Examinando por Autor "Merle, T."

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    The Gaia -ESO Survey: Double-, triple-, and quadruple-line spectroscopic binary candidates
    (EDP Sciences, 2017-12) Merle, T.; Van Eck, S.; Jorissen, A.; Van Der Swaelmen, M.; Masseron, T.; Zwitter, T.; Hatzidimitriou, D.; Klutsch, A.; Pourbaix, D.; Blomme, R.; Worley, C.C.; Sacco, G.; Lewis, J.; Abia, C.; Traven, G.; Sordo, R.; Bragaglia, A.; Smiljanic, R.; Pancino, E.; Damiani, F.; Hourihane, A.; Gilmore, G.; Randich, S.; Koposov, S.; Casey, A.; Morbidelli, L.; Franciosini, E.; Magrini, L.; Jofre, P.; Costado, M.T.; Jeffries, R.D.; Bergemann, M.; Lanzafame, A.C.; Bayo, A.; Carraro, G.; Flaccomio, E.; Monaco, L.; Zaggia, S.
    Context. The Gaia-ESO Survey (GES) is a large spectroscopic survey that provides a unique opportunity to study the distribution of spectroscopic multiple systems among different populations of the Galaxy. Aims. Our aim is to detect binarity/multiplicity for stars targeted by the GES from the analysis of the cross-correlation functions (CCFs) of the GES spectra with spectral templates. Methods. We developed a method based on the computation of the CCF successive derivatives to detect multiple peaks and determine their radial velocities, even when the peaks are strongly blended. The parameters of the detection of extrema (doe) code have been optimized for each GES GIRAFFE and UVES setup to maximize detection. The doe code therefore allows to automatically detect multiple line spectroscopic binaries (SBn, n ≥ 2). Results. We apply this method on the fourth GES internal data release and detect 354 SBn candidates (342 SB2, 11 SB3, and even one SB4), including only nine SBs known in the literature. This implies that about 98% of these SBn candidates are new because of their faint visual magnitude that can reach V = 19. Visual inspection of the SBn candidate spectra reveals that the most probable candidates have indeed a composite spectrum. Among the SB2 candidates, an orbital solution could be computed for two previously unknown binaries: CNAME 06404608+0949173 (known as V642 Mon) in NGC 2264 and CNAME 19013257-0027338 in Berkeley 81 (Be 81). A detailed analysis of the unique SB4 (four peaks in the CCF) reveals that CNAME 08414659-5303449 (HD 74438) in the open cluster IC 2391 is a physically bound stellar quadruple system. The SB candidates belonging to stellar clusters are reviewed in detail to discard false detections. We suggest that atmospheric parameters should not be used for these system components; SB-specific pipelines should be used instead. Conclusions. Our implementation of an automatic detection of spectroscopic binaries within the GES has allowed the efficient discovery of many new multiple systems. With the detection of the SB1 candidates that will be the subject of a forthcoming paper, the study of the statistical and physical properties of the spectroscopic multiple systems will soon be possible for the entire GES sample. © ESO 2017.
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    The Gaia -ESO Survey: Double-, triple-, and quadruple-line spectroscopic binary candidates
    (EDP Sciences, 2017) Merle, T.; Van Eck, S.; Jorissen, A.; Van Der Swaelmen, M.; Masseron, T.; Zwitter, T.; Hatzidimitriou, D.; Klutsch, A.; Pourbaix, D.; Blomme, R.; Worley, C.C.; Sacco, G.; Lewis, J.; Abia, C.; Traven, G.; Sordo, R.; Bragaglia, A.; Smiljanic, R.; Pancino, E.; Damiani, F.; Hourihane, A.; Gilmore, G.; Randich, S.; Koposov, S.; Casey, A.; Morbidelli, L.; Franciosini, E.; Magrini, L.; Jofre, P.; Costado, M.T.; Jeffries, R.D.; Bergemann, M.; Lanzafame, A.C.; Bayo, A.; Carraro, G.; Flaccomio, E.; Monaco, L.; Zaggia, S.
    Context. The Gaia-ESO Survey (GES) is a large spectroscopic survey that provides a unique opportunity to study the distribution of spectroscopic multiple systems among different populations of the Galaxy. Aims. Our aim is to detect binarity/multiplicity for stars targeted by the GES from the analysis of the cross-correlation functions (CCFs) of the GES spectra with spectral templates. Methods. We developed a method based on the computation of the CCF successive derivatives to detect multiple peaks and determine their radial velocities, even when the peaks are strongly blended. The parameters of the detection of extrema (doe) code have been optimized for each GES GIRAFFE and UVES setup to maximize detection. The doe code therefore allows to automatically detect multiple line spectroscopic binaries (SBn, n ≥ 2). Results. We apply this method on the fourth GES internal data release and detect 354 SBn candidates (342 SB2, 11 SB3, and even one SB4), including only nine SBs known in the literature. This implies that about 98% of these SBn candidates are new because of their faint visual magnitude that can reach V = 19. Visual inspection of the SBn candidate spectra reveals that the most probable candidates have indeed a composite spectrum. Among the SB2 candidates, an orbital solution could be computed for two previously unknown binaries: CNAME 06404608+0949173 (known as V642 Mon) in NGC 2264 and CNAME 19013257-0027338 in Berkeley 81 (Be 81). A detailed analysis of the unique SB4 (four peaks in the CCF) reveals that CNAME 08414659-5303449 (HD 74438) in the open cluster IC 2391 is a physically bound stellar quadruple system. The SB candidates belonging to stellar clusters are reviewed in detail to discard false detections. We suggest that atmospheric parameters should not be used for these system components; SB-specific pipelines should be used instead. Conclusions. Our implementation of an automatic detection of spectroscopic binaries within the GES has allowed the efficient discovery of many new multiple systems. With the detection of the SB1 candidates that will be the subject of a forthcoming paper, the study of the statistical and physical properties of the spectroscopic multiple systems will soon be possible for the entire GES sample.
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    The Gaia-ESO Public Spectroscopic Survey: Implementation, data products, open cluster survey, science, and legacy
    (EDP Sciences, 2022-10-01) Randich, S.; Gilmore, G.; Magrini, L.; Sacco, G.G.; Jackson, R.J.; Jeffries, R.D.; Worley, C.C.; Hourihane, A.; Gonneau, A.; Viscasillas Vázquez, C.; Franciosini, E.; Lewis, J.R.; Alfaro, E.J.; Allende Prieto, C.; Bensby, T.; Blomme, R.; Bragaglia, A.; Flaccomio, E.; François, P.; Irwin, M.J.; Koposov, S.E.; Korn, A.J.; Lanzafame, A.C.; Pancino, E.; Recio Blanco, A.; Smiljanic, R.; Van Eck, S.; Zwitter, T.; Asplund, M.; Bonifacio, P.; Feltzing, S.; Binney, J.; Drew, J.; Ferguson, A.M.N.; Micela, G.; Negueruela, I.; Prusti, T.; Rix, H.-W.; Vallenari, A.; Bayo, A.; Bergemann, M.; Biazzo, K.; Carraro, G.; Casey, A.R.; Damiani, F.; Frasca, A.; Heiter, U.; Hill, V.; Jofré, P.; de Laverny, P.; Lind, K.; Marconi, G.; Martayan, C.; Masseron, T.; Monaco, L.; Morbidelli, L.; Prisinzano, L.; Sbordone, L.; Sousa, S.G.; Zaggia, S.; Adibekyan, V.; Bonito, R.; Caffau, E.; Daflon, S.; Feuillet, D.K.; Gebran, M.; González Hernández, J.I.; Guiglion, G.; Herrero, A.; Lobel, A.; Maíz Apellániz, J.; Merle, T.; Mikolaitis, S.; Montes, D.; Morel, T.; Soubiran, C.; Spina, L.; Tabernero, H.M.; Tautvaišiene, G.; Traven, G.; Valentini, M.; Van der Swaelmen, M.; Villanova, S.; Wright, N.J.; Abbas, U.; Aguirre Børsen-Koch, V.; Alves, J.; Balaguer Núnez, L.; Barklem, P.S.; Barrado, D.; Berlanas, S.R.; Binks, A.S.; Bressan, A.; Capuzzo Dolcetta, R.; Casagrande, L.; Casamiquela, L.; Collins, R.S.; D’Orazi, V.; Dantas, M.L.L.; Debattista, V.P.; Delgado Mena, E.; Di Marcantonio, P.; Drazdauskas, A.; Evans, N.W.; Famaey, B.; Franchini, M.; Frémat, Y.; Friel, E.D.; Fu, X.; Geisler, D.; Gerhard, O.; González Solares, E.A.; Grebel, E.K.; Gutiérrez Albarrán, M.L.; Hatzidimitriou, D.; Held, E.V.; Jiménez Esteban, F.; Jönsson, H.; Jordi, C.; Khachaturyants, T.; Kordopatis, G.; Kos, J.; Lagarde, N.; Mahy, L.; Mapelli, M.; Marfil, E.; Martell, S.L.; Messina, S.; Miglio, A.; Minchev, I.; Moitinho, A.; Montalban, J.; Monteiro, M.J.P.F.G.; Morossi, C.; Mowlavi, N.; Mucciarelli, A.; Murphy, D.N.A.; Nardetto, N.; Ortolani, S.; Paletou, F.; Palous, J.; Paunzen, E.; Pickering, J.C.; Quirrenbach, A.; Re Fiorentin, P.; Read, J.I.; Romano, D.; Ryde, N.; Sanna, N.; Santos, W.; Seabroke, G.M.; Spagna, A.; Steinmetz, M.; Stonkuté, E.; Sutorius, E.; Thévenin, F.; Tosi, M.; Tsantaki, M.; Vink, J.S.; Wright, N.; Wyse, R.F.G.; Zoccali, M.; Zorec, J.; Zucker, D.B.; Walton, N.A.
    Context. 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, 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. Aims. 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 reviews the overall survey motivation, strategy, Giraffe pipeline data reduction, organisation, and workflow. Methods. We made use of the information recorded and archived in the observing blocks; during the observing runs; in a number of relevant documents; in the spectra and master catalogue of spectra; in the parameters delivered by the analysis nodes and the working groups; in the final catalogue; and in the science papers. Based on these sources, we critically analyse and discuss the output and products of the Survey, including science highlights. We also determined the average metallicities of the open clusters observed as science targets and of a sample of clusters whose spectra were retrieved from the ESO archive. Results. The Gaia-ESO Survey 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. Conclusions. The final catalogue will be released through the ESO archive in the first half of 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. © ESO 2022.
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    The Gaia-ESO Public Spectroscopic Survey: Motivation, implementation, GIRAFFE data processing, analysis, and final data products?
    (EDP Sciences, 2022-10-01) Gilmore, G.; Randich, S.; Worley, C.C.; Hourihane, A.; Gonneau, A.; Sacco, G.G.; Lewis, J.R.; Magrini, L.; François, P.; Jeffries, R.D.; Koposov, S.E.; Bragaglia, A.; Alfaro, E.J.; Allende Prieto, C.; Blomme, R.; Korn, A.J.; Lanzafame, A.C.; Pancino, E.; Recio Blanco, A.; Smiljanic, R.; Van Eck, S.; Zwitter, T.; Bensby, T.; Flaccomio, E.; Irwin, M.J.; Franciosini, E.; Morbidelli, L.; Damiani, F.; Bonito, R.; Friel, E.D.; Vink, J.S.; Prisinzano, L.; Abbas, U.; Hatzidimitriou, D.; Held, E.V.; Jordi, C.; Paunzen, E.; Spagna, A.; Jackson, R.J.; Maíz Apellániz, J.; Asplund, M.; Bonifacio, P.; Feltzing, S.; Binney, J.; Drew, J.; Ferguson, A.M.N.; Micela, G.; Negueruela, I.; Prusti, T.; Rix, H.-W.; Vallenari, A.; Bergemann, M.; Casey, A.R.; Laverny, P.; Frasca, A.; Hill, V.; Lind, K.; Sbordone, L.; Sousa, S.G.; Adibekyan, V.; Caffau, E.; Daflon, S.; Feuillet, D.K.; Gebran, M.; González Hernández, J.I.; Guiglion, G.; Herrero, A.; Lobel, A.; Merle, T.; Mikolaitis, S.; Montes, D.; Morel, T.; Ruchti, G.; Soubiran, C.; Tabernero, H.M.; Tautvaišiene, G.; Traven, G.; Valentini, M.; Van der Swaelmen, M.; Villanova, S.; Viscasillas Vázquez, C.; Bayo, A.; Biazzo, K.; Carraro, G.; Edvardsson, B.; Heiter, U.; Jofré, P.; Marconi, G.; Martayan, C.; Masseron, T.; Monaco, L.; Walton, N.A.; Zaggia, S.; Aguirre Børsen-Koch, V.; Alves, J.; Balaguer Núnez, L.; Barklem, P.S.; Barrado, D.; Bellazzini, M.; Berlanas, S.R.; Binks, A.S.; Bressan, A.; Capuzzo Dolcetta, R.; Casagrande, L.; Casamiquela, L.; Collins, R.S.; D’Orazi, V.; Dantas, M.L.L.; Debattista, V.P.; Delgado Mena, E.; Marcantonio, P. Di; Drazdauskas, A.; Evans, N.W.; Famaey, B.; Franchini, M.; Frémat, Y.; Fu, X.; Geisler, D.; Gerhard, O.; González Solares, E.A.; Grebel, E.K.; Albarrán Gutiérrez, M.L.; Jiménez Esteban, F.; Jönsson, H.; Khachaturyants, T.; Kordopatis, G.; Kos, J.; Lagarde, N.; Ludwig, H.-G.; Mahy, L.; Mapelli, M.; Marfil, E.; Martell, S.L.; Messina, S.; Miglio, A.; Minchev, I.; Moitinho, A.; Montalban, J.; Monteiro, M.J.P.F.G.; Morossi, C.; Mowlavi, N.; Mucciarelli, A.; Murphy, D.N.A.; Nardetto, N.; Ortolani, S.; Paletou, F.; Palous, J.; Pickering, J.C.; Quirrenbach, A.; Re Fiorentin, P.; Read, J.I.; Romano, D.; Ryde, N.; Sanna, N.; Santos, W.; Seabroke, G.M.; Spina, L.; Steinmetz, M.; Stonkuté, E.; Sutorius, E.; Thévenin, F.; Tosi, M.; Tsantaki, M.; Wright, N.; Wyse, R.F.G.; Zoccali, M.; Zorec, J.; Zucker, D.B.
    Context. 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 the homogenisation of other and future stellar surveys and Gaia’s astrophysical parameters. Aims. 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 introduces the survey results. Methods. 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. Results. 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. Conclusions. 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. A companion article reviews the survey implementation, scientific highlights, the open cluster survey, and data products. © G. Gilmore et al. 2022.