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Context. This work is part of the Gaia Data Processing and Analysis Consortium papers published with the Gaia Early Data Release 3 (EDR3). It is one of the demonstration papers aiming to highlight the improvements and quality of the newly published data by applying them to a scientific case. Aims. We use the Gaia EDR3 data to study the structure and kinematics of the Magellanic Clouds. The large distance to the Clouds is a challenge for the Gaia astrometry. The Clouds lie at the very limits of the usability of the Gaia data, which makes the Clouds an excellent case study for evaluating the quality and properties of the Gaia data. Methods. The basis of our work are two samples selected to provide a representation as clean as possible of the stars of the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC). The selection used criteria based on position, parallax, and proper motions to remove foreground contamination from the Milky Way, and allowed the separation of the stars of both Clouds. From these two samples we defined a series of subsamples based on cuts in the colour-magnitude diagram; these subsamples were used to select stars in a common evolutionary phase and can also be used as approximate proxies of a selection by age. Results. We compared the Gaia Data Release 2 and Gaia EDR3 performances in the study of the Magellanic Clouds and show the clear improvements in precision and accuracy in the new release. We also show that the systematics still present in the data make the determination of the 3D geometry of the LMC a difficult endeavour; this is at the very limit of the usefulness of the Gaia EDR3 astrometry, but it may become feasible with the use of additional external data. We derive radial and tangential velocity maps and global profiles for the LMC for the several subsamples we defined. To our knowledge, this is the first time that the two planar components of the ordered and random motions are derived for multiple stellar evolutionary phases in a galactic disc outside the Milky Way, showing the differences between younger and older phases. We also analyse the spatial structure and motions in the central region, the bar, and the disc, providing new insightsinto features and kinematics. Finally, we show that the Gaia EDR3 data allows clearly resolving the Magellanic Bridge, and we trace the density and velocity flow of the stars from the SMC towards the LMC not only globally, but also separately for young and evolved populations. This allows us to confirm an evolved population in the Bridge that is slightly shift from the younger population. Additionally, we were able to study the outskirts of both Magellanic Clouds, in which we detected some well-known features and indications of new ones.
Gaia Early Data Release 3: Structure and properties of the Magellanic Clouds
Luri X.;Chemin L.;Clementini G.;Delgado H. E.;McMillan P. J.;Romero-Gomez M.;Balbinot E.;Castro-Ginard A.;Mor R.;Ripepi V.;Sarro L. M.;Cioni M. -R. L.;Fabricius C.;Garofalo A.;Helmi A.;Muraveva T.;Brown A. G. A.;Vallenari A.;Prusti T.;De Bruijne J. H. J.;Babusiaux C.;Biermann M.;Creevey O. L.;Evans D. W.;Eyer L.;Hutton A.;Jansen F.;Jordi C.;Klioner S. A.;Lammers U.;Lindegren L.;Mignard F.;Panem C.;Pourbaix D.;Randich S.;Sartoretti P.;Soubiran C.;Walton N. A.;Arenou F.;Bailer-Jones C. A. L.;Bastian U.;Cropper M.;Drimmel R.;Katz D.;Lattanzi M. G.;Van Leeuwen F.;Bakker J.;Castaneda J.;De Angeli F.;Ducourant C.;Fouesneau M.;Fremat Y.;Guerra R.;Guerrier A.;Guiraud J.;Jean-Antoine Piccolo A.;Masana E.;Messineo R.;Mowlavi N.;Nicolas C.;Nienartowicz K.;Pailler F.;Panuzzo P.;Riclet F.;Roux W.;Seabroke G. M.;Sordo R.;Tanga P.;Thevenin F.;Gracia-Abril G.;Portell J.;Teyssier D.;Altmann M.;Andrae R.;Bellas-Velidis I.;Benson K.;Berthier J.;Blomme R.;Brugaletta E.;Burgess P. W.;Busso G.;Carry B.;Cellino A.;Cheek N.;Damerdji Y.;Davidson M.;Delchambre L.;Dell'Oro A.;Fernandez-Hernandez J.;Galluccio L.;Garcia-Lario P.;Garcia-Reinaldos M.;Gonzalez-Nunez J.;Gosset E.;Haigron R.;Halbwachs J. -L.;Hambly N. C.;Harrison D. L.;Hatzidimitriou D.;Heiter U.;Hernandez J.;Hestroffer D.;Hodgkin S. T.;Holl B.;Janssen K.;Jevardat De Fombelle G.;Jordan S.;Krone-Martins A.;Lanzafame A. C.;Loffler W.;Lorca A.;Manteiga M.;Marchal O.;Marrese P. M.;Moitinho A.;Mora A.;Muinonen K.;Osborne P.;Pancino E.;Pauwels T.;Recio-Blanco A.;Richards P. J.;Riello M.;Rimoldini L.;Robin A. C.;Roegiers T.;Rybizki J.;Siopis C.;Smith M.;Sozzetti A.;Ulla A.;Utrilla E.;Van Leeuwen M.;Van Reeven W.;Abbas U.;Abreu Aramburu A.;Accart S.;Aerts C.;Aguado J. J.;Ajaj M.;Altavilla G.;Alvarez M. A.;Alvarez Cid-Fuentes J.;Alves J.;Anderson R. I.;Anglada Varela E.;Antoja T.;Audard M.;Baines D.;Baker S. G.;Balaguer-Nunez L.;Balog Z.;Barache C.;Barbato D.;Barros M.;Barstow M. A.;Bartolome S.;Bassilana J. -L.;Bauchet N.;Baudesson-Stella A.;Becciani U.;Bellazzini M.;Bernet M.;Bertone S.;Bianchi L.;Blanco-Cuaresma S.;Boch T.;Bombrun A.;Bossini D.;Bouquillon S.;Bragaglia A.;Bramante L.;Breedt E.;Bressan A.;Brouillet N.;Bucciarelli B.;Burlacu A.;Busonero D.;Butkevich A. G.;Buzzi R.;Caffau E.;Cancelliere R.;Canovas H.;Cantat-Gaudin T.;Carballo R.;Carlucci T.;Carnerero M. I.;Carrasco J. M.;Casamiquela L.;Castellani M.;Castro Sampol P.;Chaoul L.;Charlot P.;Chiavassa A.;Comoretto G.;Cooper W. J.;Cornez T.;Cowell S.;Crifo F.;Crosta M.;Crowley C.;Dafonte C.;Dapergolas A.;David M.;David P.;De Laverny P.;De Luise F.;De March R.;De Ridder J.;De Souza R.;De Teodoro P.;De Torres A.;Del Peloso E. F.;Del Pozo E.;Delgado A.;Delisle J. -B.;Di Matteo P.;Diakite S.;Diener C.;Distefano E.;Dolding C.;Eappachen D.;Enke H.;Esquej P.;Fabre C.;Fabrizio M.;Faigler S.;Fedorets G.;Fernique P.;Fienga A.;Figueras F.;Fouron C.;Fragkoudi F.;Fraile E.;Franke F.;Gai M.;Garabato D.;Garcia-Gutierrez A.;Garcia-Torres M.;Gavras P.;Gerlach E.;Geyer R.;Giacobbe P.;Gilmore G.;Girona S.;Giuffrida G.;Gomez A.;Gonzalez-Santamaria I.;Gonzalez-Vidal J. J.;Granvik M.;Gutierrez-Sanchez R.;Guy L. P.;Hauser M.;Haywood M.;Hidalgo S. L.;Hilger T.;Hladczuk N.;Hobbs D.;Holland G.;Huckle H. E.;Jasniewicz G.;Jonker P. G.;Juaristi Campillo J.;Julbe F.;Karbevska L.;Kervella P.;Khanna S.;Kochoska A.;Kontizas M.;Kordopatis G.;Korn A. J.;Kostrzewa-Rutkowska Z.;Kruszynska K.;Lambert S.;Lanza A. F.;Lasne Y.;Le Campion J. -F.;Le Fustec Y.;Lebreton Y.;Lebzelter T.;Leccia S.;Leclerc N.;Lecoeur-Taibi I.;Liao S.;Licata E.;Lindstrom H. E. P.;Lister T. A.;Livanou E.;Lobel A.;Madrero Pardo P.;Managau S.;Mann R. G.;Marchant J. M.;Marconi M.;Marcos Santos M. M. S.;Marinoni S.;Marocco F.;Marshall D. J.;Martin Polo L.;Martin-Fleitas J. M.;Masip A.;Massari D.;Mastrobuono-Battisti A.;Mazeh T.;Messina S.;Michalik D.;Millar N. R.;Mints A.;Molina D.;Molinaro R.;Molnar L.;Montegriffo P.;Morbidelli R.;Morel T.;Morris D.;Mulone A. F.;Munoz D.;Murphy C. P.;Musella I.;Noval L.;Ordenovic C.;Orru G.;Osinde J.;Pagani C.;Pagano I.;Palaversa L.;Palicio P. A.;Panahi A.;Pawlak M.;Penalosa Esteller X.;Penttila A.;Piersimoni A. M.;Pineau F. -X.;Plachy E.;Plum G.;Poggio E.;Poretti E.;Poujoulet E.;Prsa A.;Pulone L.;Racero E.;Ragaini S.;Rainer M.;Raiteri C. M.;Rambaux N.;Ramos P.;Ramos-Lerate M.;Re Fiorentin P.;Regibo S.;Reyle C.;Riva A.;Rixon G.;Robichon N.;Robin C.;Roelens M.;Rohrbasser L.;Rowell N.;Royer F.;Rybicki K. A.;Sadowski G.;Sagrista Selles A.;Sahlmann J.;Salgado J.;Salguero E.;Samaras N.;Gimenez V. S.;Sanna N.;Santovena R.;Sarasso M.;Schultheis M.;Sciacca E.;Segol M.;Segovia J. C.;Segransan D.;Semeux D.;Siddiqui H. I.;Siebert A.;Siltala L.;Slezak E.;Smart R. L.;Solano E.;Solitro F.;Souami D.;Souchay J.;Spagna A.;Spoto F.;Steele I. A.;Steidelmuller H.;Stephenson C. A.;Suveges M.;Szabados L.;Szegedi-Elek E.;Taris F.;Tauran G.;Taylor M. B.;Teixeira R.;Thuillot W.;Tonello N.;Torra F.;Torra J.;Turon C.;Unger N.;Vaillant M.;Van Dillen E.;Vanel O.;Vecchiato A.;Viala Y.;Vicente D.;Voutsinas S.;Weiler M.;Wevers T.;Wyrzykowski L.;Yoldas A.;Yvard P.;Zhao H.;Zorec J.;Zucker S.;Zurbach C.;Zwitter T.
2021
Abstract
Context. This work is part of the Gaia Data Processing and Analysis Consortium papers published with the Gaia Early Data Release 3 (EDR3). It is one of the demonstration papers aiming to highlight the improvements and quality of the newly published data by applying them to a scientific case. Aims. We use the Gaia EDR3 data to study the structure and kinematics of the Magellanic Clouds. The large distance to the Clouds is a challenge for the Gaia astrometry. The Clouds lie at the very limits of the usability of the Gaia data, which makes the Clouds an excellent case study for evaluating the quality and properties of the Gaia data. Methods. The basis of our work are two samples selected to provide a representation as clean as possible of the stars of the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC). The selection used criteria based on position, parallax, and proper motions to remove foreground contamination from the Milky Way, and allowed the separation of the stars of both Clouds. From these two samples we defined a series of subsamples based on cuts in the colour-magnitude diagram; these subsamples were used to select stars in a common evolutionary phase and can also be used as approximate proxies of a selection by age. Results. We compared the Gaia Data Release 2 and Gaia EDR3 performances in the study of the Magellanic Clouds and show the clear improvements in precision and accuracy in the new release. We also show that the systematics still present in the data make the determination of the 3D geometry of the LMC a difficult endeavour; this is at the very limit of the usefulness of the Gaia EDR3 astrometry, but it may become feasible with the use of additional external data. We derive radial and tangential velocity maps and global profiles for the LMC for the several subsamples we defined. To our knowledge, this is the first time that the two planar components of the ordered and random motions are derived for multiple stellar evolutionary phases in a galactic disc outside the Milky Way, showing the differences between younger and older phases. We also analyse the spatial structure and motions in the central region, the bar, and the disc, providing new insightsinto features and kinematics. Finally, we show that the Gaia EDR3 data allows clearly resolving the Magellanic Bridge, and we trace the density and velocity flow of the stars from the SMC towards the LMC not only globally, but also separately for young and evolved populations. This allows us to confirm an evolved population in the Bridge that is slightly shift from the younger population. Additionally, we were able to study the outskirts of both Magellanic Clouds, in which we detected some well-known features and indications of new ones.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3537982
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.
