arXiv subjects

R. Smiljanic

Publications and source records attributed to R. Smiljanic.

At least 37 records · Page 2Linked to original sources

arXiv2023

Gaia Focused Product Release: Radial velocity time series of long-period variables

The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity (RV) in DR4, this Focused Product Release (FPR) provides RV time series for a selection of LPVs with high-quality observations. We describe the production and content of the Gaia catalog of LPV RV time series, and the methods used to compute variability parameters published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied filters to construct a sample of sources with high-quality RV measurements. We modeled their RV and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the RV period and at least one of the $G$, $G_{\rm BP}$, or $G_{\rm RP}$ photometric periods. The catalog includes RV time series and variability parameters for 9\,614 sources in the magnitude range $6\lesssim G/{\rm mag}\lesssim 14$, including a flagged top-quality subsample of 6\,093 stars whose RV periods are fully compatible with the values derived from the $G$, $G_{\rm BP}$, and $G_{\rm RP}$ photometric time series. The RV time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great most sources (88%) as genuine LPVs, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% consists of candidate ellipsoidal binaries. Quality checks against RVs available in the literature show excellent agreement. We provide illustrative examples and cautionary remarks. The publication of RV time series for almost 10\,000 LPVs constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog (abridged)

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arXiv2023

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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arXiv2023

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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arXiv2023

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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arXiv2022

CUBES: a UV spectrograph for the future

In spite of the advent of extremely large telescopes in the UV/optical/NIR range, the current generation of 8-10m facilities is likely to remain competitive at ground-UV wavelengths for the foreseeable future. The Cassegrain U-Band Efficient Spectrograph (CUBES) has been designed to provide high-efficiency (>40%) observations in the near UV (305-400 nm requirement, 300-420 nm goal) at a spectral resolving power of R>20,000, although a lower-resolution, sky-limited mode of R ~ 7,000 is also planned. CUBES will offer new possibilities in many fields of astrophysics, providing access to key lines of stellar spectra: a tremendous diversity of iron-peak and heavy elements, lighter elements (in particular Beryllium) and light-element molecules (CO, CN, OH), as well as Balmer lines and the Balmer jump (particularly important for young stellar objects). The UV range is also critical in extragalactic studies: the circumgalactic medium of distant galaxies, the contribution of different types of sources to the cosmic UV background, the measurement of H2 and primordial Deuterium in a regime of relatively transparent intergalactic medium, and follow-up of explosive transients. The CUBES project completed a Phase A conceptual design in June 2021 and has now entered the Phase B dedicated to detailed design and construction. First science operations are planned for 2028. In this paper, we briefly describe the CUBES project development and goals, the main science cases, the instrument design and the project organization and management.

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arXiv2022

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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arXiv2022

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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arXiv2022

The Gaia-ESO survey: mapping the shape and evolution of the radial abundance gradients with open clusters

The spatial distribution of elemental abundances and their time evolution are among the major constraints to disentangle the scenarios of formation and evolution of the Galaxy. We used the sample of open clusters available in the final release of the Gaia-ESO survey to trace the Galactic radial abundance and abundance to iron ratio gradients, and their time evolution. We selected member stars in 62 open clusters, with ages from 0.1 to about 7~Gyr, located in the Galactic thin disc at Galactocentric radii from about 6 to 21~kpc. We analysed the shape of the resulting [Fe/H] gradient, the average gradients [El/H] and [El/Fe] combining elements belonging to four different nucleosynthesis channels, and their individual abundance and abundance ratio gradients. We also investigated the time evolution of the gradients dividing open clusters in three age bins. The[Fe/H] gradient has a slope of -0.054 dex~kpc-1. We saw different behaviours for elements belonging to different channels. We found that the youngest clusters in the inner disc have lower metallicity than their older counterpart and they outline a flatter gradient. We considered some possible explanations, including the effects of gas inflow and migration. We suggested that it might be a bias introduced by the standard spectroscopic analysis producing lower metallicities in low gravity stars. To delineate the shape of the `true' gradient, we should limit our analysis to stars with low surface gravity logg>2.5 and xi<1.8 km~s-1. Based on this reduced sample, we can conclude that the gradient has minimally evolved over the time-frame outlined by the open clusters, indicating a slow and stationary formation of the thin disc in the latest Gyr. We found a secondary role of clusters' migration in shaping the gradient, with a more prominent role of migration for the oldest clusters.

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arXiv2022

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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arXiv2022

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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arXiv2022

The Gaia-ESO Public Spectroscopic Survey: Motivation, implementation, GIRAFFE data processing, analysis, and final data products

The Gaia-ESO Public Spectroscopic Survey is an ambitious project designed to obtain astrophysical parameters and elemental abundances for 100,000 stars, including large representative samples of the stellar populations in the Galaxy, and a well-defined sample of 60 (plus 20 archive) open clusters. We provide internally consistent results calibrated on benchmark stars and star clusters, extending across a very wide range of abundances and ages. This provides a legacy data set of intrinsic value, and equally a large wide-ranging dataset that is of value for homogenisation of other and future stellar surveys and Gaia's astrophysical parameters. This article provides an overview of the survey methodology, the scientific aims, and the implementation, including a description of the data processing for the GIRAFFE spectra. A companion paper (arXiv:2206.02901) introduces the survey results. Gaia-ESO aspires to quantify both random and systematic contributions to measurement uncertainties. Thus all available spectroscopic analysis techniques are utilised, each spectrum being analysed by up to several different analysis pipelines, with considerable effort being made to homogenise and calibrate the resulting parameters. We describe here the sequence of activities up to delivery of processed data products to the ESO Science Archive Facility for open use. The Gaia-ESO Survey obtained 202,000 spectra of 115,000 stars using 340 allocated VLT nights between December 2011 and January 2018 from GIRAFFE and UVES. The full consistently reduced final data set of spectra was released through the ESO Science Archive Facility in late 2020, with the full astrophysical parameters sets following in 2022.

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arXiv2022

CUBES, the Cassegrain U-Band Efficient Spectrograph

In the era of Extremely Large Telescopes, the current generation of 8-10m facilities are likely to remain competitive at ground-UV wavelengths for the foreseeable future. The Cassegrain U-Band Efficient Spectrograph (CUBES) has been designed to provide high-efficiency (>40%) observations in the near UV (305-400 nm requirement, 300-420 nm goal) at a spectral resolving power of R>20,000 (with a lower-resolution, sky-limited mode of R ~ 7,000). With the design focusing on maximizing the instrument throughput (ensuring a Signal to Noise Ratio (SNR) ~20 per high-resolution element at 313 nm for U ~18.5 mag objects in 1h of observations), it will offer new possibilities in many fields of astrophysics, providing access to key lines of stellar spectra: a tremendous diversity of iron-peak and heavy elements, lighter elements (in particular Beryllium) and light-element molecules (CO, CN, OH), as well as Balmer lines and the Balmer jump (particularly important for young stellar objects). The UV range is also critical in extragalactic studies: the circumgalactic medium of distant galaxies, the contribution of different types of sources to the cosmic UV background, the measurement of H2 and primordial Deuterium in a regime of relatively transparent intergalactic medium, and follow-up of explosive transients. The CUBES project completed a Phase A conceptual design in June 2021 and has now entered the detailed design and construction phase. First science operations are planned for 2028.

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arXiv2022

The Gaia-ESO survey: placing constraints on the origin of r-process elements

A renewed interest about the origin of \emph{r}-process elements has been stimulated by the multi-messenger observation of the gravitational event GW170817, with the detection of both gravitational waves and electromagnetic waves corresponding to the merger of two neutron stars. Such phenomenon has been proposed as one of the main sources of the \emph{r}-process. However, the origin of the \emph{r}-process elements at different metallicities is still under debate. We aim at investigating the origin of the \emph{r}-process elements in the Galactic thin disc population. From the sixth internal data release of the \emph{Gaia}-ESO we have collected a large sample of Milky Way thin- and thick-disc stars for which abundances of Eu, O, and Mg are available. The sample consists of members of 62 open clusters, located at a Galactocentric radius from $\sim 5$ kpc to $\sim 20$ kpc in the disc, in the metallicity range $[-0.5, 0.4]$ and covering an age interval from 0.1 to 7 Gy, and about 1300 Milky Way disc field stars in the metallicity range $[-1.5, 0.5]$. We compare the observations with the results of a chemical evolution model, in which we varied the nucleosynthesis sources for the three considered elements. Our main result is that Eu in the thin disc is predominantly produced by sources with short lifetimes, such as magneto-rotationally driven SNe. There is no strong evidence for additional sources at delayed times. Our findings do not imply that there cannot be a contribution from mergers of neutron stars in other environments, as in the halo or in dwarf spheroidal galaxies, but such a contribution is not needed to explain Eu abundances at thin disc metallicities.

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arXiv2022

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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arXiv2022

A spectroscopic quadruple as a possible progenitor of sub-Chandrasekhar Type Ia supernovae

Binaries have received much attention as possible progenitors of Type Ia supernova (SNIa) explosions, but long-term gravitational effects in tight triple or quadruple systems could also play a key role in producing SNIa. Here we report on the properties of a spectroscopic quadruple (SB4) found within a star cluster: the 2+2 hierarchical system HD 74438. Its membership in the open cluster IC 2391 makes it the youngest (43 My) SB4 discovered so far and among the quadruple systems with the shortest outer orbital period. The eccentricity of the 6 y outer period is 0.46 and the two inner orbits, with periods of 20.5 d and 4.4 d, and eccentricities of 0.36 and 0.15, are not coplanar. Using an innovative combination of ground-based high resolution spectroscopy and Gaia/Hipparcos astrometry, we show that this system is undergoing secular interaction that likely pumped the eccentricity of one of the inner orbits higher than expected for the spectral types of its components. We compute the future evolution of HD 74438 and show that this system is an excellent candidate progenitor of sub-Chandrasekhar SNIa through white dwarf (WD) mergers. Taking into account the contribution of this specific type of SNIa better accounts for the chemical evolution of iron-peak elements in the Galaxy than considering only near Chandrasekhar-mass SNIa.

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arXiv2022

The Gaia-ESO Survey: Constraining evolutionary models and ages for young low mass stars with measurements of lithium depletion and rotation

A growing disquiet has emerged in recent years that standard stellar models are at odds with observations of the colour-magnitude diagrams (CMDs) and lithium depletion patterns of pre main sequence (PMS) stars in clusters. In this work we select 1,246 high probability K/M-type constituent members of 5 young open clusters (5--125\,Myr) in the Gaia-ESO Survey to test a series of models that use standard input physics and others that incorporate surface magnetic fields or cool starspots. We find that: standard models provide systematically under-luminous isochrones for low-mass stars in the CMD and fail to predict Li-depletion of the right strength at the right colour; magnetic models provide better CMD fits with isochrones that are $\sim 1.5-2$ times older, and provide better matches to Li depletion patterns. We investigate how rotation periods, most of which are determined here for the first time from Transiting Exoplanet Survey Satellite data, correlate with CMD position and Li. Among the K-stars in the older clusters we find the brightest and least Li-depleted are the fastest rotators, demonstrating the classic "Li-rotation connection" for the first time at $\sim 35$ Myr in NGC 2547, and finding some evidence that it exists in the early M-stars of NGC 2264 at $<10\,$Myr. However, the wide dispersion in Li depletion observed in fully-convective M-dwarfs in the $γ$ Vel cluster at $\sim 20$ Myr appears not to be correlated with rotation and is challenging to explain without a very large ($>10$ Myr) age spread.

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arXiv2022

The Gaia-ESO Survey: Chemical tagging in the thin disk. Open clusters blindly recovered in the elemental abundance space

The chemical makeup of a star provides the fossil information of the environment where it formed. Under this premise, it should be possible to use chemical abundances to tag stars that formed within the same stellar association. This idea - known as chemical tagging - has not produced the expected results, especially within the thin disk where open stellar clusters have chemical patterns that are difficult to disentangle. The ultimate goal of this study is to probe the feasibility of chemical tagging within the thin disk population using high-quality data from a controlled sample of stars. We also aim at improving the existing techniques of chemical tagging and giving guidance on different strategies of clustering analysis in the elemental abundance space. Here we develop the first blind search of open clusters' members through clustering analysis in the elemental abundance space using the OPTICS algorithm applied to data from the Gaia-ESO survey. First, we evaluate different strategies of analysis, determining which ones are more performing. Second, we apply these methods to a data set including both field stars and open clusters attempting a blind recover of as many open clusters as possible. We show how specific strategies of data analysis can improve the final results. Specifically, we demonstrate that open clusters can be more efficaciously recovered with the Manhattan metric and on a space whose dimensions are carefully selected. Using these (and other) prescriptions we are able to recover open clusters hidden in our data set and find new members of these stellar associations. Our results indicate that there are chances of recovering open clusters' members via clustering analysis in the elemental abundance space. Presumably, the performances of chemical tagging will further increase with higher quality data and more sophisticated clustering algorithms.

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arXiv2022

The Gaia-ESO Survey: The analysis of the hot-star spectra

The Gaia-ESO Survey (GES) is a large public spectroscopic survey that has collected, over a period of 6 years, spectra of ~ 10^5 stars. This survey provides not only the reduced spectra, but also the stellar parameters and abundances resulting from the analysis of the spectra. The GES dataflow is organised in 19 working groups. Working group 13 (WG13) is responsible for the spectral analysis of the hottest stars (O, B and A type, with a formal cut-off of Teff > 7000 K) that were observed as part of GES. We present the procedures and techniques that have been applied to the reduced spectra, in order to determine the stellar parameters and abundances of these stars. The procedure used is similar to that of other working groups in GES. A number of groups (called `Nodes') each independently analyse the spectra, using their state-of-the-art techniques and codes. Specific for the analysis in WG13 is the large temperature range that is covered (Teff = 7000 - 50,000 K), requiring the use of different analysis codes. Most Nodes can therefore only handle part of the data. Quality checks are applied to the results of these Nodes by comparing them to benchmark stars, and by comparing them one to another. For each star the Node values are then homogenised into a single result: the recommended parameters and abundances. Eight Nodes each analysed (part of) the data. In total 17,693 spectra of 6462 stars were analysed, most of them in 37 open star clusters. The homogenisation led to stellar parameters for 5584 stars. Abundances were determined for a more limited number of stars. Elements studied are He, C, N, O, Ne, Mg, Al, Si and Sc. Abundances for at least one of those elements were determined for 292 stars. The hot-star data analysed here, as well as the Gaia-ESO Survey data in general, will be of considerable use in future studies of stellar evolution and open clusters.

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