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A. Bijaoui

Publications and source records attributed to A. Bijaoui.

At least 19 recordsLinked to original sources

Gaia DR3: Apsis III -- Non-stellar content and source classification

Context. As part of the third Gaia data release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5 deg. Results. Gaia DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 squared degree, where the extinction is evaluated by TGE.

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Stellar ages, masses, extinctions and orbital parameters based on spectroscopic parameters of Gaia DR3

Gaia DR3 provides radial velocities for 33 million stars and spectroscopically derived atmospheric parameters for more than five million targets. When combined with the astrometric data, these allow us to derive orbital and stellar parameters that are key in order to understand the stellar populations of the Milky Way and perform galactic archaeology. We use the calibrated atmospheric parameters, 2MASS and Gaia-EDR3 photometry, and parallax-based distances to compute, via an isochrone fitting method, the ages, initial stellar masses and reddenings for the stars with spectroscopic parameters. We also derive the orbits (actions, eccentricities, apocentre, pericentre and Zmax) for all of the stars with measured radial velocities and astrometry, adopting two sets of line-of-sight distances from the literature and an axisymmetric potential of the Galaxy. Comparisons with reference catalogues of field and cluster stars suggest that reliable ages are obtained for stars younger than 9-10Gyr when the estimated relative age uncertainty is <50%. For older stars, ages tend to be under-estimated. The most reliable stellar type for age determination are turn-off stars, even when the input atmospheric parameters have large uncertainties. Ages for giants and main-sequence stars are retrieved with uncertainties of ~2Gyr when extinction towards the star's line-of sight is smaller than A_V<2.5mag. The full catalogue is made publicly available to be downloaded. With it, the full chemo-dynamical properties of the extended Solar neighbourhood unfold, and allow us to better identify the properties of the spiral arms, to parameterise the dynamical heating of the disc, or to thoroughly study the chemical enrichment of the Milky Way.

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Gaia Data Release 3: Analysis of the Gaia BP/RP spectra using the General Stellar Parameterizer from Photometry

We present the General Stellar Parameterizer from Photometry (GSP-Phot), which is part of the astrophysical parameters inference system (Apsis). GSP-Phot is designed to produce a homogeneous catalogue of parameters for hundreds of millions of single non-variable stars based on their astrometry, photometry, and low-resolution BP/RP spectra. These parameters are effective temperature, surface gravity, metallicity, absolute $M_G$ magnitude, radius, distance, and extinction for each star. GSP-Phot uses a Bayesian forward-modelling approach to simultaneously fit the BP/RP spectrum, parallax, and apparent $G$ magnitude. A major design feature of GSP-Phot is the use of the apparent flux levels of BP/RP spectra to derive, in combination with isochrone models, tight observational constraints on radii and distances. We carefully validate the uncertainty estimates by exploiting repeat Gaia observations of the same source. The data release includes GSP-Phot results for 471 million sources with $G<19$. Typical differences to literature values are 110 K for $T_{\rm eff}$ and 0.2-0.25 for $\log g$, but these depend strongly on data quality. In particular, GSP-Phot results are significantly better for stars with good parallax measurements ($\varpi/σ_varpi>20$), mostly within 2kpc. Metallicity estimates exhibit substantial biases compared to literature values and are only useful at a qualitative level. However, we provide an empirical calibration of our metallicity estimates that largely removes these biases. Extinctions $A_0$ and $A_{\rm BP}$ show typical differences from reference values of 0.07-0.09 mag. MCMC samples of the parameters are also available for 95% of the sources. GSP-Phot provides a homogeneous catalogue of stellar parameters, distances, and extinctions that can be used for various purposes, such as sample selections (OB stars, red giants, solar analogues etc.).

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Gaia Data Release 3: Astrophysical parameters inference system (Apsis) I -- methods and content overview

Gaia Data Release 3 contains a wealth of new data products for the community. Astrophysical parameters are a major component of this release. They were produced by the Astrophysical parameters inference system (Apsis) within the Gaia Data Processing and Analysis Consortium. The aim of this paper is to describe the overall content of the astrophysical parameters in Gaia Data Release 3 and how they were produced. In Apsis we use the mean BP/RP and mean RVS spectra along with astrometry and photometry, and we derive the following parameters: source classification and probabilities for 1.6 billion objects, interstellar medium characterisation and distances for up to 470 million sources, including a 2D total Galactic extinction map, 6 million redshifts of quasar candidates and 1.4 million redshifts of galaxy candidates, along with an analysis of 50 million outlier sources through an unsupervised classification. The astrophysical parameters also include many stellar spectroscopic and evolutionary parameters for up to 470 million sources. These comprise Teff, logg, and m_h (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (up to 5 million), diffuse interstellar band analysis (0.5 million), activity indices (2 million), H-alpha equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). This catalogue is the most extensive homogeneous database of astrophysical parameters to date, and it is based uniquely on Gaia data.

astro-ph.GA

Gaia Data Release 3: Apsis II -- Stellar Parameters

The third Gaia data release contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way. To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly-derived, all-sky catalog of stellar astrophysical parameters (APs): Teff, logg, [M/H], [$α$/Fe], activity index, emission lines, rotation, 13 chemical abundance estimates, radius, age, mass, bolometric luminosity, distance, and dust extinction. We developed the Apsis pipeline to infer APs of Gaia objects by analyzing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against other literature works, including benchmark stars, interferometry, and asteroseismology. Here we assessed the stellar analysis performance from Apsis statistically. We describe the quantities we obtained, including our results' underlying assumptions and limitations. We provide guidance and identify regimes in which our parameters should and should not be used. Despite some limitations, this is the most extensive catalog of uniformly-inferred stellar parameters to date. These comprise Teff, logg, and [M/H] (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (1/2 million), activity indices (2 million), H{$α$} equivalent widths (200 million), and further classification of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS are planned for the next Gaia data release.

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Gaia Data Release 3. Stellar chromospheric activity and mass accretion from Ca II IRT observed by the Radial Velocity Spectrometer

The Gaia Radial Velocity Spectrometer provides the unique opportunity of a spectroscopic analysis of millions of stars at medium-resolution in the near-infrared. This wavelength range includes the Ca II infrared triplet (IRT), which is a good diagnostics of magnetic activity in the chromosphere of late-type stars. Here we present the method devised for inferring the Gaia stellar activity index together with its scientific validation. A sample of well studied PMS stars is considered to identify the regime in which the Gaia stellar activity index may be affected by mass accretion. The position of these stars in the colour-magnitude diagram and the correlation with the amplitude of the photometric rotational modulation is also scrutinised. Three regimes of the chromospheric stellar activity are identified, confirming suggestions made by previous authors on much smaller $R'_{\rm HK}$ datasets. The highest stellar activity regime is associated with PMS stars and RS CVn systems, in which activity is enhanced by tidal interaction. Some evidence of a bimodal distribution in MS stars with $T_{\rm eff}\ge$ 5000 K is also found, which defines the two other regimes, without a clear gap in between. Stars with 3500 K$\le T_{\rm eff} \le$ 5000 K are found to be either very active PMS stars or active MS stars with a unimodal distribution in chromospheric activity. A dramatic change in the activity distribution is found for $T_{\rm eff}\le$3500 K, with a dominance of low activity stars close to the transition between partially- and fully-convective stars and a rise in activity down into the fully-convective regime.

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Gaia Data Release 3: Chemical cartography of the Milky Way

Gaia DR3 opens a new era of all-sky spectral analysis of stellar populations thanks to the nearly 5.6 million stars observed by the RVS and parametrised by the GSP-spec module. The all-sky Gaia chemical cartography allows a powerful and precise chemo-dynamical view of the Milky Way with unprecedented spatial coverage and statistical robustness. First, it reveals the strong vertical symmetry of the Galaxy and the flared structure of the disc. Second, the observed kinematic disturbances of the disc -- seen as phase space correlations -- and kinematic or orbital substructures are associated with chemical patterns that favour stars with enhanced metallicities and lower [alpha/Fe] abundance ratios compared to the median values in the radial distributions. This is detected both for young objects that trace the spiral arms and older populations. Several alpha, iron-peak elements and at least one heavy element trace the thin and thick disc properties in the solar cylinder. Third, young disc stars show a recent chemical impoverishment in several elements. Fourth, the largest chemo-dynamical sample of open clusters analysed so far shows a steepening of the radial metallicity gradient with age, which is also observed in the young field population. Finally, the Gaia chemical data have the required coverage and precision to unveil galaxy accretion debris and heated disc stars on halo orbits through their [alpha/Fe] ratio, and to allow the study of the chemo-dynamical properties of globular clusters. Gaia DR3 chemo-dynamical diagnostics open new horizons before the era of ground-based wide-field spectroscopic surveys. They unveil a complex Milky Way that is the outcome of an eventful evolution, shaping it to the present day (abridged).

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Gaia Data Release 3: Analysis of RVS spectra using the General Stellar Parametriser from spectroscopy

The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. Gaia DR3 contains the parametrisation of RVS data performed by the General Stellar Parametriser-spectroscopy, module. Here we describe the parametrisation of the first 34 months of RVS observations. GSP-spec estimates the chemo-physical parameters from combined RVS spectra of single stars. The main analysis workflow described here, MatisseGauguin, is based on projection and optimisation methods and provides the stellar atmospheric parameters; the individual chemical abundances of N, Mg, Si, S, Ca, Ti, Cr, FeI, FeII, Ni, Zr, Ce and Nd; the differential equivalent width of a cyanogen line; and the parameters of a DIB feature. Another workflow, based on an artificial neural network, provides a second set of atmospheric parameters that are useful for classification control. We implement a detailed quality flag chain considering different error sources. With about 5.6 million stars, the Gaia DR3 GSP-spec all-sky catalogue is the largest compilation of stellar chemo-physical parameters ever published and the first one from space data. Internal and external biases have been studied taking into account the implemented flags. In some cases, simple calibrations with low degree polynomials are suggested. The homogeneity and quality of the estimated parameters enables chemo-dynamical studies of Galactic stellar populations, interstellar extinction studies from individual spectra, and clear constraints on stellar evolution models. We highly recommend that users adopt the provided quality flags for scientific exploitation . The Gaia DR3 GSP-spec catalogue is a major step in the scientific exploration of Milky Way stellar populations, confirming the Gaia promise of a new Galactic vision (abridged).

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The AMBRE Project: Stellar Parameterisation of the ESO:UVES archived spectra

The AMBRE Project is a collaboration between the European Southern Observatory (ESO) and the Observatoire de la Cote d'Azur (OCA) that has been established in order to carry out the determination of stellar atmospheric parameters for the archived spectra of four ESO spectrographs. The analysis of the UVES archived spectra for their stellar parameters has been completed in the third phase of the AMBRE Project. From the complete ESO:UVES archive dataset that was received covering the period 2000 to 2010, 51921 spectra for the six standard setups were analysed. The AMBRE analysis pipeline uses the stellar parameterisation algorithm MATISSE to obtain the stellar atmospheric parameters. The synthetic grid is currently constrained to FGKM stars only. Stellar atmospheric parameters are reported for 12,403 of the 51,921 UVES archived spectra analysed in AMBRE:UVES. This equates to ~23.9% of the sample and ~3,708 stars. Effective temperature, surface gravity, metallicity and alpha element to iron ratio abundances are provided for 10,212 spectra (~19.7%), while at least effective temperature is provided for the remaining 2,191 spectra. Radial velocities are reported for 36,881 (~71.0%) of the analysed archive spectra. Typical external errors of sigmaTeff~110dex, sigmalogg~0.18dex, sigma[M/H]~0.13dex, and sigma[alpha/Fe]~0.05dex with some reported variation between giants and dwarfs and between setups are reported. UVES is used to observe an extensive collection of stellar and non-stellar objects all of which have been included in the archived dataset provided to OCA by ESO. The AMBRE analysis extracts those objects which lie within the FGKM parameter space of the AMBRE slow rotating synthetic spectra grid. Thus by homogeneous blind analysis AMBRE has successfully extracted and parameterised the targeted FGK stars (23.9% of the analysed sample) from within the ESO:UVES archive.

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Stellar parametrization from Gaia RVS spectra

Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as G_RVS~16. A specific stellar parametrization will be performed for most of these RVS spectra. Some individual chemical abundances will also be estimated for the brightest targets. We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-spec working group of the analysis consortium. The tested codes are based on optimization (FERRE and GAUGUIN), projection (MATISSE) or pattern recognition methods (Artificial Neural Networks). We present and discuss their expected performances in the recovered stellar atmospheric parameters (Teff, log(g), [M/H]) for B- to K- type stars. The performances for the determinations of [alpha/Fe] ratios are also presented for cool stars. For all the considered stellar types, stars brighter than G_RVS~12.5 will be very efficiently parametrized by the GSP-spec pipeline, including solid estimations of [alpha/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40K in Teff , 0.1dex in log(g), 0.04dex in [M/H], and 0.03dex in [alpha/Fe] at G_RVS=10.3. Similar accuracies in Teff and [M/H] are found for A-type stars, while the log(g) derivation is more accurate. For the faintest stars, with G_RVS>13-14, a spectrophotometric Teff input will allow the improvement of the final GSP-spec parametrization. The reported results show that the contribution of the RVS based stellar parameters will be unique in the brighter part of the Gaia survey allowing crucial age estimations, and accurate chemical abundances. This will constitute a unique and precious sample for which many pieces of the Milky Way history puzzle will be available, with unprecedented precision and statistical relevance.

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The RAdial Velocity Experiment (RAVE): Fourth data release

We present the stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity), radial velocities, individual abundances and distances determined for 425 561 stars, which constitute the fourth public data release of the RAdial Velocity Experiment (RAVE). The stellar atmospheric parameters are computed using a new pipeline, based on the algorithms of MATISSE and DEGAS. The spectral degeneracies and the 2MASS photometric information are now better taken into consideration, improving the parameter determination compared to the previous RAVE data releases. The individual abundances for six elements (magnesium, aluminum, silicon, titanium, iron and nickel) are also given, based on a special-purpose pipeline which is also improved compared to that available for the RAVE DR3 and Chemical DR1 data releases. Together with photometric information and proper motions, these data can be retrieved from the RAVE collaboration website and the Vizier database.

astro-ph.GA

The Gaia astrophysical parameters inference system (Apsis). Pre-launch description

The Gaia satellite will survey the entire celestial sphere down to 20th magnitude, obtaining astrometry, photometry, and low resolution spectrophotometry on one billion astronomical sources, plus radial velocities for over one hundred million stars. Its main objective is to take a census of the stellar content of our Galaxy, with the goal of revealing its formation and evolution. Gaia's unique feature is the measurement of parallaxes and proper motions with hitherto unparalleled accuracy for many objects. As a survey, the physical properties of most of these objects are unknown. Here we describe the data analysis system put together by the Gaia consortium to classify these objects and to infer their astrophysical properties using the satellite's data. This system covers single stars, (unresolved) binary stars, quasars, and galaxies, all covering a wide parameter space. Multiple methods are used for many types of stars, producing multiple results for the end user according to different models and assumptions. Prior to its application to real Gaia data the accuracy of these methods cannot be assessed definitively. But as an example of the current performance, we can attain internal accuracies (RMS residuals) on F,G,K,M dwarfs and giants at G=15 (V=15-17) for a wide range of metallicites and interstellar extinctions of around 100K in effective temperature (Teff), 0.1mag in extinction (A0), 0.2dex in metallicity ([Fe/H]), and 0.25dex in surface gravity (logg). The accuracy is a strong function of the parameters themselves, varying by a factor of more than two up or down over this parameter range. After its launch in November 2013, Gaia will nominally observe for five years, during which the system we describe will continue to evolve in light of experience with the real data.

astro-ph.IM

The AMBRE Project: Stellar parameterisation of the ESO:FEROS archived spectra

The AMBRE Project is a collaboration between the European Southern Observatory (ESO) and the Observatoire de la Cote d'Azur (OCA) that has been established in order to carry out the determination of stellar atmospheric parameters for the archived spectra of four ESO spectrographs. The analysis of the FEROS archived spectra for their stellar parameters (effective temperatures, surface gravities, global metallicities, alpha element to iron ratios and radial velocities) has been completed in the first phase of the AMBRE Project. From the complete ESO:FEROS archive dataset that was received, a total of 21551 scientific spectra have been identified, covering the period 2005 to 2010. These spectra correspond to ~6285 stars. The determination of the stellar parameters was carried out using the stellar parameterisation algorithm, MATISSE (MATrix Inversion for Spectral SynthEsis), which has been developed at OCA to be used in the analysis of large scale spectroscopic studies in galactic archaeology. An analysis pipeline has been constructed that integrates spectral reduction and radial velocity correction procedures with MATISSE in order to automatically determine the stellar parameters of the FEROS spectra. Stellar atmospheric parameters (Teff, log g, [M/H] and [alpha/Fe]) were determined for 6508 (30.2%) of the FEROS archived spectra (~3087 stars). Radial velocities were determined for 11963 (56%) of the archived spectra. 2370 (11%) spectra could not be analysed within the pipeline. 12673 spectra (58.8%) were analysed in the pipeline but their parameters were discarded based on quality criteria and error analysis determined within the automated process. The majority of these rejected spectra were found to have broad spectral features indicating that they may be hot and/or fast rotating stars, which are not considered within the adopted reference synthetic spectra grid of FGKM stars.

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A spectroscopic survey of thick disc stars outside the solar neighbourhood

We performed a spectroscopic survey of nearly 700 stars probing the galactic thick disc far from the solar neighbourhood towards the galactic coordinates (l~277, b~47). The derived effective temperatures, surface gravities and overall metallicities were then combined with stellar evolution isochrones, radial velocities and proper motions to derive the distances, kinematics and orbital parameters of the sample stars. The targets belonging to each galactic component (thin disc, thick disc, halo) were selected either on their kinematics or according to their position above the galactic plane, and the vertical gradients were also estimated. We present here atmospheric parameters, distances and kinematics for this sample, and a comparison of our kinematic and metallicity distributions with the Besancon model of the Milky Way. The thick disc far from the solar neighbourhood is found to differ only slightly from the thick disc properties as derived in the solar vicinity. For regions where the thick disc dominates, we measured vertical velocity and metallicity trends of d(V_phi)/dZ = 19 +/- 8 km/s/kpc and d[M/H]/dZ = -0.14 +/- 0.05 dex/kpc, respectively. These trends can be explained as a smooth transition between the different galactic components, although intrinsic gradients could not be excluded. In addition, a correlation d(V_phi)/d[M/H] = -45 +/- 12 km/s/dex between the orbital velocity and the metallicity of the thick disc is detected. This gradient is inconsistent with the SDSS photometric survey analysis, which did not detect any such trend, and challenges radial migration models of thick disc formation. Estimations of the scale heights and scale lengths for different metallicity bins of the thick disc result in consistent values, with hR~3.4 \pm 0.7 kpc, and hZ~694 \pm 45 pc, showing no evidence of relics of destroyed massive satellites.

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Automatic stellar spectra parameterisation in the IR CaII triplet region

(Abridged) Galactic archaeology aims to determine the evolution of the Galaxy from the chemical and kinematical properties of its stars. The analysis of current large spectroscopic surveys (thousands of stars) and future ones (millions of stars) require automated analysis techniques to obtain robust estimates of the stellar parameters. Several on-going and planned spectroscopic surveys have selected their wavelength region to contain the IR CaII triplet and this paper focuses on the automatic analysis of such spectra. We investigated two algorithms, MATISSE and DEGAS, both of which compare the observed spectrum to a grid of synthetic spectra, but each uses a different mathematical approach for finding the optimum match and hence the best stellar parameters. We identified degeneracies in different regions of the HR diagram: hot dwarfs and giants share the same spectral signatures. Furthermore, the surface gravity of cooler dwarfs is difficult to determine accurately. These effects are intensified when the information decreases (e.g. metal-poor stars or low SNR spectra). Our results show that the local projection method MATISSE is preferred for high SNR spectra, whereas the decision-tree method DEGAS is preferred for noisier spectra. We therefore propose a hybrid approach of both methods and show that sufficiently accurate results for the purposes of galactic archaeology are retrieved down to SNR~20 for typical thin or thick disc stars, and down to SNR~50 for the more metal-poor halo giants. If unappreciated, degeneracies in stellar parameters can introduce biases in derived quantities for target stars such as distances and full space motions. These biases can be minimised using the knowledge gained by thorough testing of the proposed algorithm, which in turn lead to robust automated methods for the coming extensive stellar spectroscopic surveys in the Local Group.

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Stellar characterization of CoRoT/Exoplanet fields with MATISSE

The homogeneous spectroscopic determination of the stellar parameters is a mandatory step for transit detections from space. Knowledge of which population the planet hosting stars belong to places constraints on the formation and evolution of exoplanetary systems. We used the FLAMES/GIRAFFE multi-fiber instrument at ESO to spectroscopically observe samples of stars in three CoRoT/Exoplanet fields, namely the LRa01, LRc01, and SRc01 fields, and characterize their stellar populations. We present accurate atmospheric parameters, Teff, logg, [M/H], and [$α$/Fe]\ derived for 1227 stars in these fields using the \matisse algorithm. The latter is based on the spectral synthesis methodology and automatically provides stellar parameters for large samples of observed spectra. We trained and applied this algorithm to \flames observations covering the Mg \textsc{i} b spectral range. It was calibrated on reference stars and tested on spectroscopic samples from other studies in the literature. The barycentric radial velocities and an estimate of the Vsini values were measured using cross-correlation techniques. We corrected our samples in the LRc01 and LRa01 CoRoT fields for selection effects to characterize their FGK dwarf stars population, and compiled the first unbiased reference sample for the in-depth study of planet metallicity relationship in these CoRoT fields. We conclude that the FGK dwarf population in these fields mainly exhibit solar metallicity. We show that for transiting planet finding missions, the probability of finding planets as a function of metallicity could explain the number of planets found in the LRa01 and LRc01 CoRoT fields. This study demonstrates the potential of multi-fiber observations combined with an automated classifier such as MATISSE for massive spectral classification.

astro-ph.EP

Parameter Estimation from an Optimal Projection in a Local Environment

The parameter fit from a model grid is limited by our capability to reduce the number of models, taking into account the number of parameters and the non linear variation of the models with the parameters. The Local MultiLinear Regression (LMLR) algorithms allow one to fit linearly the data in a local environment. The MATISSE algorithm, developed in the context of the estimation of stellar parameters from the Gaia RVS spectra, is connected to this class of estimators. A two-steps procedure was introduced. A raw parameter estimation is first done in order to localize the parameter environment. The parameters are then estimated by projection on specific vectors computed for an optimal estimation. The MATISSE method is compared to the estimation using the objective analysis. In this framework, the kernel choice plays an important role. The environment needed for the parameter estimation can result from it. The determination of a first parameter set can be also avoided for this analysis. These procedures based on a local projection can be fruitfully applied to non linear parameter estimation if the number of data sets to be fitted is greater than the number of models.

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Automated derivation of stellar atmospheric parameters and chemical abundances: the MATISSE algorithm

We present an automated procedure for the derivation of atmospheric parameters (Teff, log g, [M/H]) and individual chemical abundances from stellar spectra. The MATrix Inversion for Spectral SythEsis (MATISSE) algorithm determines a basis, B_θ(λ), allowing to derive a particular stellar parameter θby projection of an observed spectrum. The B_θ(λ) function is determined from an optimal linear combination of theoretical spectra and it relates, in a quantitative way, the variations in the spectrum flux with variations in θ. An application of this method to the GAIA/RVS spectral range is described, together with its performances for different types of stars of various metallicities. Blind tests with synthetic spectra of randomly selected parameters and observed input spectra are also presented. The method gives rapid, accurate and stable results and it can be efficiently applied to the study of stellar populations through the analysis of large spectral data sets, including moderate to low signal to noise spectra.

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