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S. Zaggia

Publications and source records attributed to S. Zaggia.

At least 19 recordsLinked to original sources

Something new under the Sun: A magnetically driven CH/CN anti-correlation

Spectroscopic monitoring surveys have shown that the magnetic cycle alters the photospheric structure of the Sun, perturbing the formation of molecular lines. In parallel, the study of Globular Clusters has remained centred on the multiple stellar populations conundrum, a phenomenon defined-most notably-by the anti-correlation between CH and CN molecular bands, serving to distinguish between first-population and second-population stars. We systematically monitored the behaviour of the CH and CN molecular bands as a function of the solar magnetic cycle. We demonstrate that the disc-integrated solar spectrum exhibits a distinct CH/CN anti-correlation driven by the magnetic cycle. Our results suggest that the spectroscopic and photometric anomalies defining the multiple populations conundrum may be physically linked to a differential spectral response to varying degrees of surface magnetic coverage.

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photoD with Rubin's Data Preview 1: first stellar photometric distances and deficit of faint blue stars. Stellar distances with Rubin's DP1

Aims: We investigate the utility of Rubin's Data Preview 1 for estimating stellar number density profile in the Milky Way halo. Methods: Stellar broad-band near-UV to near-IR $ugrizy$ photometry released in Rubin's Data Preview 1 is used to estimate distance and metallicity for blue main sequence stars brighter than $r=24$ in three $\sim$1.1. sq.~deg. fields at southern Galactic latitudes. Results: Compared to TRILEGAL simulations of the Galaxy's stellar content by (Dal Tio, 2022), we find a significant deficit of blue main sequence turn-off stars with $22 < r < 24$. We interpret this discrepancy as a signature of a much steeper halo number density profile at galactocentric distances $10-50$ kpc than the cannonical $\sim1/r^3$ profile assumed in TRILEGAL simulations. Conclusions: This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, and a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin's Legacy Survey of Space and Time.

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PARSEC V2.0: Rotating tracks and isochrones for seven addtional metallicities in the range Z=0.0001-0.03

PARSEC v2.0 rotating stellar tracks were previously presented for six values of metallicity from subsolar to solar values, with initial rotation rates ($ω_\mathrm{i}$, defined as the ratio of angular velocity and its critical value) spanning from the non-rotating case to very near the critical velocity (i.e. $ω_\mathrm{i}=0.99$), and for initial masses covering the $\sim 0.7 M_\odot$ to $14 M_\odot$ interval. Furthermore, we provided the corresponding isochrones converted into several photometric systems, for different inclination angles between the line-of-sight and the rotation axes, from $0^\circ$ (pole-on) to $90^\circ$ (equator-on). In this work, we expand this database with seven other sets of metallicity, including five sets of low metallicity ($Z=0.0001-0.002$) and two sets of super-solar values (up to $Z=0.03$). Here, we present the new stellar tracks, comprising $\sim$3\,040 tracks in total ($\sim$5\,500 including previous sets), along with the new corresponding rotating isochrones. We also introduce the possibility of creating isochrones, by interpolation, for values of rotating rates not available in the initial set of tracks. We compare a selection of our new models with rotating stellar tracks from the Geneva Stellar Evolution Code, and we assess the quality of our new tracks by fitting the colour-magnitude diagram of the open cluster NGC6067. We take advantage of the projected rotational velocity of member stars measured by Gaia to validate our results and examine the surface oxygen abundances in comparison with the observed data. All newly computed stellar tracks and isochrones are retrievable via our dedicated web databases and interfaces.

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The Gaia-ESO Survey: Projected Rotational Velocities of B stars in the Carina Nebula

The Carina Nebula is an active star-forming region with several open clusters rich in massive OB stars, thus making it an optimal target for studying stellar properties such as rotation for large samples of these early-type stars. We studied a sample of early-type stars probable members of the 8 open clusters in the Carina Complex. The observational data consist of high-resolution spectra from the Gaia-ESO public Spectroscopic Survey. Astrometric and photometric data from Gaia EDR3 and radial velocities measured from the observed spectra are used to confirm the cluster members. The projected rotational velocities of 330 early-type stars of Carina are derived from the widths of \ion{He}{i} lines at 4388 and 4471 Å. The reported \Vsini\ values are the first estimates for 222 early-type stars. The \Vsini\ distribution for the Carina clusters peaks at $\sim$100-150 \kms, consistent with the distributions for B stars in Galactic clusters. \Vsini\ estimates for stars members of the clusters Trumpler 15, Collinder 228, Collinder 232, and Bochum 11 are presented for the first time in the literature. For a subsample of stars with earlier spectral types from B0 to B3, we find a bimodal distribution, with a third, small peak towards the upper values of \Vsini. When the full sample is split according to the parent cluster, we find that the oldest cluster in our sample, NGC 3293, presents a higher concentration of rapidly rotating stars. In contrast, Collinder 228 presents a larger number of stars with lower \Vsini.

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The VMC survey -- LIII. Data release #7. Complete survey data and data from additional programmes

The near-infrared YJKs Visual and Infrared Survey Telescope for Astronomy (VISTA) survey of the Magellanic Clouds (VMC) is complete and there are also data from additional programmes enhancing its quality over the original footprint. This work presents the final data release of the VMC survey, which includes additional observations and provides an overview of the scientific results. The overall data quality has been revised and reprocessed standard data products, that already appeared in previous data releases, are made available together with new data products. These include individual stellar proper motions, reddening towards red clump stars and source classifications. Several data products, such as the parameters of some variable stars and of background galaxies, from the VMC publications are associated to a data release for the first time. The data are processed using the VISTA Data Flow System and additional products, e.g. catalogues with point-spread function photometry or tables with stellar proper motions, are obtained with software developed by the survey team. This release supersedes all previous data releases of the VMC survey for the combined (deepstacked) data products, whilst providing additional (complementary) images and catalogues of single observations per filter. Overall, it includes about 64 million detections, split nearly evenly between sources with stellar or galaxy profiles. The VMC survey provides a homogeneous data set resulting from deep and multi-epoch YJKs-band imaging observations of the Large and Small Clouds, the Bridge and two fields in the Stream. The VMC data represent a valuable counterpart for sources detected at other wavelengths for both stars and background galaxies.

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Evolutionary tracks, ejecta, and ionizing photons from intermediate-mass to very massive stars with PARSEC

Recent advancements in stellar evolution modeling offer unprecedented accuracy in predicting the evolution and deaths of stars. We present new stellar evolutionary models computed with the updated PARSEC V2.0 code for a comprehensive and homogeneous grid of metallicities and initial masses. Nuclear reaction networks, mass loss prescriptions, and the treatment of elemental mixing have all been updated in PARSEC V2.0. We computed models for thirteen initial metallicities spanning $Z = 10^{-11}$ to $Z = 0.03$, with masses ranging from 2.0 M$_{\odot}$ to 2000 M$_{\odot}$, consisting of a library of over 1,100 ($\sim 2100$ tracks including pure-He models) full stellar evolution tracks. For each track, the evolution is followed from the pre-main-sequence to the most advanced early-asymptotic-giant-branch or the pre-supernova phases, depending on the stellar mass. Here, we describe the properties of the tracks and their chemical and structural evolution. We computed the final fates and the remnant masses and built the mass spectrum for each metallicity, finding that the combined black hole (BH) pair-instability mass gap spans just between 100 and 130 M$_{\odot}$. Moreover, the remnant masses provide models consistent with observed BH masses, such as those from the primaries of GW190521, Cygnus X-1, and $\textit{Gaia}$ BH3 binary systems. We computed and provided the chemical ejecta from stellar winds and explosive final fates, along with the ionizing photon rates. Our results show strong overall consistency with other tracks computed with different codes. A comparison with a large sample of observed massive stars in the Tarantula Nebula of the Large Magellanic Cloud shows that our tracks nicely reproduce the majority of stars that lie on the main sequence. All the models are publicly available and can be retrieved on the PARSEC database.

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The Gaia-ESO Survey: No sign of multiple stellar populations in open clusters from their sodium and oxygen abundances

Context: The light element (anti-)correlations shown by globular clusters (GCs) are the main spectroscopic signature of multiple stellar populations. These internal abundance variations provide us with fundamental constraints on the formation mechanism of stellar clusters. Aims: Using Gaia-ESO, the largest and most homogeneous survey of open clusters (OCs), we intend to check whether these stellar aggregates display the same patterns. Based on previous studies of many GCs, several young and massive clusters in the Magellanic Clouds, as well as a few OCs, we do not expect to find any anti-correlation, given the low mass of Milky Way OCs. Methods: We used the results based on UVES spectra of stars in Gaia-ESO to derive the distribution of Na and O abundances and seevwhether they show an unexplained dispersion or whether they are anti-correlated. By selecting only high-probability members with high-precision stellar parameters, we ended up with more than 700 stars in 74 OCs. We examined the O-Na distribution in 28 OCsvwith at least 4 stars available as well as the Na distribution in 24 OCs, with at least 10 stars available. Results: We find that the distribution of Na abundances is compatible with a single-value population, within the errors. The fewvapparent exceptions can be explained by differences in the evolutionary phase (main sequence and giant post first dredge-up episode) or by difficulties in analysing low gravity giants. We did not find any indication of an Na-O anti-correlation in any of the clusters for which O has been derived. Conclusions: Based on the very small spread we find, OCs maintain the status of single stellar populations. However, a definitive answer requires studying more elements and larger samples covering different evolutionary phases. This will be possible with the next generation of large surveys

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The Gaia-ESO Survey: Calibrating the lithium-age relation with open clusters and associations. II. Expanded cluster sample and final membership selection

The Li abundance observed in pre-main sequence and main sequence late-type stars is strongly age-dependent, but also shows a complex pattern depending on several parameters, such as rotation, chromospheric activity and metallicity. The best way to calibrate these effects, with the aim of studying Li as an age indicator for FGK stars, is to calibrate coeval groups of stars, such as open clusters (OCs) and associations. We present a considerable target sample of 42 OCs and associations, ranging from 1 Myr to 5 Gyr, observed within the Gaia-ESO survey (GES), and using the latest data provided by GES iDR6 and the most recent release of Gaia that was then available, EDR3. As part of this study, we update and improve the membership analysis for all 20 OCs presented in our previous article. We perform detailed membership analyses for all target clusters to identify likely candidates, using all available parameters provided by GES and based on numerous criteria: from radial velocity distributions, to the astrometry and photometry provided by Gaia, to gravity indicators, [Fe/H] metallicity, and Li content. We obtain updated lists of cluster members for the whole target sample, as well as a selection of Li-rich giant contaminants obtained as an additional result of the membership process. Each selection of cluster candidates was thoroughly contrasted with numerous existing membership studies using data from Gaia to ensure the most robust results. These final cluster selections will be used in the third and last paper of this series, which reports the results of a comparative study characterising the observable Li dispersion in each cluster and analysing its dependence on several parameters, allowing us to calibrate a Li-age relation and obtain a series of empirical Li envelopes for key ages in our sample.

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The Gaia-ESO Survey: The DR5 analysis of the medium-resolution GIRAFFE and high-resolution UVES spectra of FGK-type stars

The Gaia-ESO Survey is an European Southern Observatory (ESO) public spectroscopic survey that targeted $10^5$ stars in the Milky Way covering the major populations of the disk, bulge and halo. The observations were made using FLAMES on the VLT obtaining both UVES high ($R\sim47,000$) and GIRAFFE medium ($R\sim20,000$) resolution spectra. The analysis of the Gaia-ESO spectra was the work of multiple analysis teams (nodes) within five working groups (WG). The homogenisation of the stellar parameters within WG11 (high resolution observations of FGK stars) and the homogenisation of the stellar parameters within WG10 (medium resolution observations of FGK stars) is described here. In both cases, the homogenisation was carried out using a bayesian Inference method developed specifically for the Gaia-ESO Survey by WG11. The WG10 homogenisation primarily used the cross-match of stars with WG11 as the reference set in both the stellar parameter and chemical abundance homogenisation. In this way the WG10 homogenised results have been placed directly onto the WG11 stellar parameter and chemical abundance scales. The reference set for the metal-poor end was sparse which limited the effectiveness of the homogenisation in that regime. For WG11, the total number of stars for which stellar parameters were derived was 6,231 with typical uncertainties for Teff, log g and [Fe/H] of 32~K, 0.05 and 0.05 respectively. One or more chemical abundances out of a possible 39 elements were derived for 6,188 of the stars. For WG10, the total number of stars for which stellar parameters were derived was 76,675 with typical uncertainties for Teff, log g and [Fe/H] of 64~K, 0.15 and 0.07 respectively. One or more chemical abundances out of a possible 30 elements were derived for 64,177 of the stars.

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The nature of medium-period variables on the extreme horizontal branch I. X-shooter study of variable stars in the globular cluster $ω$ Cen

A fraction of the extreme horizontal branch stars of globular clusters exhibit a periodic light variability that has been attributed to rotational modulation caused by surface spots. These spots are believed to be connected to inhomogeneous surface distribution of elements. However, the presence of such spots has not been tested against spectroscopic data. We analyzed the phase-resolved ESO X-shooter spectroscopy of three extreme horizontal branch stars that are members of the globular cluster $ω$ Cen and also display periodic light variations. The aim of our study is to understand the nature of the light variability of these stars and to test whether the spots can reproduce the observed variability. Our spectroscopic analysis of these stars did not detect any phase-locked abundance variations that are able to reproduce the light variability. Instead, we revealed the phase variability of effective temperature and surface gravity. In particular, the stars show the highest temperature around the light maximum. This points to pulsations as a possible cause of the observed spectroscopic and photometric variations. However, such an interpretation is in a strong conflict with Ritter's law, which relates the pulsational period to the mean stellar density. The location of the $ω$ Cen variable extreme horizontal branch stars in HR diagram corresponds to an extension of PG 1716 stars toward lower temperatures or blue, low-gravity, large-amplitude pulsators toward lower luminosities, albeit with much longer periods. Other models of light variability, namely, related to temperature spots, should also be tested further. The estimated masses of these stars in the range of $0.2-0.3\,M_\odot$ are too low for helium-burning objects.

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The Gaia-ESO Survey: new spectroscopic binaries in the Milky Way

The Gaia-ESO Survey (GES) is a large public spectroscopic survey which acquired spectra for more than 100000 stars across all major components of the Milky Way. In addition to atmospheric parameters and stellar abundances that have been derived in previous papers of this series, the GES spectra allow us to detect spectroscopic binaries with one (SB1), two (SB2) or more (SBn $\ge$ 3) components. Cross-correlation functions (CCFs) have been re-computed thanks to a dozen spectral masks probing a range of effective temperatures, surface gravities and metallicities. By optimising the mask choice for a given spectrum, the new computed so-called Nacre (Narrow cross-correlation experiment) CCFs are narrower and allow to unblend more stellar components than standard masks. The Doe (Detection of Extrema) extremum-finding code then selects the individual components and provides their radial velocities. From the sample of HR10 and HR21 spectra corresponding to 37565 objects, the present study leads to the detection of 322 SB2, ten (three of them being tentative) SB3, and two tentative SB4. In particular, compared to our previous study, the Nacre CCFs allow us to multiply the number of SB2 candidates by $\approx$ 1.5. The colour-magnitude diagram reveals, as expected, the shifted location of the SB2 main sequence. A comparison between the SB identified in Gaia DR3 and the ones detected in the present work is performed and the complementarity of the two censuses is discussed. An application to mass-ratio determination is presented, and the mass-ratio distribution of the GES SB2 is discussed. When accounting for the SB2 detection rate, an SB2 frequency of $\approx$ 1.4% is derived within the present stellar sample of mainly FGK-type stars. As primary outliers identified within the GES data, SBn spectra produce a wealth of information and useful constraints for the binary population synthesis studies.

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The Gaia-ESO Survey: Empirical estimates of stellar ages from lithium equivalent widths (EAGLES)

We present an empirical model of age-dependent photospheric lithium depletion, calibrated using a large, homogeneously-analysed sample of 6200 stars in 52 open clusters, with ages from 2--6000 Myr and $-0.3<{\rm [Fe/H}]<0.2$, observed in the Gaia-ESO spectroscopic survey. The model is used to obtain age estimates and posterior age probability distributions from measurements of the Li I 6708A equivalent width for individual (pre) main sequence stars with $3000 < T_{\rm eff}/{\rm K} <6500$, a domain where age determination from the HR diagram is either insensitive or highly model-dependent. In the best cases, precisions of 0.1 dex in log age are achievable; even higher precision can be obtained for coeval groups and associations where the individual age probabilities of their members can be combined. The method is validated on a sample of exoplanet-hosting young stars, finding agreement with claimed young ages for some, but not others. We obtain better than 10 per cent precision in age, and excellent agreement with published ages, for seven well-studied young moving groups. The derived ages for young clusters ($<1$ Gyr) in our sample are also in good agreement with their training ages, and consistent with several published, model-insensitive lithium depletion boundary ages. For older clusters there remain systematic age errors that could be as large as a factor of two. There is no evidence to link these errors to any strong systematic metallicity dependence of (pre) main sequence lithium depletion, at least in the range $-0.29 < {\rm [Fe/H]} < 0.18$. Our methods and model are provided as software -- "Empirical AGes from Lithium Equivalent widthS" (EAGLES).

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The Gaia-ESO Survey: homogenisation of stellar parameters and elemental abundances

The Gaia-ESO Survey is a public spectroscopic survey that has targeted $\gtrsim10^5$ stars covering all major components of the Milky Way from the end of 2011 to 2018, delivering its public final release in May 2022. Unlike other spectroscopic surveys, Gaia-ESO is the only survey that observed stars across all spectral types with dedicated, specialised analyses: from O ($T_\mathrm{eff} \sim 30,000-52,000$~K) all the way to K-M ($\gtrsim$3,500~K). The physics throughout these stellar regimes varies significantly, which has previously prohibited any detailed comparisons between stars of significantly different type. In the final data release (internal data release 6) of the Gaia-ESO Survey, we provide the final database containing a large number of products such as radial velocities, stellar parameters and elemental abundances, rotational velocity, and also, e.g., activity and accretion indicators in young stars and membership probability in star clusters for more than 114,000 stars. The spectral analysis is coordinated by a number of Working Groups (WGs) within the Survey, which specialise in the various stellar samples. Common targets are analysed across WGs to allow for comparisons (and calibrations) amongst instrumental setups and spectral types. Here we describe the procedures employed to ensure all Survey results are placed on a common scale to arrive at a single set of recommended results for all Survey collaborators to use. We also present some general quality and consistency checks performed over all Survey results.

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The Gaia-ESO Survey: Preparing the ground for 4MOST & WEAVE galactic surveys. Chemical evolution of lithium with machine learning

With its origin coming from several sources (Big Bang, stars, cosmic rays) and given its strong depletion during its stellar lifetime, the lithium element is of great interest as its chemical evolution in the Milky Way is not well understood at present. To help constrain stellar and galactic chemical evolution models, numerous and precise lithium abundances are necessary for a large range of evolutionary stages, metallicities, and Galactic volume. In the age of stellar parametrization on industrial scales, spectroscopic surveys such as APOGEE, GALAH, RAVE, and LAMOST have used data-driven methods to rapidly and precisely infer stellar labels (atmospheric parameters and abundances). To prepare the ground for future spectroscopic surveys such as 4MOST and WEAVE, we aim to apply machine learning techniques to lithium measurements and analyses. We trained a convolution neural network (CNN), coupling Gaia-ESO Survey iDR6 stellar labels (Teff, log(g), [Fe/H], and A(Li)) and GIRAFFE HR15N spectra, to infer the atm parameters and lithium abundances for ~40,000 stars. We show that the CNN properly learns the physics of the stellar labels, from relevant spectral features through a broad range of evolutionary stages and stellar parameters. The Li feature at 6707.8 A is successfully singled out by our CNN, among the thousands of lines. Rare objects such as Li-rich giants are found in our sample. This level of performance is achieved thanks to a meticulously built, high-quality, and homogeneous training sample. The CNN approach is very well adapted for the next generations of spectroscopic surveys aimed at studying (among other elements) lithium, such as the 4MIDABLE-LR/HR (4MOST Milky Way disk and bulge low- and high-resolution) surveys. In this context, the caveats of ML applications should be appropriately investigated, along with the realistic label uncertainties and upper limits for abundances.

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The Gaia-ESO Survey: Probing the lithium abundances in old metal-rich dwarf stars in the Solar vicinity

We test a scenario in which radial migration could affect the Li abundance pattern of dwarf stars in the solar neighbourhood. This may confirm that the Li abundance in these stars can not serve as a probe for the Li abundance in the interstellar medium. We use the high-quality data (including Li abundances) from the 6th internal Data Release of the Gaia-ESO survey. In this sample, we group stars by similarity in chemical abundances via hierarchical clustering. Our analysis treats both measured Li abundances and upper limits. The Li envelope of the previously identified radially migrated stars is well below the benchmark meteoritic value (<3.26 dex); the star with the highest detected abundance has A(Li) = 2.76 dex. This confirms the previous trends observed for old dwarf stars (median ages $\sim$ 8 Gyr), where Li decreases for [Fe/H]$\gtrsim$0. This result acts as supporting evidence that the abundance of Li measured in the upper envelope of old dwarf stars should not be considered a proxy for the interstellar medium Li. Our scenario also indicates that the stellar yields for [M/H]>0 should not be decreased, as recently proposed in the literature. Our study backs the recent studies that claimed that old dwarfs on the hot side of the dip are efficient probes of the ISM abundance of Li, provided atomic diffusion does not lower significantly the initial Li abundance in the atmospheres of metal-rich objects.

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The Gaia-ESO Survey: Old super-metal-rich visitors from the inner Galaxy

We report the identification of a set of old super metal-rich dwarf stars with orbits of low eccentricity that reach a maximum height from the Galactic plane between ~0.5-1.5 kpc. We discuss their properties to understand their origins. We use data from the internal data release 6 of the Gaia-ESO Survey. We selected stars observed at high resolution with abundances of 21 species of 18 individual elements. We apply hierarchical clustering to group the stars with similar chemical abundances within the complete chemical abundance space. According to their chemical properties, this set of super metal-rich stars can be arranged into five subgroups. Four seem to follow a chemical enrichment flow, where nearly all abundances increase in lockstep with Fe. The fifth subgroup shows different chemical characteristics. All subgroups have the following features: median ages of the order of 7-9 Gyr, Solar or sub-Solar [Mg/Fe] ratios, maximum height between 0.5-1.5 kpc, low eccentricities, and a detachment from the expected metallicity gradient with guiding radius. The high metallicity of our stars is incompatible with a formation in the Solar neighbourhood. Their dynamic properties agree with theoretical expectations that these stars travelled from the inner Galaxy due to blurring and, most importantly, to churning. We suggest that most of this population's stars originated in the Milky Way's inner regions (inner disc and/or the bulge) and later migrated to the Solar neighbourhood. The region from where the stars originated had a complex chemical enrichment history, with contributions from supernovae types Ia and II and possibly asymptotic giant branch stars.

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The Gaia-ESO Survey: Lithium measurements and new curves of growth

The Gaia-ESO Survey (GES) is a large public spectroscopic survey that was carried out using the multi-object FLAMES spectrograph at the Very Large Telescope. The survey provides accurate radial velocities, stellar parameters, and elemental abundances for ~115,000 stars in all Milky Way components. In this paper we describe the method adopted in the final data release to derive lithium equivalent widths (EWs) and abundances. Lithium EWs were measured using two different approaches for FGK and M-type stars, to account for the intrinsic differences in the spectra. For FGK stars, we fitted the lithium line using Gaussian components, while direct integration over a predefined interval was adopted for M-type stars. Care was taken to ensure continuity between the two regimes. Abundances were derived using a new set of homogeneous curves of growth that were derived specifically for GES, and which were measured on a synthetic spectral grid consistently with the way the EWs were measured. The derived abundances were validated by comparison with those measured by other analysis groups using different methods. Lithium EWs were measured for ~40,000 stars, and abundances could be derived for ~38,000 of them. The vast majority of the measures (80%) have been obtained for stars in open cluster fields. The remaining objects are stars in globular clusters, or field stars in the Milky Way disc, bulge, and halo. The GES dataset of homogeneous lithium abundances described here will be valuable for our understanding of several processes, from stellar evolution and internal mixing in stars at different evolutionary stages to Galactic evolution.

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The Gaia-ESO Survey: Chemical evolution of Mg and Al in the Milky Way with Machine-Learning

We aim to prepare the machine-learning ground for the next generation of spectroscopic surveys, such as 4MOST and WEAVE. Our goal is to show that convolutional neural networks can predict accurate stellar labels from relevant spectral features in a physically meaningful way. We built a neural network and trained it on GIRAFFE spectra with associated stellar labels from the sixth internal Gaia-ESO data release. Our neural network predicts the atmospheric parameters Teff and log(g) as well as the chemical abundances [Mg/Fe], [Al/Fe], and [Fe/H] for 30115 stellar spectra. The scatter of predictions from eight slightly different network models shows a high internal precision of the network results: 24 K for Teff, 0.03 for log(g), 0.02 dex for [Mg/Fe], 0.03 dex for [Al/Fe], and 0.02 dex for [Fe/H]. The network gradients reveal that the network is inferring the labels in a physically meaningful way from spectral features. Validation with benchmark stars and several scientific applications confirm that our network predictions are accurate for individual stars and recover the properties of different stellar populations in the Milky Way galaxy. Such a study provides very good insights into the application of machine-learning for the spectral analysis of large-scale spectroscopic surveys, such as WEAVE and 4MIDABLE-LR and -HR (4MOST Milky Way disk and bulge low- and high-resolution). The community will have to put a substantial effort into building proactive training sets for machine-learning methods to minimize the possible systematics.

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