Context.
We describe the atomic and molecular data that were used for the abundance analyses of FGK-type stars carried out within the
Gaia
-ESO Public Spectroscopic Survey in the years 2012 to 2019. ...The
Gaia
-ESO Survey is one among several current and future stellar spectroscopic surveys producing abundances for Milky-Way stars on an industrial scale.
Aims.
We present an unprecedented effort to create a homogeneous common line list, which was used by several abundance analysis groups using different radiative transfer codes to calculate synthetic spectra and equivalent widths. The atomic data are accompanied by quality indicators and detailed references to the sources. The atomic and molecular data are made publicly available at the CDS.
Methods.
In general, experimental transition probabilities were preferred but theoretical values were also used. Astrophysical
gf
-values were avoided due to the model-dependence of such a procedure. For elements whose lines are significantly affected by a hyperfine structure or isotopic splitting, a concerted effort has been made to collate the necessary data for the individual line components. Synthetic stellar spectra calculated for the Sun and Arcturus were used to assess the blending properties of the lines. We also performed adetailed investigation of available data for line broadening due to collisions with neutral hydrogen atoms.
Results.
Among a subset of over 1300 lines of 35 elements in the wavelength ranges from 475 to 685 nm and from 850 to 895 nm, we identified about 200 lines of 24 species which have accurate
gf
-values and are free of blends in the spectra of the Sun and Arcturus. For the broadening due to collisions with neutral hydrogen, we recommend data based on Anstee-Barklem-O’Mara theory, where possible. We recommend avoiding lines of neutral species for which these are not available. Theoretical broadening data by R.L. Kurucz should be used for Sc
II
, Ti
II
, and Y
II
lines; additionally, for ionised rare-earth species, the Unsöld approximation with an enhancement factor of 1.5 for the line width can be used.
Conclusions.
The line list has proven to be a useful tool for abundance determinations based on the spectra obtained within the
Gaia
-ESO Survey, as well as other spectroscopic projects. Accuracies below 0.2 dex are regularly achieved, where part of the uncertainties are due to differences in the employed analysis methods. Desirable improvements in atomic data were identified for a number of species, most importantly Al
I
, S
I
, and Cr
II
, but also Na
I
, Si
I
, Ca
II
, and Ni
I
.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Context. The pattern of chemical abundance ratios in stellar populations of the Milky Way is a fingerprint of the Galactic chemical history. In order to interpret such chemical fossils of Galactic ...archaeology, chemical evolution models have to be developed. However, despite the complex physics included in the most recent models, significant discrepancies between models and observations are widely encountered. Aims. The aim of this paper is to characterise the abundance patterns of five iron-peak elements (Mn, Fe, Ni, Cu, and Zn) for which the stellar origin and chemical evolution are still debated. Methods. We automatically derived iron peak (Mn, Fe, Ni, Cu, and Zn) and α element (Mg) chemical abundances for 4666 stars, adopting classical LTE spectral synthesis and 1D atmospheric models. Our observational data collection is composed of high-resolution, high signal-to-noise ratios HARPS and FEROS spectra, which were previously parametrised by the AMBRE project. Results. We used the bimodal distribution of the magnesium-to-iron abundance ratios to chemically classify our sample stars into different Galactic substructures: thin disc, metal-poor and high-α metal rich, high-α, and low-α metal-poor populations. Both high-α and low-α metal-poor populations are fully distinct in Mg, Cu, and Zn, but these substructures are statistically indistinguishable in Mn and Ni. Thin disc trends of Ni/Fe and Cu/Fe are very similar and show a small increase at supersolar metallicities. Also, both thin and thick disc trends of Ni and Cu are very similar and indistinguishable. Yet, Mn looks very different from Ni and Cu. Mn/Fe trends of thin and thick discs actually have noticeable differences: the thin disc is slightly Mn richer than the thick disc. The Zn/Fe trends look very similar to those of α/Fe trends. The typical dispersion of results in both discs is low (≈0.05 dex for Mg, Mn, and Cu/Fe) and is even much lower for Ni/Fe (≈0.035 dex). Conclusions. It is clearly demonstrated that Zn is an α-like element and could be used to separate thin and thick disc stars. Moreover, we show that the Mn/Mg ratio could also be a very good tool for tagging Galactic substructures. From the comparison with Galactic chemical evolutionary models, we conclude that some recent models can partially reproduce the observed Mg, Zn, and, Cu behaviours in thin and thick discs and metal-poor sequences. Models mostly fail to reproduce Mn and Ni in all metallicity domains, however, models adopting yields normalised from solar chemical properties reproduce Mn and Ni better, suggesting that there is still a lack of realistic theoretical yields of some iron-peak elements. The very low scatter (≈0.05 dex) in thin and thick disc sequences could provide an observational constrain for Galactic evolutionary models that study the efficiency of stellar radial migration.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Aims.
The aim of this work is to determine abundances of neutron-capture elements for thin- and thick-disc F, G, and K stars in several selected sky fields near the north ecliptic pole and to compare ...the results with the Galactic chemical evolution models, to explore elemental gradients according to stellar ages, mean galactocentric distances, and maximum heights above the Galactic plane.
Methods.
The observational data were obtained with the 1.65 m telescope at the Molėtai Astronomical Observatory and a fibre-fed high-resolution spectrograph covering a full visible wavelength range (4000−8500 Å). Elemental abundances were determined using a differential line-by-line spectrum synthesis using the TURBOSPECTRUM code with the MARCS stellar model atmospheres and accounting for the hyperfine-structure effects.
Results.
We determined abundances of Sr, Y, Zr, Ba, La, Ce, Pr, Nd, Sm, and Eu for 424 thin- and 82 thick-disc stars. The sample of thick-disc stars shows a clearly visible decrease in Eu/Mg with increasing metallicity compared to the thin-disc stars, bringing more evidence of a different chemical evolution in these two Galactic components. Abundance correlation with age slopes for the investigated thin-disc stars are slightly negative for the majority of
s
-process dominated elements, while
r
-process dominated elements have positive correlations. Our sample of thin-disc stars with ages spanning from 0.1 to 9 Gyr gives the Y/Mg = 0.022 (±0.015)−0.027 (±0.003)⋅age Gyr relation. However, for the thick-disc stars, when we also took data from other studies into account, we found that Y/Mg cannot serve as an age indicator. The radial abundance-to-iron gradients in the thin disc are negligible for the
s
-process dominated elements and become positive for the
r
-process dominated elements. The vertical gradients are negative for the light
s
-process dominated elements and become positive for the
r
-process dominated elements. In the thick disc, the radial abundance-to-iron slopes are negligible, and the vertical slopes are predominantly negative.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Context.
In June 2022,
Gaia
DR3 provided the astronomy community with about one million spectra from the Radial Velocity Spectrometer (RVS) covering the CaII triplet region. In the next
Gaia
data ...releases, we anticipate the number of RVS spectra to successively increase from several 10 million spectra to eventually more than 200 million spectra. Thus, stellar spectra are projected to be produced on an ‘industrial scale’, with numbers well above those for current and anticipated ground-based surveys. However, one-third of the published spectra have 15 ≤
S /N
≤ 25 per pixel such that they pose problems for classical spectral analysis pipelines, and therefore, alternative ways to tap into these large datasets need to be devised.
Aims.
We aim to leverage the versatility and capabilities of machine learning techniques for supercharged stellar parametrisation by combining
Gaia
-RVS spectra with the full set of
Gaia
products and high-resolution, high-quality ground-based spectroscopic reference datasets.
Methods.
We developed a hybrid convolutional neural network (CNN) that combines the
Gaia
DR3 RVS spectra, photometry (G, G_BP, G_RP), parallaxes, and XP coefficients to derive atmospheric parameters (
T
eff
, log(g) as well as overall M/H) and chemical abundances (Fe/H and
α
/M). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels.
Results.
With this CNN, we derived homogeneous atmospheric parameters and abundances for 886 080 RVS stars that show remarkable precision and accuracy compared to external datasets (such as GALAH and asteroseismology). The CNN is robust against noise in the RVS data, and we derive very precise labels down to S/N =15. We managed to characterise the
α
/M - M/H bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets.
Conclusions.
This work is the first to combine machine learning with such diverse datasets and paves the way for large-scale machine learning analysis of
Gaia
-RVS spectra from future data releases. Large, high-quality datasets can be optimally combined thanks to the CNN, thereby realising the full power of spectroscopy, astrometry, and photometry.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Accurate atmospheric parameters and chemical composition of stars play a vital role in characterizing physical parameters of exoplanetary systems and understanding of their formation. A full ...asteroseismic characterization of a star is also possible if its main atmospheric parameters are known. The NASA Transiting Exoplanet Survey Satellite (TESS) space telescope will play a very important role in searching of exoplanets around bright stars and stellar asteroseismic variability research. We have observed all 302 bright (V < 8 mag) and cooler than F5 spectral class stars in the northern TESS continuous viewing zone with a 1.65 m telescope at the Mol tai Astronomical Observatory of Vilnius University and the high-resolution Vilnius University Echelle Spectrograph. We uniformly determined the main atmospheric parameters, ages, orbital parameters, velocity components, and precise abundances of 24 chemical species (C(C2), N(CN), O i, Na i, Mg i, Al i, Si i, Si ii, Ca i, Ca ii, Sc i, Sc ii, Ti i, Ti ii, V i, Cr i, Cr ii, Mn i, Fe i, Fe ii, Co i, Ni i, Cu i, and Zn i) for 277 slowly rotating single stars in the field. About 83% of the sample stars exhibit the Mg/Si ratios greater than 1.0 and may potentially harbor rocky planets in their systems.
Context. The Gaia-ESO Public Spectroscopic Survey using FLAMES at the VLT has obtained high-resolution UVES spectra for a large number of giant stars, allowing a determination of the abundances of ...the key chemical elements carbon and nitrogen at their surface. The surface abundances of these chemical species are known to change in stars during their evolution on the red giant branch (RGB) after the first dredge-up episode, as a result of the extra mixing phenomena. Aims. We investigate the effects of thermohaline mixing on C and N abundances using the first comparison between the Gaia-ESO survey C/N determinations with simulations of the observed fields using a model of stellar population synthesis. Methods. We explore the effects of thermohaline mixing on the chemical properties of giants through stellar evolutionary models computed with the stellar evolution code STAREVOL. We include these stellar evolution models in the Besançon Galaxy model to simulate the C/N distributions determined from the UVES spectra of the Gaia-ESO survey and to compare them with the observations. Results. Theoretical predictions including the effect of thermohaline mixing are in good agreement with the observations. However, the field stars in the Gaia-ESO survey with C and N abundance measurements have a metallicity close to solar, where the efficiency of thermohaline mixing is not very large. The C and N abundances derived by the Gaia-ESO survey in open and globular clusters clearly show the impact of thermohaline mixing at low metallicity, which explains the C/N value observed in lower mass and older giant stars. Using independent observations of carbon isotopic ratio in clump field stars and open clusters, we also confirm that thermohaline mixing should be taken into account to explain the behaviour of 12C/13C as a function of stellar age. Conclusions. Overall, the current model including thermohaline mixing is able to reproduce very well the C and N abundances over the whole metallicity range investigated by the Gaia-ESO survey data.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Context.
NGC 1851 is one of several globular clusters for which multiple stellar populations of the subgiant branch have been clearly identified and a difference in metallicity detected. A crucial ...piece of information on the formation history of this cluster can be provided by the sum of
A
(C+N+O) abundances. However, these values have lacked a general consensus thus far. The separation of the subgiant branch can be based on age and/or
A
(C+N+O) abundance differences.
Aims.
Our main aim was to determine carbon, nitrogen, and oxygen abundances for evolved giants in the globular cluster NGC 1851 in order to check whether or not the double populations of stars are coeval.
Methods.
High-resolution spectra, observed with the FLAMES-UVES spectrograph on the ESO VLT telescope, were analysed using a differential model atmosphere method. Abundances of carbon were derived using spectral synthesis of the C
2
band heads at 5135 and 5635.5 Å. The wavelength interval 6470−6490 Å, with CN features, was analysed to determine nitrogen abundances. Oxygen abundances were determined from the O
I
line at 6300 Å. Abundances of other chemical elements were determined from equivalent widths or spectral syntheses of unblended spectral lines.
Results.
We provide abundances of up to 29 chemical elements for a sample of 45 giants in NGC 1851. The investigated stars can be separated into two populations with a difference of 0.07 dex in the mean metallicity, 0.3 dex in the mean C/N, and 0.35 dex in the mean
s
-process dominated element-to-iron abundance ratios
s
/Fe. No significant difference was determined in the mean values of
A
(C+N+O) as well as in abundance to iron ratios of carbon,
α
- and iron-peak-elements, and of europium.
Conclusions.
As the averaged
A
(C+N+O) values between the two populations do not differ, additional evidence is given that NGC 1851 is composed of two clusters, the metal-rich cluster being by about 0.6 Gyr older than the metal-poor one. A global overview of NGC 1851 properties and the detailed abundances of chemical elements favour its formation in a dwarf spheroidal galaxy that was accreted by the Milky Way.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
Abstract
In fulfilling the aims of the planetary and asteroseismic research missions, such as that of the NASA Transiting Exoplanet Survey Satellite (TESS) space telescope, accurate stellar ...atmospheric parameters and a detailed chemical composition are required as inputs. We have observed high-resolution spectra for all 848 bright (
V
< 8 mag) stars that are cooler than F5 spectral class in the area up to 12 deg surrounding the northern TESS continuous viewing zone and uniformly determined the main atmospheric parameters, ages, orbital parameters, velocity components, and precise abundances of up to 24 chemical species (C(C
2
), N(CN), O
i
, Na
i
, Mg
i
, Al
i
, Si
i
, Si
ii
, Ca
i
, Ca
ii
, Sc
i
, Sc
ii
, Ti
i
, Ti
ii
, V
i
, Cr
i
, Cr
ii
, Mn
i
, Fe
i
, Fe
ii
, Co
i
, Ni
i
, Cu
i
, and Zn
i
) for 740 slowly rotating stars. The analysis of 25 planet-hosting stars in our sample drove us to the following conclusions: the dwarf stars hosting high-mass planets are more metal rich than those with low-mass planets. We find slightly negative C/O and Mg/Si slopes toward the stars with high-mass planets. All the low-mass planet hosts in our sample show positive ΔEl/Fe versus condensation temperature slopes, in particular, the star with the largest number of various planets. The high-mass planet hosts have a diversity of slopes, but in more metal-rich, older, and cooler stars, the positive elemental abundance slopes are more common.
Abundances of lithium, carbon, and oxygen have been derived using spectral synthesis for a sample of 249 bright F, G, and K Northern Hemisphere dwarf stars from the high-resolution spectra acquired ...with the VUES spectrograph at the Mol tai Astronomical Observatory of Vilnius University. The sample stars have metallicities, effective temperatures, and ages between (-0.7 0.4) dex, (5000 6900) K, (1 12) Gyr, accordingly. We confirm a so far unexplained lithium abundance decrease at supersolar metallicities-A(Li) in our sample stars, which drop by 0.7 dex in the Fe/H range from +0.10 to +0.55 dex. Furthermore, we identified stars with similar ages, atmospheric parameters, and rotational velocities, but with significantly different lithium abundances, which suggests that additional specific evolutionary factors should be taken into account while interpreting the stellar lithium content. Nine stars with predominantly supersolar metallicities, i.e., about 12% among 78 stars with C and O abundances determined, have the C/O number ratios larger than 0.65, thus may form carbon-rich rocky planets. Ten planet-hosting stars, available in our sample, do not show a discernible difference from the stars with no planets detected regarding their lithium content.
Context.
To take full advantage of upcoming large-scale spectroscopic surveys, it will be necessary to parameterize millions of stellar spectra in an efficient way. Machine learning methods, ...especially convolutional neural networks (CNNs), will be among the main tools geared at achieving this task.
Aims.
We aim to prepare the groundwork for machine learning techniques for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that CNNs can predict accurate stellar labels from relevant spectral features in a physically meaningful way. The predicted labels can be used to investigate properties of the Milky Way galaxy.
Methods.
We built a neural network and trained it on GIRAFFE spectra with their associated stellar labels from the sixth internal
Gaia
-ESO data release. Our network architecture contains several convolutional layers that allow the network to identify absorption features in the input spectra. The internal uncertainty was estimated from multiple network models. We used the t-distributed stochastic neighbor embedding tool to remove bad spectra from our training sample.
Results.
Our neural network is able to predict the atmospheric parameters
T
eff
and log(
g
) as well as the chemical abundances Mg/Fe, Al/Fe, and Fe/H for 36 904 stellar spectra. The training precision is 37 K for
T
eff
, 0.06 dex for log(
g
), 0.05 dex for Mg/Fe, 0.08 dex for Al/Fe, and 0.04 dex for Fe/H. Network gradients reveal that the network is inferring the labels in a physically meaningful way from spectral features. We validated our methodology using benchmark stars and recovered the properties of different stellar populations in the Milky Way galaxy.
Conclusions.
Such a study provides very good insights into the application of machine learning for the analysis of large-scale spectroscopic surveys, such as WEAVE and 4MOST Milky Way disk and bulge low- and high-resolution (4MIDABLE-LR and -HR). The community will have to put substantial efforts into building proactive training sets for machine learning methods to minimize any possible systematics.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
PDF
