arXiv subjects

Š. Mikolaitis

Publications and source records attributed to Š. Mikolaitis.

At least 19 recordsLinked to original sources

arXiv2026

The non-LTE abundances of magnesium and yttrium and asteroseismic ages for the chemical clock calibration

Building on our previous study, which demonstrated the importance of accounting for departures from local thermodynamic equilibrium (LTE) in elemental-abundance determinations and of using asteroseismic ages, we investigate spatial variations in the empirical [Y/Mg]-age relation across the Galactic disc using a substantially larger stellar sample. We analysed high-resolution stellar spectra and determined Mg and Y abundances through spectral synthesis of multiple spectral features, rigorously accounting for non-LTE (NLTE) effects. We derived asteroseismic ages for stars exhibiting solar-type oscillations and used cross-checked isochrone-based methods for the remaining stars. We determined atmospheric parameters and Mg and Y abundances for 528 Galactic field stars, together with asteroseismic ages for 307 stars and isochronal ages for 221 stars. We also identified two new triple-lined and nine double-lined spectroscopic systems. Combining the present sample with that of our previous study yielded a total of 736 stars, which we used to examine the [Y/Mg]-age relation across the Galactic disc. The relation shows systematic spatial variations that likely reflect differences in star-formation and chemical-enrichment histories. In general, [Y/Mg] tends to increase with metallicity over the investigated age range. At supersolar metallicity, however, this trend may weaken, and the [Y/Mg]-age relations become flatter than those of solar-metallicity stars, which show lower [Y/Mg] values at young ages and higher values at old ages.

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arXiv2026

Calibration of the [C/N] and [Y/Mg] chemical clocks with asteroseismic ages from the TESS space mission

Context. Stellar ages are typically very difficult to estimate for field stars. New empirical methods, based on abundance ratios of chemical elements, are emerging and need to be calibrated. Aims. Our main aim is to contribute to revealing relations between [C/N] and [Y/Mg] ratios and stellar ages by determining astroseismic ages and non-local thermodynamic equilibrium (NLTE) abundances, and accounting for stellar evolutionary stages and birth places in the Galaxy. Methods. We searched for solar pulsations in a sample of 1250 bright F, G, and K giants using data from the TESS space telescope and determined asteroseismic ages using the BASTA and PARAM codes. For the [Y/Mg] relations with age, we determined abundances accounting for deviations from the local thermodynamic equilibrium. For the [C/N] relations with age, we separated stars according to their evolutionary stages. Results. We determined asteroseismic ages for 218 giants and derived [Y/Mg] and [C/N] relations with age for subsamples of stars in three regions of the Galactic thin disc and the thick disc. Conclusions. The [Y/Mg]-age relation exhibits a clear radial dependence across the Galactic disc, with a steeper trend in the outer disc, progressively flatter relations towards the inner disc, and a very flat trend in the thick disc. NLTE abundances of Mg and especially of Y have to be used in order to obtain a more precise stellar age evaluation from [Y/Mg] ratios. When using [C/N] abundance ratios as stellar age indicators, evolutionary stages of stars have to be taken into account.

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arXiv2026

Detection of hot subdwarf binaries and sdB stars using machine learning methods and a large sample of Gaia XP spectra

Hot subdwarfs (hot sds) are compact, evolved stars near the Extreme Horizontal Branch (EHB) and are key to understanding stellar evolution and the ultraviolet excess in galaxies. We extend our previous analysis of Gaia XP spectra of hot subdwarf stars to a much larger sample, enabling a comprehensive study of their physical and binary properties. Our goal is to identify patterns in Gaia XP spectra, investigate binarity, and assess the influence of parameters such as temperature, helium abundance, and variability. We analyse approximately 20000 hot subdwarf candidates selected from the literature, combining Gaia XP data with published parameters. We apply Uniform Manifold Approximation and Projection (UMAP) to the XP coefficients, which represent the Gaia XP spectra in a compact, feature-based form, to construct a similarity map. We then use self-organizing maps (SOMs) and convolutional neural networks (CNNs) to classify spectra as binaries or singles, and as cool and helium-poor or hot and helium-rich. The spectra are normalised using asymmetric least squares baseline fitting to emphasise individual spectral features. The BP-RP colour dominates the similarity map, with additional influence from temperature, helium abundance, and variability. Most binaries, identified via the Virtual Observatory SED Analyser (VOSA), cluster in two filaments linked to main sequence companions. CNN classification suggests a strong correlation between variability and binarity, with binary fractions exceeding 60 percent for active hot subdwarfs. Gaia XP spectra combined with dimensionality reduction and machine learning effectively reveal patterns in hot subdwarf properties. Our findings indicate that binarity and environmental density strongly shape the evolutionary paths of hot subdwarfs, and we identify possible contamination by main sequence and cataclysmic variable stars in the base sample.

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arXiv2025

Carbon and nitrogen as indicators of stellar evolution and age. A homogeneous sample of 44 open clusters from the Gaia-ESO Survey

Context. Low- and intermediate-mass giants undergo a complex chemical evolution that has yet to be observationally probed. The influence of core helium flash on the chemical composition of stellar atmospheres has been an open question since its theoretical prediction 60 years ago. Aims. Based on high-resolution spectral observations of 44 open star clusters in the Gaia-ESO survey, our aim is to perform the first large-scale homogeneous investigation into the carbon and nitrogen photospheric content of low- and intermediate-mass giant stars in different phases of evolution. Methods. We determined carbon and nitrogen abundances using spectral synthesis of the C2 Swan (1,0) band head at 5135 Å and C2 Swan (0,1) band head at 5635.5 Å, 12C14N bands in the interval 6470 - 6490 Å, and the forbidden [O i] line at 6300.31 Å. Results. We revealed differences in C/N abundance ratios between pre- and post-core-He-flash stars. The lower C/N ratios in core He-burning red clump stars are mainly due to the enhancement of nitrogen abundances. We presented calibrations of the relationship between [C/N] and stellar age for solar metallicity low- and intermediate-mass giants taking into account different evolutionary stages. Conclusions. The C/N abundance ratios in the investigated first-ascent giant stars are slightly less affected by the first dredge-up than predicted by the theoretical models. The rotation-induced extra mixing is not as efficient as theoretically predicted. The core helium flash may trigger additional alterations in carbon and nitrogen abundances that are not yet theoretically modelled. We found that the evolutionary stage of stars must be taken into account when using [C/N] as an age indicator.

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arXiv2025

Chemical composition of planetary hosts: II. Abundances of neutron-capture elements

We present a study of neutron-capture element abundances (Sr, Y, Zr, Ba, La, Ce, Nd, Pr, and Eu) in a large and homogeneous sample of 160 F-, G-, and K-type planet-host stars located in the northern hemisphere, including 32 stars in multi-planetary systems. The sample hosts a total of 175 high-mass planets and 47 Neptunian and super-Earth planets. High-resolution spectra were obtained with the 1.65-metre telescope at the Molėtai Astronomical Observatory using a fibre-fed spectrograph covering 4000-8500 Å. Elemental abundances were determined by differential line-by-line spectrum synthesis with the TURBOSPECTRUM code and MARCS model atmospheres. The analysis of $[\mathrm{El}/\mathrm{Fe}]$ ratios shows that most elements in PHSs follow the Galactic chemical evolution, but $[\mathrm{Zr}/\mathrm{Fe}]$, $[\mathrm{La}/\mathrm{Fe}]$, and $[\mathrm{Ce}/\mathrm{Fe}]$ are overabundant in PHSs relative to reference stars at a given $[\mathrm{Fe}/\mathrm{H}]$. Correlations between $[\mathrm{El}/\mathrm{Fe}]$ and planet mass are generally positive, except for Sr, Y, and Ba, which show no significant trends. The distribution of $Δ[\mathrm{El}/\mathrm{H}]$ versus condensation temperature ($T_{\mathrm{cond}}$) slopes is positively skewed for PHSs, indicating enrichment in refractory elements compared to analogues. While no strong correlations are found between $Δ[\mathrm{El}/\mathrm{H}]$-$T_{\mathrm{cond}}$ slopes and stellar or planetary parameters, older dwarf stars with multiple planets tend to have smaller or negative slopes, whereas younger dwarf stars exhibit larger positive slopes. Our results also confirm that multi-planetary systems are more frequent around metal-rich stars.

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arXiv2024

Chemical composition of planetary hosts: C, N, and $α$-element abundances

Accurate atmospheric parameters and chemical composition of planet-hosting stars are crucial for characterising exoplanets and understanding their formation and evolution. Our objective is to uniformly determine the atmospheric parameters and chemical abundances of carbon, nitrogen, oxygen, and the $α$-elements, magnesium and silicon, along with C/O, N/O and Mg/Si abundance ratios in planet-hosts. We aim to investigate the potential links between stellar chemistry and the presence of planets using high-resolution spectra of 149 F, G, and K dwarf and giant stars hosting planets or planetary systems. The spectra were obtained with the Vilnius University Echelle Spectrograph on the 1.65 m Molėtai Observatory telescope. Stellar parameters were determined through standard analysis using equivalent widths and one-dimensional, plane-parallel model atmospheres calculated under the assumption of local thermodynamical equilibrium. The differential synthetic spectrum method was used to uniformly determine carbon C(C2), nitrogen N(CN), oxygen [O I], magnesium Mg I, and silicon Si I elemental abundances as well as the C/O, N/O, and Mg/Si ratios. We found that [C/Fe], [O/Fe], and [Mg/Fe] are lower in metal-rich dwarf hosts; whereas [N/Fe] is close to the Solar ratio. Giants show smaller scatter in [C/Fe] and [O/Fe] and lower than the Solar average [C/Fe] and C/O ratios. The (C+N+O) abundances increase with [Fe/H] in giant stars, with a minimal scatter. We also noted an overabundance of Mg and Si in planet hosting stars, particularly at lower metallicities, and a lower Mg/Si ratio in stars with planets. In giants hosting high-mass planets, nitrogen shows a moderate positive relationship with planet mass. C/O and N/O ratios show moderate negative and positive slopes in giant stars, respectively. The Mg/Si ratio shows a negative correlation with planet mass across the entire stellar sample.

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arXiv2024

Advanced Classification of Hot Subdwarf Binaries Using Artificial Intelligence Techniques and Gaia DR3 data

Hot subdwarfs are compact blue evolved objects, burning helium in their cores surrounded by a tiny hydrogen envelope. Most models agree on a common envelope binary evolution scenario in the Red Giant phase. However, the binarity rate for these objects is yet unsolved. We aim to develop a novel classification method for identifying hot subdwarf binaries within large datasets using Artificial Intelligence methods and Gaia DR3 data. The results will be compared with those obtained previously using VOSA (Virtual Observatory Sed Analyzer) on coincident samples. The methods include several machine learning techniques. We used Support Vector Machines (SVM) to classify 3084 hot subdwarf stars based on their color-magnitude properties. Of these, 2815 objects have Gaia Data Release 3 BP/RP spectra, which were classified using Self-Organizing Maps (SOM) and Convolutional Neural Networks (CNN). The findings demonstrate a high agreement level (70-90%) with VOSA's classification, indicating that machine learning methods effectively classify sources with an accuracy comparable to human inspection or non-AI techniques. SVM in a radial basis function achieves 70.97% reproducibility for binary targets using photometry. CNN reaches 84.94% for binary detection using spectroscopy. We also found that the single-binary differences are especially observable on the infrared flux in our GDR3 BP/BR spectra, at wavelengths larger than 700 nm. We found that all our methods are effective in discerning between single and binary systems and are consistent with the results previously obtained with VOSA. In global terms, considering all quality metrics, CNN is the method that provides the best accuracy. The methods are also effective for detecting peculiarities in the spectra. Further research is needed to refine our techniques and enhance automated classification reliability, especially for large-scale surveys.

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arXiv2024

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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arXiv2023

Beyond Gaia DR3: Tracing the [$α$/M]-[M/H] bimodality from the inner to the outer Milky Way disc with Gaia-RVS and convolutional neural networks

In June 2022, Gaia DR3 has provided the astronomy community with about one million spectra from the Radial Velocity Spectrometer (RVS) covering the CaII triplet region. However, one-third of the published spectra have 15<S/N<25 per pixel such that they pose problems for classical spectral analysis pipelines, and therefore, alternative ways to tap into these large datasets need to be devised. We aim to leverage the versatility and capabilities of machine learning techniques for supercharged stellar parametrisation by combining Gaia-RVS spectra with the full set of Gaia products and high-resolution, high-quality ground-based spectroscopic reference datasets. We developed a hybrid convolutional neural network (CNN) that combines the Gaia DR3 RVS spectra, photometry (G, G_BP, G_RP), parallaxes, and XP coefficients to derive atmospheric parameters (Teff, log(g) as well as overall [M/H]) and chemical abundances ([Fe/H] and [α/M]). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels. With this CNN, we derived homogeneous atmospheric parameters and abundances for 886080 RVS stars that show remarkable precision and accuracy compared to external datasets (such as GALAH and asteroseismology). The CNN is robust against noise in the RVS data, and we derive very precise labels down to S/N=15. We managed to characterise the [α/M]-[M/H] bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets. This work is the first to combine machine learning with such diverse datasets and paves the way for large-scale machine learning analysis of Gaia-RVS spectra from future data releases. Large, high-quality datasets can be optimally combined thanks to the CNN, thereby realising the full power of spectroscopy, astrometry, and photometry.

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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

Chemical Composition Of Bright Stars In The Northern Hemisphere: Star-Planet Connection

In fulfilling the aims of the planetary and asteroseismic research missions, such as that of the NASA Transiting Exoplanet Survey Satellite (TESS) space telescope, accurate stellar atmospheric parameters and a detailed chemical composition are required as input. We have observed high-resolution spectra for all 848 bright (V<8 mag) stars that are cooler than F5 spectral class in the area up to 12 deg surrounding the northern TESS continuous viewing zone and uniformly determined the main atmospheric parameters, ages, orbital parameters, velocity components, and precise abundances of up to 24 chemical species (C(C2), N(CN), [O I], Na I, Mg I, Al I, Si I, Si I, Ca I, Ca II, Sc I, Sc II, Ti I, Ti II, V I, Cr I, Cr II, Mn I, Fe I, Fe II, Co I, Ni I, Cu I, and Zn I) for 740 slowly rotating stars. The analysis of 25 planet-hosting stars in our sample drove us to the following conclusions: the dwarf stars hosting high-mass planets are more metal rich than those with low-mass planets. We find slightly negative C/O and Mg/Si slopes toward the stars with high-mass planets. All the low-mass planet hosts in our sample show positive $Δ$[El/Fe] versus condensation temperature slopes, in particular, the star with the large number of various planets. The high-mass planet hosts have a diversity of slopes, but in more metal rich, older, and cooler stars, the positive elemental abundance slopes are more common.

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arXiv2022

The Gaia-ESO Survey: Age-chemical-clock relations spatially resolved in the Galactic disc

The last decade has seen a revolution in our knowledge of the Galaxy thanks to the Gaia and asteroseismic space missions and the ground-based spectroscopic surveys. To complete this picture, it is necessary to map the ages of its stellar populations. During recent years, the dependence on time of abundance ratios involving slow (s) neutron-capture and $α$ elements (called chemical-clocks) has been used to provide estimates of stellar ages, usually in a limited volume close to the Sun. We aim to analyse the relations of chemical clocks in the Galactic disc extending the range to R$_{\rm GC}\sim$6-20~kpc. Using the sixth internal data release of the Gaia-ESO survey, we calibrated several relations between stellar ages and abundance ratios [s/$α$] using a sample of open clusters, the largest one so far used with this aim. Thanks to their wide galactocentric coverage, we investigated the radial variations of the shape of these relations, confirming their non-universality. We estimated our accuracy and precision in recovering the global ages of open clusters, and the ages of their individual members. We applied the multi-variate relations with the highest correlation coefficients to the field star population. We confirm that there is no single age-chemical clock relationship valid for the whole disc, but that there is a dependence on the galactocentric position, which is related to the radial variation of the star formation history combined with the non-monotonic dependence on metallicity of the yields of the s-process elements from low- and intermediate-mass stars. Finally, the abundance ratios [Ba/$α$] are more sensitive to age than those with [Y/$α$] for young disc stars, and their slopes vary less with galactocentric distance.

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arXiv2020

Properties of the Hyades, the eclipsing binary HD27130, and the oscillating red giant $ε$ Tau

Eclipsing binary stars allow derivation of accurate and precise masses and radii. When they reside in star clusters, properties of even higher precision, along with additional information, can be extracted. Asteroseismology of solar-like oscillations offers similar possibilities for single stars. We improve the previously established properties of the Hyades eclipsing binary HD27130 and re-assess the asteroseismic properties of the giant star $ε$ Tau. The physical properties of these members of the Hyades are then used to constrain the helium content and age of the cluster. New multi-colour light curves were combined with multi-epoch radial velocities to yield masses and radii of HD27130. $T_{\rm eff}$ was derived from spectroscopy and photometry, and verified using the Gaia parallax. We estimate the cluster age from re-evaluated asteroseismic properties of $ε$ Tau while using HD27130 to constrain the helium content. The masses and radii, and $T_{\rm eff}$ of HD 27130 were found to be $M=1.0245\pm0.0024 M_{\odot}$, $R=0.9226\pm0.015 R_{\odot}$, $T_{\rm eff}=5650\pm50$ K for the primary, and $M=0.7426\pm0.0016 M_{\odot}$, $R=0.7388\pm0.026 R_{\odot}$, $T_{\rm eff}=4300\pm100$ K for the secondary component. Our re-evaluation of $ε$ Tau suggests that the previous literature estimates are trustworthy, and that the Hipparcos parallax is more reliable than the Gaia DR2 parallax. The helium content of HD27130 and thus of the Hyades is found to be $Y=0.27$ but with significant model dependence. Correlations with the adopted metallicity results in a robust helium enrichment law with $\frac{ΔY}{ΔZ}$ close to 1.2. We estimate the age of the Hyades to be 0.9 $\pm$ 0.1 (stat) $\pm$ 0.1 (sys) Gyr in slight tension with recent age estimates based on the cluster white dwarfs. (abridged)

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arXiv2020

Chemical Composition of Bright Stars in the Continuous Viewing Zone of the TESS Space Mission

Accurate atmospheric parameters and chemical composition of stars play a vital role in characterizing physical parameters of exoplanetary systems and understanding of their formation. A full asteroseismic characterization of a star is also possible if its main atmospheric parameters are known. The NASA Transiting Exoplanet Survey Satellite (TESS) space telescope will play a very important role in searching of exoplanets around bright stars and stellar asteroseismic variability research. We have observed all 302 bright (V < 8 mag) and cooler than F5 spectral class stars in the northern TESS continuous viewing zone with a 1.65 m telescope at the Moletai Astronomical Observatory of Vilnius University and the high-resolution Vilnius University Echelle Spectrograph. We uniformly determined the main atmospheric parameters, ages, orbital parameters, velocity components, and precise abundances of 24 chemical species ( C(C2), N(CN), [O I], Na I, Mg I, Al I, Si I, Si II, Ca I, Ca II, Sc I, Sc II, Ti I, Ti II, V I, Cr I, Cr II, Mn I, Fe I, Fe II, Co I, Ni I, Cu I, and Zn I) for 277 slowly rotating single stars in the field. About 83 % of the sample stars exhibit the Mg/Si ratios greater than 1.0 and may potentially harbor rocky planets in their systems.

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arXiv2019

Search for variable stars in the northern sky:Analysis of photometric time series for 3598 stars

As extensive ground-based observations and characterisation of different variable stars are of the utmost importance in preparing optimal input catalogues for space missions, our aim was to search for new variable stars in selected fields of the northern sky. We obtained 24470 CCD images and analysed photometric time series of stars using the DAOPHOT based package Muniwin as the first step, and the Period04 package was used to further analyse the suspected new variable stars. The light curves and other observational results are presented for 3598 stars online. We found 81 new variable stars, among them is an eclipsing binary with a variable component and possibly eccentric orbits TYC4038-693-1 which we also observed spectroscopically, four δ Scuti candidates, six other variable stars with periods falling into the interval of 35 minutes to 20 days. Furthermore, we identified 70 slowly varying stars with so far undefined periodicity. Additional photometric and spectral observations were carried out for TYC 2764-1997-1, and its previous candidacy for eclipsing binaries was approved.

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arXiv2018

The Gaia-ESO survey: impact of extra-mixing on C- and N-abundances of giant stars

The GES survey using FLAMES at the VLT has obtained high-resolution UVES spectra for a large number of giant stars, allowing a determination of the abundances of the key chemical elements C and N at their surface. The surface abundances of these chemical species are well-known to change in stars during their evolution on the red giant branch after the first dredge-up episod, as a result of extra-mixing phenomena. We investigate the effects of thermohaline mixing on C and N abundances using the first comparison between the GES [C/N] determinations with simulations of the observed fields using a model of stellar population synthesis. We explore the effects of thermohaline mixing on the chemical properties of giants through stellar evolutionary models computed with the stellar evolution code STAREVOL. We include these stellar evolution models in the Besançon Galaxy model to simulate the [C/N] distributions determined from the UVES spectra of the GES and compare them with the observations. Theoretical predictions including the effect of thermohaline mixing are in good agreement with the observations. However, the field stars in the GES with C and N-abundance measurements have a metallicity close to solar, where the efficiency of thermohaline mixing is not very large. The C and N abundances derived by the GES in open and globular clusters clearly show the impact of thermohaline mixing at low-metallicity, allowing to explain the [C/N] ratio observed in lower-mass and older giant stars. Using independent observations of carbon isotopic ratio in clump field stars and open clusters, we also confirm that thermohaline mixing should be taken into account to explain the behavior of 12C/13C ratio as a function of stellar age. Overall the current model including thermohaline mixing is able to reproduce very well the C- and N-abundances over the whole metallicity range investigated by the GES data.

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arXiv2017

The AMBRE project: Iron-peak elements in the solar neighbourhood

The aim of this paper is to characterise the abundance patterns of five iron-peak elements (Mn, Fe, Ni, Cu, and Zn) for which the stellar origin and chemical evolution are still debated. We automatically derived iron peak (Mn, Fe, Ni, Cu, and Zn) and alpha element (Mg) chemical abundances for 4666 stars. We used the bimodal distribution of [Mg/Fe] to chemically classify sample stars into different Galactic substructures: thin disc, metal-poor and high-alpha metal rich, high-alpha and low-alpha metal-poor populations. High-alpha and low-alpha metal-poor populations are fully distinct in Mg, Cu, and Zn. Thin disc trends of [Ni/Fe] and [Cu/Fe] are very similar and show a small increase at supersolar metallicities. Thin and thick disc trends of Ni and Cu are very similar and indistinguishable. Mn looks different from Ni and Cu. [Mn/Fe] trends of thin and thick discs actually have noticeable differences: the thin disc is slightly Mn richer than the thick disc. [Zn/Fe] trends look very similar to those of [alpha/Fe] trends. The dispersion of results in both discs is low (approx 0.05 dex for [Mg, Mn, and Cu/Fe]) and is even much lower for [Ni/Fe] (approx 0.035 dex). Zn is an alpha-like element and could be used to separate thin and thick disc stars. [Mn/Mg] ratio could also be a very good tool for tagging Galactic substructures. Some models can partially reproduce the observed Mg, Zn, and, Cu behaviours. Models mostly fail to reproduce Mn and Ni in all metallicity domains, however, models adopting yields normalised from solar chemical properties reproduce Mn and Ni better, suggesting that there is still a lack of realistic theoretical yields of some iron-peak elements. Very low scatter (approx 0.05 dex) in thin and thick disc sequences could provide an observational constrain for Galactic evolutionary models that study the efficiency of stellar radial migration.

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arXiv2017

The AMBRE Project: chemical evolution models for the Milky Way thick and thin discs

We study the chemical evolution of the thick and thin discs of the Galaxy by comparing detailed chemical evolution models with recent data from the AMBRE Project. The data suggest that the stars in the thick and thin discs form two distinct sequences with the thick disc stars showing higher [α/Fe] ratios. We adopt two different approaches to model the evolution of thick and thin discs. In particular, we adopt: i) a two-infall approach where the thick disc forms fast and before the thin disc and by means of a fast gas accretion episode, whereas the thin disc forms by means of a second accretion episode on a longer timescale; ii) a parallel approach, where the two discs form in parallel but at different rates. By comparing our model results with the observed [Mg/Fe] vs. [Fe/H] and the metallicity distribution functions in the two Galactic components, we conclude that the parallel approach can account for a group of α-enhanced metal rich stars present in the data, whereas the two-infall approach cannot explain these stars unless they are the result of stellar migration. In both approaches, the thick disc has formed on a timescale of accretion of 0.1 Gyr, whereas the thin disc formed on a timescale of 7 Gyr in the solar region. In the two-infall approach a gap in star formation between the thick and thin disc formation of several hundreds of Myr should be present, at variance with the parallel approach where no gap is present.

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