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P. Jofré

Publications and source records attributed to P. Jofré.

At least 19 recordsLinked to original sources

Gaia FGK benchmark stars: Abundances of n-capture elements of the third version

In the current era, in which an unprecedented wealth of data are available for the study of the Milky Way, Gaia benchmark stars (GBSs) have become an established reference and calibration sample. Studies of stellar structure and evolution and of the chemical history of our Galaxy generally rely on large spectroscopic surveys and their output catalogs. In this context, deriving precise and accurate stellar parameters and chemical abundances is of paramount importance. This study provides the determination of neutron (n)-capture element abundances and extends the set of chemical abundances available for the third GBS release (GBSv3). Based on the compilation of high-resolution spectra assembled for GBSv3 and consistent with the spectral analysis adopted for the chemical abundances of GBSv3, we used the public iSpec code to derive heavy element abundances. We inferred homogeneous abundances of n-capture elements across the GBSv3 sample using an in-depth line assessment tailored to different groups identified through a clustering algorithm that accounts for the diversity in stellar parameters and metallicities. This approach addresses key challenges in the spectral analysis of these elements, including the paucity of usable lines, weak line strengths, saturation effects, and sensitivity to atomic data. The assessment yielded reliable measurements, establishing an extended and robust reference scale in good agreement with the literature. This compilation of n-capture abundances is based on the GBS sample's accurate atmospheric parameters and the analysis of a large sample of stellar spectra per star, which provides a reliable and homogeneous spectral analysis. It also supports the use of chemical abundances as precise tracers of the Milky Ways star formation history and chemical evolution and constitutes a legacy sample for the calibration of current and future spectroscopic surveys.

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Stellar nucleosynthesis in the era of large surveys: S-process polluted binaries in GALAH DR4

Binary interactions during the AGB phase can lead to the formation of chemically peculiar stars with overabundances of s-process elements. Only a few hundreds of these stars have been subject to detailed chemical or dynamical studies. This work aims at compiling a systematic sample of s-process-polluted candidates using GALAH DR4. We also want to compare their properties with those of confirmed s-polluted stars to have stronger evidence of their nature. GALAH DR4 uses neural networks and automatic spectral analysis methods as well as data of a lower spectral resolution than normally used to characterise these objects. Because of this, we built a validation sample, for which we obtained UVES@VLT and HERMES@Mercator high-resolution spectra. We compare our stellar parameters and abundances with those of the survey and use this validation to define the thresholds that a star in GALAH DR4 must pass to be flagged as a good s-process-rich candidate. Based on our comparisons, we define thresholds on [s/Fe], [Y/Fe], [Zr/Fe], [Ba/Fe], and [La/Fe]. We identified 1059 stars in GALAH DR4 that are good candidates to be s-process polluted stars, covering a broad parameter space. They share many similarities with the samples of confirmed s-rich stars, especially their ratios of heavy over light s-elements ([hs/ls]), which strengthen our confidence in the purity of the sample. We find that only 7% of the candidates have measured orbital periods and eccentricities, limiting for now a full comparison with confirmed Ba and related stars. However, their binary fraction is, as expected, higher than the one we found for the full GALAH DR4 catalogue. Our sample of candidates is almost five times larger than the number of currently confirmed polluted stars. This and the fact that it has been homogeneously treated by GALAH open very interesting avenues to confront nucleosynthesis and binary evolution models.

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Gaia FGK Benchmark Stars: spectral library, metallicities and abundances of $α$ and Fe-peak elements of the third version

The accurate determination of chemical abundances in stars plays a pivotal role in understanding stellar structure and evolution, nucleosynthesis, and the chemical enrichment history of the Milky Way. Benchmark stars with precise and accurate atmospheric parameters and abundances are indispensable for calibrating spectroscopic surveys and testing stellar atmosphere models. This study focuses on the compilation of high-quality spectra and the determination of LTE chemical abundances of iron-peak and $α$ elements for the third version of the Gaia FGK Benchmark Stars (GBSv3). We compiled spectra of the GBSv3 from public archives and complemented these with our own observations. We use fundamental atmospheric parameters from Soubiran et al. 2024 to derive the chemical abundances and perform a spectroscopic analysis using the public code iSpec. We compile a homogeneous spectral library of high-resolution (42,000) and high signal-to-noise ($>100$) normalised spectra for 202 stars: including the 192 GBSv3, 9 stars with indirect measurement of the angular diameter from previous GBS versions, and the Sun. Using four radiative transfer codes, we derive chemical abundances of 13 chemical species (Fe I, Fe II, Mg I, Si I, Ca I, Ti I, Ti II, Sc II, V I, Cr I, Mn I, Co I, Ni I). We make an in-depth study of several sources of error. The GBSv3 contributes to the legacy samples of spectroscopic reference stars with improved statistics and homogeneity. This work offers the community a homogeneous spectral library and robust reference abundances for iron-peak and $α$ elements, supported by an extensive analysis of the associated uncertainties.

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Studying stellar populations in Omega Centauri with phylogenetics

The nature and formation history of our Galaxy's largest and most enigmatic stellar cluster, known as Omega Centauri (ocen) remains debated. Here, we offer a novel approach to disentangling the complex stellar populations within ocen based on phylogenetics methodologies from evolutionary biology. These include the Gaussian Mixture Model and Neighbor-Joining clustering algorithms applied to a set of chemical abundances of ocen stellar members. Instead of using the classical approach in astronomy of grouping them into separate populations, we focused on how the stars are related to each other. In this way, we could identify stars that likely formed in globular clusters versus those originating from prolonged in-situ star formation and how these stars interconnect. Our analysis supports the hypothesis that ocen might be a nuclear star cluster of a galaxy accreted by the Milky Way with a mass of about 10^9M_sun. Furthermore, we revealed the existence of a previously unidentified in-situ stellar population with a distinct chemical pattern unlike any known population found in the Milky Way to date. Our analysis of ocen is an example of the success of cross-disciplinary research and shows the vast potential of applying evolutionary biology tools to astronomical datasets, opening new avenues for understanding the chemical evolution of complex stellar systems.

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Mocking IFU observations and metallicity diagnostics from cosmological simulations

Hydrodynamic simulations are powerful tools for studying galaxy formation. However, it is crucial to test and improve the sub-grid physics underlying these simulations by comparing their predictions with observations. To this aim, observable quantities can be derived for simulated galaxies, enabling the analysis of simulated properties through an observational approach. Our goal is to develop a new numerical tool capable of generating synthetic emission line spectra from spatially resolved regions in simulated galaxies, mocking Integral Field Unit (IFU) observations. Synthetic spectra of simulated galaxies are produced by integrating the software CIGALE with the outcomes of hydrodynamical simulations. We consider contributions of both stellar populations and nebular emission. The nebular emission lines in the spectra are modeled by considering only the contributions from the simulated star-forming regions. Our model considers the properties of the surrounding interstellar medium to estimate the ionizing parameters, the metallicity, the velocity dispersion and the electron density. We present the new numerical tool PRISMA. Leveraging synthetic spectra generated by our model, PRISMA successfully computed and recovered the intrinsic values of the star formation rate and gas-phase metallicity in local regions of simulated galaxies. Additionally, we examine the behavior of metallicity tracers such as N2, R23, O3N2, N2O2, recovered by PRISMA and propose new calibrations based on our simulated result. These findings show the robustness of our tool in recovering the intrinsic properties of simulated galaxies through their synthetic spectra, thereby becoming a powerful tool to confront simulations and observational data.

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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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Exploring the dependence of chemical traits on metallicity: chemical trends for red giant stars with asteroseismic ages

Given the massive spectroscopic surveys and the Gaia mission, the Milky Way has turned into a unique laboratory to be explored using abundance ratios that show a strong dependency with time. Within this framework, the data provided through asteroseismology serve as a valuable complement. Yet, it has been demonstrated that chemical traits can not be used as universal relations across the Galaxy. To complete this picture, it is important to investigate the dependence on metallicity of the chemical ratios employed for inferring stellar ages. We aim to explore different combinations of neutron-capture, odd-Z and $α$ elements as a function of age, particularly focusing on their metallicity dependence for a sample of 74 giant field stars. Using UVES observations, we derive atmospheric parameters and high-precision line by line chemical abundances (<0.04 dex) for the entire set of spectra. Stellar ages are inferred from astereoseismic information. By fitting chemical-age trends for three different metallicity groups, we estimated their dependence on metallicity. We found that the stronger chemical-age relations ([Zr/$α$]) are not necessarily the ratios with the smaller dependence on metallicity ([Ce/$α$] and [Ce/Eu]). We confirm the [n-capture/$α$]-age trends for evolved stars, wherein the most significant correlation is evident in stars with solar-metallicity, gradually diminishing in stars with lower iron content. The lack of homogeneity within the metallicity range highlights the intricate nature of our Galaxy's star formation history and yield production. Metallicity dependence in s-process element yields and the impact of radial stellar migration challenge the reliability of using chemical abundances alone to date stars. These discoveries raise doubts about universally valid chemical clocks applicable across the entire Galaxy and its diverse metallicity ranges.

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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: 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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Unraveling UBC 274: a morphological, kinematical and chemical analysis of a disrupting open cluster

We do a morphological, kinematic and chemical analysis of the disrupting cluster UBC 274 (2.5 Gyr, $d=1778$ pc) to study its global properties. We use HDBSCAN to obtain a new membership list up to 50 pc from its centre and up to magnitude $G=19$ using Gaia EDR3 data. We use high resolution and high signal-to-noise spectra to obtain atmospheric parameters of 6 giants and subgiants, and individual abundances of 18 chemical species. The cluster has a highly eccentric (0.93) component, tilted $\sim$10 deg with respect to the plane of the Galaxy, which is morphologically compatible with the result of a test-particle simulation of a disrupting cluster. Our abundance analysis shows that the cluster has a subsolar metallicity of [Fe/H]$=-0.08\pm0.02$. Its chemical pattern is compatible with that of Ruprecht 147, of similar age but located closer to the Sun, with the remarkable exception of neutron-capture elements, which present an overabundance of $[n\mathrm{/Fe]}\sim0.1$. The cluster's elongated morphology is associated with the internal part of its tidal tail, following the expected dynamical process of disruption. We find a significant sign of mass segregation where the most massive stars appear 1.5 times more concentrated than other stars. The cluster's overabundance of neutron-capture elements can be related to the metallicity dependence of the neutron-capture yields due to the secondary nature of these elements, predicted by some models. UBC 274 presents a high chemical homogeneity at the level of $0.03$ dex in the sampled region of its tidal tails.

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The Gaia-ESO Public Spectroscopic Survey: Implementation, data products, open cluster survey, science, and legacy

In the last 15 years different ground-based spectroscopic surveys have been started (and completed) with the general aim of delivering stellar parameters and elemental abundances for large samples of Galactic stars, complementing Gaia astrometry. Among those surveys, the Gaia-ESO Public Spectroscopic Survey (GES), the only one performed on a 8m class telescope, was designed to target 100,000 stars using FLAMES on the ESO VLT (both Giraffe and UVES spectrographs), covering all the Milky Way populations, with a special focus on open star clusters. This article provides an overview of the survey implementation (observations, data quality, analysis and its success, data products, and releases), of the open cluster survey, of the science results and potential, and of the survey legacy. A companion article (Gilmore et al.) reviews the overall survey motivation, strategy, Giraffe pipeline data reduction, organisation, and workflow. The GES has determined homogeneous good-quality radial velocities and stellar parameters for a large fraction of its more than 110,000 unique target stars. Elemental abundances were derived for up to 31 elements for targets observed with UVES. Lithium abundances are delivered for about 1/3 of the sample. The analysis and homogenisation strategies have proven to be successful; several science topics have been addressed by the Gaia-ESO consortium and the community, with many highlight results achieved. The final catalogue has been released through the ESO archive at the end of May 2022, including the complete set of advanced data products. In addition to these results, the Gaia-ESO Survey will leave a very important legacy, for several aspects and for many years to come.

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J01020100-7122208: an accreted evolved blue straggler that wasn't ejected from a supermassive black hole

J01020100-7122208 is a star whose origin and nature still challenges us. It was first believed to be a yellow super giant ejected from the Small Magellanic Cloud, but it was more recently claimed to be a red giant accelerated by the Milky Way's central black hole. In order to unveil its nature, we analysed photometric, astrometric and high resolution spectroscopic observations to estimate the orbit, age, and 16 elemental abundances. Our results show that this star has a retrograde and highly-eccentric orbit, $e=0.914_{-0.020}^{+0.016}$. Correspondingly, it likely crossed the Galactic disk at $550\;\mathrm{pc}$ from the Galactic centre. We obtained a spectroscopic mass and age of $1.09\pm0.10$ $M_\odot$ and $4.51\pm1.44$ Gyr respectively. Its chemical composition is similar to the abundance of other retrograde halo stars. We found that the star is enriched in europium, having [Eu/Fe] = 0.93 $\pm$ 0.24, and is more metal-poor than reported in the literature, with [Fe/H] = -1.30 $\pm$ 0.10. This information was used to conclude that J01020100-7122208 is likely not a star ejected from the central black of the Milky Way or from the Small Magellanic Cloud. Instead, we propose that it is simply a halo star which was likely accreted by the Milky Way in the distant past but its mass and age suggest it is probably an evolved blue straggler.

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The Gaia-ESO Survey: Membership probabilities for stars in 63 open and 7 globular clusters from 3D kinematics

Spectroscopy from the final internal data release of the Gaia-ESO Survey (GES) has been combined with Gaia EDR3 to assign membership probabilities to targets observed towards 63 Galactic open clusters and 7 globular clusters. The membership probabilities are based chiefly on maximum likelihood modelling of the 3D kinematics of the targets, separating them into cluster and field populations. From 43211 observed targets, 13985 are identified as highly probable cluster members ($P>0.9$), with an average membership probability of 0.993. The addition of GES radial velocities successfully drives down the fraction of false positives and we achieve better levels of discrimination in most clusters over the use of astrometric data alone, especially those at larger distances. Since the membership selection is almost purely kinematic, the union of this catalogue with GES and Gaia is ideal for investigating the photometric and chemical properties of clusters as a function of stellar mass, age and Galactic position.

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The Gaia-ESO Survey: A new approach to chemically characterising young open clusters II. Abundances of the neutron-capture elements Cu, Sr, Y, Zr, Ba, La, and Ce

Young open clusters (t<200 Myr) have been observed to exhibit several peculiarities in their chemical compositions, from a slightly sub-solar iron content, super-solar abundances of some atomic species (e.g. ionised chromium), and atypical enhancements of [Ba/Fe], with values up to +0.7 dex. Regarding the behaviour of the other $s$-process elements like yttrium, zirconium, lanthanum, and cerium, there is general disagreement in the literature. In this work we expand upon our previous analysis of a sample of five young open clusters (IC2391, IC2602, IC4665, NGC2516, and NGC2547) and one star-forming region (NGC2264), with the aim of determining abundances of different neutron-capture elements, mainly CuI, SrI, SrII, YII, ZrII, BaII, LaII, and CeII. We analysed high-resolution, high signal-to-noise spectra of 23 solar-type stars observed within the \textit{Gaia}-ESO survey. We find that our clusters have solar [Cu/Fe] within the uncertainties, while we confirm the super-solar [Ba/Fe] values (from +0.22 to +0.64 dex). Our analysis also points to mildly enhanced [Y/Fe] values (from 0 and +0.3 dex). For the other $s$-process elements we find that [X/Fe] ratios are solar at all ages. It is not possible to reconcile the anomalous behaviour of Ba and Y at young ages with standard stellar yields and Galactic chemical evolution model predictions. Thus, we explore different possible scenarios related to the behaviour of spectral lines, from the sensitivity to the presence of magnetic fields to the first ionisation potential effect. We also investigate the possibility that they may arise from alterations of the structure of the stellar photosphere due to higher levels of activity in such young stars. We are still unable to explain these enhancements, but we suggest that other elements (i.e. La) might be more reliable tracer of the $s$-process at young ages and encourage further observations.

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The Gaia-ESO Survey: Galactic evolution of lithium from iDR6

We exploit the unique characteristics of a sample of open clusters (OCs) and field stars for which high-precision 7Li abundances and stellar parameters are homogeneously derived by the Gaia-ESO Survey (GES). We derive possibly undepleted 7Li abundances for 26 OCs and star forming regions with ages from young to old spanning a large range of Galactocentric distances, which allows us to reconstruct the local late Galactic evolution of lithium as well as its current abundance gradient along the disc. Field stars are added to look further back in time and to constrain 7Li evolution in other Galactic components. The data are then compared to theoretical tracks from chemical evolution models that implement different 7Li forges. We find that the upper envelope of the 7Li abundances measured in field stars of nearly solar metallicities traces very well the level of lithium enrichment attained by the ISM as inferred from observations of cluster stars. We confirm previous findings that the abundance of 7Li in the solar neighbourhood does not decrease at supersolar metallicity. The comparison of the data with the chemical evolution model predictions favours a scenario in which the majority of the 7Li abundance in meteorites comes from novae. Current data also seem to suggest that the nova rate flattens out at later times. This requirement might have implications for the masses of the white dwarf nova progenitors and deserves further investigation. Neutrino-induced reactions taking place in core-collapse supernovae also produce some fresh lithium. This likely makes a negligible contribution to the meteoritic abundance, but could be responsible for a mild increase of the 7Li abundance in the ISM of low-metallicity systems that would counterbalance the astration processes.

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Abundance-age relations with red clump stars in open clusters

Context: Precise chemical abundances coupled with reliable ages are key ingredients to understand the chemical history of our Galaxy. Open Clusters (OCs) are useful for this purpose because they provide ages with good precision. Aims: The aim of this work is to investigate the relations of different chemical abundance ratios vs age traced by red clump (RC) stars in OCs. Methods: We analyze a large sample of 209 reliable members in 47 OCs with available high-resolution spectroscopy. We applied a differential line-by-line analysis to provide a comprehensive chemical study of 25 chemical species. This sample is among the largest samples of OCs homogeneously characterized in terms of atmospheric parameters, detailed chemistry, and ages. Results: In our metallicity range (-0.2<[M/H]<+0.2) we find that while most Fe-peak and alpha elements have flat dependence with age, the s-process elements show decreasing trends with increasing age with a remarkable knee at 1 Gyr. For Ba, Ce, Y, Mo and Zr we find a plateau at young ages (< 1 Gyr). We investigate the relations of all possible combinations among the computed chemical species with age. We find 19 combinations with significant slopes, including [Y/Mg] and [Y/Al]. The ratio [Ba/alpha] is the one with the most significant correlations found. Conclusions: We find that the [Y/Mg] relation found in the literature using Solar twins is compatible with the one found here in the Solar neighbourhood. The age-abundance relations show larger scatter for clusters at large distances (d>1 kpc) than for the Solar neighbourhood, particularly in the outer disk. We conclude that these relations need to be understood also in terms of the complexity of the chemical space introduced by the Galactic dynamics, on top of pure nucleosynthetic arguments, especially out of the local bubble.

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