Accuracy and Precision of Industrial Stellar Abundances

Jofré, P.; Heiter, U.; Soubiran, C.

doi:10.1146/annurev-astro-091918-104509

Cited by 179 publications

(168 citation statements)

References 216 publications

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“…Following the requirements of the Gaia-ESO Survey, both methods use MARCS stellar atmosphere models (Gustafsson et al 2008) and the Gaia-ESO linelist (Heiter et al 2020). These two nodes were selected because they represent two of the most widely used methods for parameter determination in stellar spectroscopy (equivalent widths and syntheses, see Jofré et al 2019). Figure 3 illustrates the iterative process between spectroscopic and seismic parameter determinations that was followed in this analysis.…”

Section: Iterative Determination Of Parametersmentioning

confidence: 99%

“…However, the robustness of the stellar parameters determined for these large spectroscopic datasets depends, in particular, on the accuracy of the parameters of just a few small samples of reference stars (see discussion in e.g. Jofré et al 2019). A stellar reference set commonly used for the validation and verification of automated stellar parameterisation pipelines is the Gaia FGK Benchmark Stars (Jofré et al 2014;Heiter et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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The Gaia-ESO Survey: Spectroscopic-asteroseismic analysis of K2 stars in Gaia-ESO

Worley

Jofré

Rendle

et al. 2020

A&A

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Context. The extensive stellar spectroscopic datasets that are available for studies in Galactic Archeaology thanks to, for example, the Gaia-ESO Survey, now benefit from having a significant number of targets that overlap with asteroseismology projects such as Kepler, K2, and CoRoT. Combining the measurements from spectroscopy and asteroseismology allows us to attain greater accuracy with regard to the stellar parameters needed to characterise the stellar populations of the Milky Way. Aims. The aim of this Gaia-ESO Survey special project is to produce a catalogue of self-consistent stellar parameters by combining measurements from high-resolution spectroscopy and precision asteroseismology. Methods. We carried out an iterative analysis of 90 K2@Gaia-ESO red giants. The spectroscopic values of Teff were used as input in the seismic analysis to obtain log g values. The seismic estimates of log g were then used to re-determine the spectroscopic values of Teff and [Fe/H]. Only one iteration was required to obtain parameters that are in good agreement for both methods and, thus, to obtain the final stellar parameters. A detailed analysis of outliers was carried out to ensure a robust determination of the parameters. The results were then combined with Gaia DR2 data to compare the seismic log g with a parallax-based log g and to investigate instances of variations in the velocity and possible binaries within the dataset. Results. This analysis produced a high-quality catalogue of stellar parameters for 90 red giant stars from K2@Gaia-ESO that were determined through iterations between spectroscopy and asteroseismology. We compared the seismic gravities with those based on Gaia parallaxes to find an offset which is similar to other studies that have used asteroseismology. Our catalogue also includes spectroscopic chemical abundances and radial velocities, as well as indicators for possible binary detections.

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Section: Iterative Determination Of Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Gaia-ESO Survey: Spectroscopic-asteroseismic analysis of K2 stars in Gaia-ESO

Worley

Jofré

Rendle

et al. 2020

A&A

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“…For most of high resolution spectra data sets, their precise element information are extracted from the absorption lines based on the measurement of equivalent widths (EWs) or the computation of synthetic spectra (Jofré et al 2019). However, for most medium resolution spectra, these methods do not play a desired role to precisely derive elemental abundances because of line blending.…”

Section: Introductionmentioning

confidence: 99%

SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey

Wang

Luo

Chen³

et al. 2020

ApJ

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The fundamental stellar atmospheric parameters (T eff and log g) and 13 chemical abundances are derived for medium-resolution spectroscopy from LAMOST Medium-Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named as SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet are with precisions of 119 K for T eff and 0.17 dex for log g. The abundance precision of 11 elements including [[Fe/H], and [Ni/H] are 0.06∼0.12 dex, while of [Cu/H] is 0.19 dex. These precisions can be reached even for spectra with signal-to-noise as low as 10. The results of SPCANet are consistent with those from other surveys such as APOGEE, GALAH and RAVE, and are also validated with the previous literature values including clusters and field stars. The catalog of the estimated parameters is available at http://paperdata.china-vo.org/LAMOST/MRS parameters elements.csv.

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“…Valenti & Fischer 2005;Piskunov & Valenti 2017), one of the most widely-used spectroscopic techniques for determining stellar atmospheric parameters. A full account of the key caveats of these two methods can be found in Jofré et al (2019) and Blanco-Cuaresma (2019). The advent of high-resolution near-infrared (NIR) spectrographs such as CARMENES (Quirrenbach et al 2018), SPIRou (Artigau et al 2014), GIANO (Origlia et al 2014;Oliva et al 2018), CRIRES+ (Hatzes & CRIRES+ Team 2017), IRD (Kotani et al 2014), HPF (Wright et al 2018), and NIRPS (Wildi et al 2017) allows us to revisit these techniques, originally applied in the optical, in order to assess the impact of the NIR wavelength range on stellar parameter computations.…”

Section: Introductionmentioning

confidence: 99%

Stellar atmospheric parameters of FGK-type stars from high-resolution optical and near-infrared CARMENES spectra

Marfil

Tabernero

Montes

et al. 2020

Monthly Notices of the Royal Astronomical Society

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With the purpose of assessing classic spectroscopic methods on high-resolution and high signal-to-noise ratio spectra in the near-infrared wavelength region, we selected a sample of 65 F-, G-, and K-type stars observed with CARMENES, the new, ultrastable, double-channel spectrograph at the 3.5 m Calar Alto telescope. We computed their stellar atmospheric parameters (T eff , log g, ξ, and [Fe/H]) by means of the StePar code, a Python implementation of the equivalent width method that employs the 2017 version of the MOOG code and a grid of MARCS model atmospheres. We compiled four Fe i and Fe ii line lists suited to metal-rich dwarfs, metal-poor dwarfs, metal-rich giants, and metal-poor giants that cover the wavelength range from 5 300 to 17 100Å, thus substantially increasing the number of identified Fe i and Fe ii lines up to 653 and 23, respectively. We examined the impact of the near-infrared Fe i and Fe ii lines upon our parameter determinations after an exhaustive literature search, placing special emphasis on the 14 Gaia benchmark stars contained in our sample. Even though our parameter determinations remain in good agreement with the literature values, the increase in the number of Fe i and Fe ii lines when the near-infrared region is taken into account reveals a deeper T eff scale that might stem from a higher sensitivity of the near-infrared lines to T eff .

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Accuracy and Precision of Industrial Stellar Abundances

Abstract: 8Jofré et al.

Cited by 179 publications

References 216 publications

The Gaia-ESO Survey: Spectroscopic-asteroseismic analysis of K2 stars in Gaia-ESO

The Gaia-ESO Survey: Spectroscopic-asteroseismic analysis of K2 stars in Gaia-ESO

SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey

Stellar atmospheric parameters of FGK-type stars from high-resolution optical and near-infrared CARMENES spectra

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