Examinando por Autor "Spitoni, E."

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    Gaia Focused Product Release: Radial velocity time series of long-period variables
    (EDP Sciences, 2023-12) Trabucchi, M.; Mowlavi, N.; Lebzelter, T.; Lecoeur-Taibi, I.; Audard, M.; Eyer, L.; García-Lario, P.; Gavras, P.; Holl, B.; Jevardat De Fombelle, G.; Nienartowicz, K.; Rimoldini, L.; Sartoretti, P.; Blomme, R.; Frémat, Y.; Marchal, O.; Damerdji, Y.; Brown A.G.A.; Guerrier, A.; Panuzzo, P.; Katz, D.; Seabroke, G.M.; Benson, K.; Haigron, R.; Smith, M.; Lobel, A.; Vallenari, A.; Prusti, T.; De Bruijne, J.H.J.; Arenou, F.; Babusiaux, C.; Barbier, A.; Biermann, M.; Creevey, O.L.; Ducourant, C.; Evans, D.W.; Guerra, R.; Hutton, A.; Jordi, C.; Klioner, S.A.; Lammers, U.; Lindegren, L.; Luri, X.; Mignard, F.; Randich, S.; Smiljanic, R.; Tanga, P.; Walton, N.A.; Bailer-Jones, C.A.L.; Bastian, U.; Cropper, M.; Drimmel, R.; Lattanzi, M.G.; Soubiran, C.; Van Leeuwen, F.; Bakker, J.; Castañeda, J.; De Angeli, F.; Fabricius, C.; Fouesneau, M.; Galluccio, L.; Masana, E.; Messineo, R.; Nicolas, C.; Pailler, F.; Riclet, F.; Roux, W.; Sordo, R.; Thévenin, F.; Gracia-Abril G.; Portell, J.; Teyssier, D.; Altmann, M.; Berthier, J; Burgess, P.W.; Busonero, D.; Busso, G.; Cánovas, H.; Carry, B.; Cheek, N.; Clementini, G.; Davidson, M.; De Teodoro, P.; Delchambre, L.; Dell'oro, A.; Fraile Garcia, E.; Garabato, D.; Garralda Torres, N.; Hambly, N.C.; Harrison, D.L.; Hatzidimitriou, D.; Hernández, J.; Hodgkin, S.T.; Jamal, S.; Jordan, S.; Krone-Martins, A.; Lanzafame, A.C.; Löffler, W.; Lorca, A.; Marrese, P.M.; Moitinho, A.; Muinonen, K.; Nuñez Campos, M.; Oreshina-Slezak, I.; Osborne, P.; Pancino, E.; Pauwels, T.; Recio-Blanco, A.; Riello, M.; Robin, A.C.; Roegiers, T.; Sarro, L.M.; Schultheis, M.; Siopis, C.; Siopis, C.; Sozzetti, A.; Utrilla, E.; Van Leeuwen, M.; Weingrill, K.; Abbas, U.; Ábrahám, P.; Abreu Aramburu, A.; Aerts , C.; Altavilla, G.; Álvarez, M.A.; Alves, J.; Anders, F.; Anderson, R.I.; Antoja, T.; Baines, D.; Baker, S.G.; Balog, Z.; Barache, C; Barbato, D.; Barros, M.; Barstow, M.A.; Bartolomé, S.; Bashi, D.; Bauchet, N.; Baudeau, N.; Becciani, U.; Bedin, L.R.; Bellas-Velidis, I.; Bellazzini, M.; Beordo, W.; Berihuete, A.; Bernet, M.; Bertolotto, C.; Bertone, S.; Bianchi, L.; Binnenfeld, A.; Blazere, A.; Boch, T.; Bombrun, A.; Bouquillon, S.; Bragaglia, A.; Braine, J.; Bramante, L.; Breedt, E.; Bressan, A.; Brouillet, N.; Brugaletta, E.; Bucciarelli, B.; Butkevich, A.G.; Buzzi, R.; Caffau, E.; Cancelliere, R.; Cannizzo, S.; Carballo, R.; Carlucci, T.; Carnerero, M.I.; Carrasco, J.M.; Carretero, J.; Carton, S.; Casamiquela, L.; Castellani, M.; Castro-Ginard, A.; Cesare, V.; Charlot, P.; Chemin, L.; Chiaramida, V.; Chiavassa, A.; Chornay, N.; Collins, R.; Contursi, G.; Cooper, W.J.; Cornez, T.; Crosta, M.; Crowley, C.; Dafonte, C.; David, M.; De Laverny, P.; De Luise, F.; De March, R.; De Ridder, J.; De Souza, R.; De Torres A.; Del Peloso, E.F.; Delbo, M.; Delgado, A.; Dharmawardena, T.E.; Diakite, S.; Diener, C.; Distefano, E.; Dolding, C.; Dsilva, K.; Durán, J.; Enke, H.; Esquej, P.; Fabre, C.; Fabrizio, M.; Faigler, S.; Fatović, M.; Fedorets, G.; Fernández-Hernández, J.; Fernique, P.; Figueras, F.; Fournier, Y.; Fouron, C.; Gai, M.; Galinier, M.; Garcia-Gutierrez, A.; García-Torres, M.; Garofalo, A.; Gerlach, E.; Geyer, R.; Giacobbe, P.; Gilmore, G.; Girona, S.; Giuffrida, G.; Gomel, R.; Gomez, A.; González-Núñez, J.; González-Santamaría, I.; Gosset, E.; Granvik, M.; Gregori Barrera, V.; Gutiérrez-Sánchez, R.; Haywood, M.; Helmer, A.; Helmi, A.; Henares, K.; Hidalgo, S.L.; Hilger, T.; Hobbs, D.; Hottier, C.; Huckle, H.E.; Jabłońska, M.; Jansen, F.; Jiménez-Arranz, Ó.; Juaristi Campillo, J.; Khanna, S.; Kordopatis, G.; Kóspál, Á.; Kostrzewa-Rutkowska, Z.; Kun, M.; Lambert, S.; Lanza, A.F.; Le Campion, J.-F.; Lebreton, Y.; Leccia, S.; Lecoutre, G.; Liao, S.; Liberato, L.; Licata, E.; Lindstrøm, H.E.P.; Lister, T.A.; Livanou, E.; Loup, C.; Mahy, L.; Mann, R.G.; Manteiga, M.; Marchant, J.M.; Marconi, M.; Marín Pina, D.; Marinoni, S.; Marshall, D.J.; Martín Lozano. J.; Martín-Fleitas, J.M.; Marton, G.; Mary, N.; Masip, A.; Massari, D.; Mastrobuono-Battisti, A.; Mazeh, T.; McMillan, P.J.; Meichsner, J.; Messina, S.; Michalik , D.; Millar, N.R.; Mints, A.; Molina, D.; Molinaro, R.; Molnár, L.; Monari, G.; Monguió, M.; Montegriffo, P.; Montero, A.; Mor, R.; Mora, A.; Morbidelli, R.; Morel, T.; Morris, D.; Munoz, D.; Muraveva, T.; Murphy, C.P.; Musella, I.; Nagy, Z.; Nieto, S.; Noval, L.; Ogden, A.; Ordenovic, C.; Pagani, C.; Pagano, I.; Palaversa, L.; Palicio, P.A.; Pallas-Quintela, L.; Panahi, A.; Panem, C.; Payne-Wardenaar, S.; Pegoraro, L.; Penttilä, A.; Pesciullesi, P.; Piersimoni, A.M.; Pinamonti, M.; Pineau, F.-X.; Plachy, E.; Plum, G.; Poggio, E.; Pourbaix, D.; Prša, A.; Pulone, L.; Racero, E.; Rainer, M.; Raiteri, C.M.; Ramos, P.; Ramos-Lerate, M.; Ratajczak, M.; Re Fiorentin, P.; Regibo, S.; Reylé, C.; Ripepi, V.; Riva, A.; Rix H.-W.; Rixon, G.; Robichon, N.; Robin, C.; Romero-Gómez, M.; Rowell, N.; Royer, F.; Ruz Mieres, D.; Rybicki, K.A.; Sadowski, G.; Sáez Núñez, A.; Sagristà Sellés, A.; Sahlmann, J.; Sanchez Gimenez, V.; Sanna, N.; Santoveña, R.; Sarasso, M.; Sarrate Riera, C.; Sciacca, E.; Segovia, J.C.; Ségransan, D.; Shahaf, S.; Siebert, A.; Siltala, L.; Slezak, E.; Smart, R.L.; Snaith, O.N.; Solano, E.; Solitro, F.; Souami, D.; Souchay, J.; Spina, L.; Spitoni, E.; Spoto, F.; Squillante, L.A.; Steele, I.A.; Steidelmüller, H.; Surdej, J.; Szabados, L.; Taris, F.; Taylor, M.B.; Teixeira, R.; Tisanić, K.; Tolomei, L.; Torra, F.; Torralba, Elipe G.; Tsantaki, M.; Ulla, A.; Unger, N.; Vanel, O.; Vecchiato, A.; Vicente, D.; Voutsinas, S.; Weiler, M.; Wyrzykowski, Ł.; Zhao, H.; Zorec, J.; Zwitter, T.; Balaguer-Nunez, L.; Leclerc, N.; Morgenthaler, S.; Robert, G.; Zucker, S.
    Context. The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (FPR) provides radial-velocity time series for a selection of LPV candidates with high-quality observations. Aims. We describe the production and content of the Gaia catalog of LPV radial-velocity time series, and the methods used to compute the variability parameters published as part of the Gaia FPR. Methods. Starting from the DR3 catalog of LPV candidates, we applied several filters to construct a sample of sources with high-quality radial-velocity measurements. We modeled their radial-velocity and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the radial-velocity period and at least one of the G, GBP, or GRP photometric periods. Results. The catalog includes radial-velocity time series and variability parameters for 9614 sources in the magnitude range 6 ≲ G/mag ≲ 14, including a flagged top-quality subsample of 6093 stars whose radial-velocity periods are fully compatible with the values derived from the G, GBP, and GRP photometric time series. The radial-velocity time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great majority of the sources (88%) as genuine LPV candidates, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% of the catalog consists of candidate ellipsoidal binaries. Quality checks against radial velocities available in the literature show excellent agreement. We provide some illustrative examples and cautionary remarks. Conclusions. The publication of radial-velocity time series for almost ten thousand LPV candidates constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog. © The Authors 2023.
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    MINCE: I. Presentation of the project and of the first year sample
    (EDP Sciences, 2022-12-01) Cescutti, G.; Bonifacio, P.; Caffau, E.; Monaco, L.; Franchini, M.; Lombardo, L.; Matas Pinto, A.M.; Lucertini, F.; François, P.; Spitoni, E.; Lallement, R.; Sbordone, L.; Mucciarelli, A.; Spite, M.; Hansen, C.J.; Di Marcantonio, P.; Kučinskas, A.; Dobrovolskas, V.; Korn, A.J.; Valentini, M.; Magrini, L.; Cristallo, S.; Matteucci, F.
    Context. In recent years, Galactic archaeology has become a particularly vibrant field of astronomy, with its main focus set on the oldest stars of our Galaxy. In most cases, these stars have been identified as the most metal-poor. However, the struggle to find these ancient fossils has produced an important bias in the observations - in particular, the intermediate metal-poor stars (-2.5 < [Fe/H] <-1.5) have been frequently overlooked. The missing information has consequences for the precise study of the chemical enrichment of our Galaxy, in particular for what concerns neutron capture elements and it will be only partially covered by future multi object spectroscopic surveys such as WEAVE and 4MOST. Aims. Measuring at Intermediate Metallicity Neutron Capture Elements (MINCE) is gathering the first high-quality spectra (high signal-to-noise ratio, S/N, and high resolution) for several hundreds of bright and metal-poor stars, mainly located in our Galactic halo. Methods. We compiled our selection mainly on the basis of Gaia data and determined the stellar atmospheres of our sample and the chemical abundances of each star. Results. In this paper, we present the first sample of 59 spectra of 46 stars. We measured the radial velocities and computed the Galactic orbits for all stars. We found that 8 stars belong to the thin disc, 15 to disrupted satellites, and the remaining cannot be associated to the mentioned structures, and we call them halo stars. For 33 of these stars, we provide abundances for the elements up to zinc. We also show the chemical evolution results for eleven chemical elements, based on recent models. Conclusions. Our observational strategy of using multiple telescopes and spectrographs to acquire high S/N and high-resolution spectra for intermediate-metallicity stars has proven to be very efficient, since the present sample was acquired over only about one year of observations. Finally, our target selection strategy, after an initial adjustment, proved satisfactory for our purposes. © 2022 EDP Sciences. All rights reserved.