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    The Gaia -ESO Survey: Lithium measurements and new curves of growth
    (Les Ulis : EDP Sciences, 2022) Franciosini, E.; Randich, S.; de Laverny, P.; Biazzo, K.; Feuillet, D.K.; Frasca, A.; Lind, K.; Prisinzano, L.; Tautvaišiene, G.; Lanzafame, A.C.; Smiljanic, R.; Gonneau, A.; Magrini, L.; Pancino, E.; Guiglion, G.; Sacco, G.G.; Sanna, N.; Gilmore, G.; Bonifacio, P.; Jeffries, R.D.; Micela, G.; Prusti, T.; Alfaro, E.J.; Bensby, T.; Bragaglia, A.; François, P.; Korn, A.J.; Van Eck, S.; Bayo, A.; Bergemann, M.; Carraro, G.; Heiter, U.; Hourihane, A.; Jofré, P.; Lewis, J.; Martayan, C.; Monaco, L.; Morbidelli, L.; Worley, C.C.; Zaggia, S.
    Context. 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. Aims. In this paper, we describe the method adopted in the final data release to derive lithium equivalent widths (EWs) and abundances. Methods. 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. Results. 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. Conclusions. 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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    Gaia Data Release 2 : Processing the spectroscopic data
    (Les Ulis : EDP Sciences, 2018) Sartoretti, P.; Katz, D.; Cropper, M.; Panuzzo, P.; Seabroke, G. M.; Viala, Y.; Benson, K.; Blomme, R.; Jasniewicz, G.; Jean-Antoine, A.; Huckle, H.; Smith, M.; Baker, S.; Crifo, F.; Damerdji, Y.; David, M.; Dolding, C.; Frémat, Y.; Gosset, E.; Guerrier, A.; Guy, L. P.; Haigron, R.; Janßen, K.; Marchal, O.; Plum, G.; Soubiran, C.; Thévenin, F.; Ajaj, M.; Allende Prieto, C.; Babusiaux, C.; Boudreault, S.; Chemin, L.; Delle Luche, C.; Fabre, C.; Gueguen, A.; Hambly, N. C.; Lasne, Y.; Meynadier, F.; Pailler, F.; Panem, C.; Riclet, F.; Royer, F.; Tauran, G.; Zurbach, C.; Zwitter, T.; Arenou, F.; Gomez, A.; Lemaitre, V.; Leclerc, N.; Morel, T.; Munari, U.; Turon, C.; Žerjal, M.
    Context. The Gaia Data Release 2 (DR2 ) contains the first release of radial velocities complementing the kinematic data of a sample of about 7 million relatively bright, late-type stars. Aims. This paper provides a detailed description of the Gaia spectroscopic data processing pipeline, and of the approach adopted to derive the radial velocities presented in DR2 . Methods. The pipeline must perform four main tasks: (i) clean and reduce the spectra observed with the Radial Velocity Spectrometer (RVS); (ii) calibrate the RVS instrument, including wavelength, straylight, line-spread function, bias non-uniformity, and photometric zeropoint; (iii) extract the radial velocities; and (iv) verify the accuracy and precision of the results. The radial velocity of a star is obtained through a fit of the RVS spectrum relative to an appropriate synthetic template spectrum. An additional task of the spectroscopic pipeline was to provide first-order estimates of the stellar atmospheric parameters required to select such template spectra. We describe the pipeline features and present the detailed calibration algorithms and software solutions we used to produce the radial velocities published in DR2 . Results. The spectroscopic processing pipeline produced median radial velocities for Gaia stars with narrow-band near-IR magnitude GRVS ≤ 12 (i.e. brighter than V ∼ 13). Stars identified as double-lined spectroscopic binaries were removed from the pipeline, while variable stars, single-lined, and non-detected double-lined spectroscopic binaries were treated as single stars. The scatter in radial velocity among different observations of a same star, also published in Gaia DR2, provides information about radial velocity variability. For the hottest (Te≥ 7000 K) and coolest (Te≤ 3500 K) stars, the accuracy and precision of the stellar parameter estimates are not sufficient to allow selection of appropriate templates. The radial velocities obtained for these stars were removed from DR2 . The pipeline also provides a first-order estimate of the performance obtained. The overall accuracy of radial velocity measurements is around ∼200-300 m s-1, and the overall precision is ∼1 km s-1; it reaches ∼200 m s-1 for the brightest stars.
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    Synthetic simulations of the extragalactic sky seen by eROSITA : I. Pre-launch selection functions from Monte-Carlo simulations
    (Les Ulis : EDP Sciences, 2018) Clerc, N.; Ramos-Ceja, M.E.; Ridl, J.; Lamer, G.; Brunner, H.; Hofmann, F.; Comparat, J.; Pacaud, F.; Käfer, F.; Reiprich, T.H.; Merloni, A.; Schmid, C.; Brand, T.; Wilms, J.; Friedrich, P.; Finoguenov, A.; Dauser, T.; Kreykenbohm, I.
    Context. Studies of galaxy clusters provide stringent constraints on models of structure formation. Provided that selection effects are under control, large X-ray surveys are well suited to derive cosmological parameters, in particular those governing the dark energy equation of state. Aims. We forecast the capabilities of the all-sky eROSITA (extended ROentgen Survey with an Imaging Telescope Array) survey to be achieved by the early 2020s. We bring special attention to modelling the entire chain from photon emission to source detection and cataloguing. Methods. The selection function of galaxy clusters for the upcoming eROSITA mission is investigated by means of extensive and dedicated Monte-Carlo simulations. Employing a combination of accurate instrument characterisation and a state-of-the-art source detection technique, we determine a cluster detection efficiency based on the cluster fluxes and sizes. Results. Using this eROSITA cluster selection function, we find that eROSITA will detect a total of approximately 105 clusters in the extra-galactic sky. This number of clusters will allow eROSITA to put stringent constraints on cosmological models. We show that incomplete assumptions on selection effects, such as neglecting the distribution of cluster sizes, induce a bias in the derived value of cosmological parameters. Conclusions. Synthetic simulations of the eROSITA sky capture the essential characteristics impacting the next-generation galaxy cluster surveys and they highlight parameters requiring tight monitoring in order to avoid biases in cosmological analyses.