Examinando por Autor "Ludwig, H.-G."
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Ítem 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.Ítem TOPoS: II. on the bimodality of carbon abundance in CEMP stars Implications on the early chemical evolution of galaxies(EDP Sciences, 2015-07) Bonifacio, P.; Caffau, E.; Spite, M.; Limongi, M.; Chieffi, A.; Klessen, R.S.; François, P.; Molaro, P.; Ludwig, H.-G.; Zaggia, S.; Spite, F.; Plez, B.; Cayrel, R.; Christlieb, N.; Clark, P.C.; Glover, S.C.O.; Hammer, F.; Koch, A.; Monaco, L.; Sbordone, L.; Steffen, M.In the course of the Turn Off Primordial Stars (TOPoS) survey, aimed at discovering the lowest metallicity stars, we have found several carbon-enhanced metal-poor (CEMP) stars. These stars are very common among the stars of extremely low metallicity and provide important clues to the star formation processes. We here present our analysis of six CEMP stars. Aims. We want to provide the most complete chemical inventory for these six stars in order to constrain the nucleosynthesis processes responsible for the abundance patterns. Methods. We analyse both X-Shooter and UVES spectra acquired at the VLT. We used a traditional abundance analysis based on OSMARCS 1D local thermodynamic equilibrium (LTE) model atmospheres and the turbospectrum line formation code. Results. Calcium and carbon are the only elements that can be measured in all six stars. The range is-5.0 ≤ [Ca/H] <-2.1 and 7.12 ≤ A(C) ≤ 8.65. For star SDSS J1742+2531 we were able to detect three Fe i lines from which we deduced [Fe/H] =-4.80, from four Ca ii lines we derived [Ca/H] =-4.56, and from synthesis of the G-band we derived A(C) = 7.26. For SDSS J1035+0641 we were not able to detect any iron lines, yet we could place a robust (3σ) upper limit of [Fe/H] <-5.0 and measure the Ca abundance, with [Ca/H] =-5.0, and carbon, A(C) = 6.90, suggesting that this star could be even more metal-poor than SDSS J1742+2531. This makes these two stars the seventh and eighth stars known so far with [Fe/H] <-4.5, usually termed ultra-iron-poor (UIP) stars. No lithium is detected in the spectrum of SDSS J1742+2531 or SDSS J1035+0641, which implies a robust upper limit of A(Li) < 1.8 for both stars. Conclusions. Our measured carbon abundances confirm the bimodal distribution of carbon in CEMP stars, identifying a high-carbon band and a low-carbon band. We propose an interpretation of this bimodality according to which the stars on the high-carbon band are the result of mass transfer from an AGB companion, while the stars on the low-carbon band are genuine fossil records of a gas cloud that has also been enriched by a faint supernova (SN) providing carbon and the lighter elements. The abundance pattern of the UIP stars shows a large star-to-star scatter in the [X/Ca] ratios for all elements up to aluminium (up to 1 dex), but this scatter drops for heavier elements and is at most of the order of a factor of two. We propose that this can be explained if these stars are formed from gas that has been chemically enriched by several SNe, that produce the roughly constant [X/Ca] ratios for the heavier elements, and in some cases the gas has also been polluted by the ejecta of a faint SN that contributes the lighter elements in variable amounts. The absence of lithium in four of the five known unevolved UIP stars can be explained by a dominant role of fragmentation in the formation of these stars. This would result either in a destruction of lithium in the pre-main-sequence phase, through rotational mixing or to a lack of late accretion from a reservoir of fresh gas. The phenomenon should have varying degrees of efficiency. © 2015 ESO.Ítem TOPoS: III. An ultra iron-poor multiple CEMP system ?(EDP Sciences, 2016-11) Caffau, E.; Bonifacio, P.; Spite, M.; Spite, F.; Monaco, L.; Sbordone, L.; François, P.; Gallagher, A.J.; Plez, B.; Zaggia, S.; Ludwig, H.-G.; Cayrel, R.; Koch, A.; Steffen, M.; Salvadori, S.; Klessen, R.; Glover, S.; Christlieb, N.Aims. One of the primary objectives of the TOPoS survey is to search for the most metal-poor stars. Our search has led to the discovery of one of the most iron-poor objects known, SDSS J092912.32+023817.0. This object is a multiple system, in which two components are clearly detected in the spectrum. Methods. We have analysed 16 high-resolution spectra obtained using the UVES spectrograph at the ESO 8.2 m VLT telescope to measure radial velocities and determine the chemical composition of the system. Results. Cross correlation of the spectra with a synthetic template yields a double-peaked cross-correlation function (CCF) for eight spectra, and in one case there is evidence for the presence of a third peak. Chemical analysis of the spectrum obtained by averaging all the spectra for which the CCF showed a single peak found that the iron abundance is [Fe/H] = −4.97. The system is also carbon enhanced with [C/Fe] = +3.91 (A(C) = 7.44). From the permitted oxygen triplet we determined an upper limit for oxygen of [O/Fe] < +3.52 such that C/O > 1.3. We are also able to provide more stringent upper limits on the Sr and Ba abundances ([Sr/Fe] < +0.70, and [Ba/Fe] < +1.46, respectively).Ítem TOPoS: IV. Chemical abundances from high-resolution observations of seven extremely metal-poor stars(EDP Sciences, 2018-04) Bonifacio, P.; Caffau, E.; Spite, M.; Spite, F.; Sbordone, L.; Monaco, L.; François, P.; Plez, B.; Molaro, P.; Gallagher, A.J.; Cayrel, R.; Christlieb, N.; Klessen, R.S.; Koch, A.; Ludwig, H.-G.; Steffen, M.; Zaggia, S.; Abate, C.Context. Extremely metal-poor (EMP) stars provide us with indirect information on the first generations of massive stars. The TOPoS survey has been designed to increase the census of these stars and to provide a chemical inventory that is as detailed as possible. Aims. Seven of the most iron-poor stars have been observed with the UVES spectrograph at the ESO VLT Kueyen 8.2 m telescope to refine their chemical composition. Methods. We analysed the spectra based on 1D LTE model atmospheres, but also used 3D hydrodynamical simulations of stellar atmospheres. Results. We measured carbon in six of the seven stars: all are carbon-enhanced and belong to the low-carbon band, defined in the TOPoS II paper. We measured lithium (A(Li) = 1.9) in the most iron-poor star (SDSS J1035+0641, [Fe/H] <-5.2). We were also able to measure Li in three stars at [Fe/H] ~-4.0, two of which lie on the Spite plateau. We confirm that SDSS J1349+1407 is extremely rich in Mg, but not in Ca. It is also very rich in Na. Several of our stars are characterised by low α-to-iron ratios. Conclusions. The lack of high-carbon band stars at low metallicity can be understood in terms of evolutionary timescales of binary systems. The detection of Li in SDSS J1035+0641 places a strong constraint on theories that aim at solving the cosmological lithium problem. The Li abundance of the two warmer stars at [Fe/H] ~-4.0 places them on the Spite plateau, while the third, cooler star, lies below. We argue that this suggests that the temperature at which Li depletion begins increases with decreasing [Fe/H]. SDSS J1349+1407 may belong to a class of Mg-rich EMP stars. We cannot assess if there is a scatter in α-to-iron ratios among the EMP stars or if there are several discrete populations. However, the existence of stars with low α-to-iron ratios is supported by our observations. © ESO 2018.