARES+MOOG) as for the previous SWEET-Cat releases. We re-derived parameters for the stars in the catalog using better quality spectra and/or using the most recent versions of the codes. Moreover, the new SWEET-Cat table can now be more easily combined with the planet properties listed both at the Extrasolar Planets Encyclopedia and at the NASA exoplanet archive to perform statistical analyses of exoplanets. We also made use of the recent GAIA eDR3 parallaxes and respective photometry to derive consistent and accurate surface gravity values for the host stars.Results. We increased the number of stars with homogeneous parameters by more than 40% (from 645 to 928). We reviewed and updated the metallicity distributions of stars hosting planets with different mass regimes comparing the low-mass planets (< 30M ⊕ ) with the high-mass planets. The new data strengthen previous results showing the possible trend in the metallicity-period-mass diagram for low-mass planets.

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Section: Introductionmentioning

confidence: 99%

SWEET-Cat 2.0: The Cat just got SWEETer

Sousa

Adibekyan

Delgado-Mena

et al. 2021

A&A

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“…In fact, while the value of [Fe/H] is usually more constant, T eff and log(g) tend to vary along a local minimum. Details specific to each method and complete set of comparison results (including all individual stellar parameters derived by FAMA and FASMA) are reported in a dedicated study by [24].…”

Section: Methods and Resultsmentioning

confidence: 99%

“…The radiative transfer code to derive the abundances is MOOG 2014 [115], assuming local thermodynamic equilibrium (LTE) and ATLAS stellar model atmospheres. The second approach used the DOOp code, based on DAOSPEC [119], to measure the EWs [27] and the FAMA code [70], based on MOOG 2014, to derive the stellar abundances (which can determine also the atmospheric parameters, as reported in Section 2 and fully described in [24]). It adopted MARCS stellar model atmospheres and the Gaia-ESO clean line-list [58], from which we selected only lines with the best oscillator strengths (log gf ).…”

Section: Na Mg Al Si Abundances Determinationmentioning

confidence: 99%

“…In parallel, in [24], we performed a benchmark study between three different spectroscopic techniques to determine stellar parameters in order to identify the most robust method(s) to uniformly determine T eff , [Fe/H] and log(g) all along the Ariel stellar parameter space. The uncertainty on these parameters directly reflects on the limb-darkening estimation, phenomenon that is important to take into account to precisely derive a planetary spectrum.…”

Section: Ground Based Observational Campaignmentioning

confidence: 99%

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The homogeneous characterisation of Ariel host stars

et al. 2021

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The Ariel mission will characterise the chemical and thermal properties of the atmospheres of about a thousand exoplanets transiting their host star(s). The observation of such a large sample of planets will allow to deepen our understanding of planetary and atmospheric formation at the early stages, providing a truly representative picture of the chemical nature of exoplanets, and relating this directly to the type and chemical environment of the host star. Hence, the accurate and precise determination of the host star fundamental properties is essential to Ariel for drawing a comprehensive picture of the underlying essence of these planetary systems. We present here a structured approach for the characterisation of Ariel stars that accounts for the concepts of homogeneity and coherence among a large set of stellar parameters. We present here the studies and benchmark analyses we have been performing to determine robust stellar fundamental parameters, elemental abundances, activity indices, and stellar ages. In particular, we present results for the homogeneous estimation of the activity indices S and log(R HK ), and preliminary results for elemental abundances of Na, Al, Mg, Si, C, N. In addition, we analyse the variation of a planetary spectrum, obtained with Ariel, as a function of the uncertainty on the stellar effective temperature. Finally, we present our observational campaign for precisely and homogeneously characterising all Ariel stars in order to perform a meaningful choice of final targets before the mission launch.

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“…The determination of stellar parameters is also of great interest to exoplanetary science because the masses and radii of the host stars are key to characterising the planets orbiting around them (see, e.g. Torres et al 2012;Santos et al 2013;Brewer et al 2016;Sousa et al 2018;Schweitzer et al 2019;Brucalassi et al 2021). Moreover, they are critical to the high-resolution transmission spectroscopy since they are employed to model the centre-to-limb variation, the limb-darkening, and the Rossiter-McLaughlin effect (see, e.g.…”

Section: Introductionmentioning

confidence: 99%

STEPARSYN: A Bayesian code to infer stellar atmospheric parameters using spectral synthesis

Tabernero

Marfil

Montes

et al. 2022

A&A

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Context. SteParSyn is an automatic code written in Python 3.X designed to infer the stellar atmospheric parameters T eff , log g, and [Fe/H] of FGKM-type stars following the spectral synthesis method. Aims. We present a description of the SteParSyn code and test its performance against a sample of late-type stars that were observed with the HERMES spectrograph mounted at the 1.2-m Mercator Telescope. This sample contains 35 late-type targets with well-known stellar parameters determined independently from spectroscopy. The code is available to the astronomical community in a GitHub repository. Methods. SteParSyn uses a Markov chain Monte Carlo (MCMC) sampler to explore the parameter space by comparing synthetic model spectra generated on the fly to the observations. The synthetic spectra are generated with an spectral emulator. Results. We computed T eff , log g, and [Fe/H] for our sample stars and discussed the performance of the code. We calculated an internal scatter for these targets of −12 ± 117 K in T eff , 0.04 ± 0.14 dex in log g, and 0.05 ± 0.09 dex in [Fe/H]. In addition, we find that the log g values obtained with SteParSyn are consistent with the trigonometric surface gravities to the 0.1 dex level. Finally, SteParSyn can compute stellar parameters that are accurate down to 50 K, 0.1 dex, and 0.05 dex for Teff, log g, and [Fe/H] for stars with sin i ≤ 30 km s −1 .

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Determination of stellar parameters for Ariel targets: a comparison analysis between different spectroscopic methods

Cited by 8 publications

References 65 publications

SWEET-Cat 2.0: The Cat just got SWEETer

SWEET-Cat 2.0: The Cat just got SWEETer

The homogeneous characterisation of Ariel host stars

STEPARSYN: A Bayesian code to infer stellar atmospheric parameters using spectral synthesis

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