Gaia Early Data Release 3. The Gaia Catalogue of Nearby Stars

Creators: Smart, R. L.; Sarro, L. M.; Rybizki, J.; Reylé, C.; Robin, A. C.; Hambly, N. C.; Abbas, U.; Barstow, M. A.; de Bruijne, J. H. J.; Bucciarelli, B.; Carrasco, J. M.; Cooper, W. J.; Hodgkin, S. T.; Masana, E.; Michalik, D.; Sahlmann, J.; Sozzetti, A.; Brown, A. G. A.; Vallenari, A.; Prusti, T.; 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.; Luri, X.; 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.; Castañeda, J.; De Angeli, F.; Ducourant, C.; Fabricius, C.; Fouesneau, M.; Frémat, Y.; Guerra, R.; Guerrier, A.; Guiraud, J.; Jean-Antoine Piccolo, A.; Messineo, R.; Mowlavi, N.; Nicolas, C.; Nienartowicz, K.; Pailler, F.; Panuzzo, P.; Riclet, F.; Roux, W.; Seabroke, G. M.; Sordo, R.; Tanga, P.; Thévenin, 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.; Clementini, G.; Damerdji, Y.; Davidson, M.; Delchambre, L.; Dell'Oro, A.; Fernández-Hernández, J.; Galluccio, L.; García-Lario, P.; Garcia-Reinaldos, M.; González-Núñez, J.; Gosset, E.; Haigron, R.; Halbwachs, J.-L.; Harrison, D. L.; Hatzidimitriou, D.; Heiter, U.; Hernández, J.; Hestroffer, D.; Holl, B.; Janßen, K.; Jevardat de Fombelle, G.; Jordan, S.; Krone-Martins, A.; Lanzafame, A. C.; Löffler, 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.; Roegiers, T.; Siopis, C.; Smith, M.; Ulla, A.; Utrilla, E.; van Leeuwen, M.; van Reeven, W.; Abreu Aramburu, A.; Accart, S.; Aerts, C.; Aguado, J. J.; Ajaj, M.; Altavilla, G.; Álvarez, M. A.; Álvarez Cid-Fuentes, J.; Alves, J.; Anderson, R. I.; Anglada Varela, E.; Antoja, T.; Audard, M.; Baines, D.; Baker, S. G.; Balaguer-Núñez, L.; Balbinot, E.; Balog, Z.; Barache, C.; Barbato, D.; Barros, M.; Bartolomé, 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.; Burlacu, A.; Busonero, D.; Butkevich, A. G.; Buzzi, R.; Caffau, E.; Cancelliere, R.; Cánovas, H.; Cantat-Gaudin, T.; Carballo, R.; Carlucci, T.; Carnerero, M. I; Casamiquela, L.; Castellani, M.; Castro-Ginard, A.; Castro Sampol, P.; Chaoul, L.; Charlot, P.; Chemin, L.; Chiavassa, A.; Cioni, M.-R. L.; Comoretto, G.; 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.; Delgado, H. E.; Delisle, J.-B.; Di Matteo, P.; Diakite, S.; Diener, C.; Distefano, E.; Dolding, C.; Eappachen, D.; Edvardsson, B.; 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.; García-Torres, M.; Garofalo, A.; Gavras, P.; Gerlach, E.; Geyer, R.; Giacobbe, P.; Gilmore, G.; Girona, S.; Giuffrida, G.; Gomel, R.; Gomez, A.; Gonzalez-Santamaria, I.; González-Vidal, J. J.; Granvik, M.; Gutiérrez-Sánchez, R.; Guy, L. P.; Hauser, M.; Haywood, M.; Helmi, A.; Hidalgo, S. L.; Hilger, T.; Hładczuk, 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.; Kruszyńska, 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.; Lindstrøm, 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.; Martín-Fleitas, J. M.; Masip, A.; Massari, D.; Mastrobuono-Battisti, A.; Mazeh, T.; McMillan, P. J.; Messina, S.; Millar, N. R.; Mints, A.; Molina, D.; Molinaro, R.; Molnár, L.; Montegriffo, P.; Mor, R.; Morbidelli, R.; Morel, T.; Morris, D.; Mulone, A. F.; Munoz, D.; Muraveva, T.; Murphy, C. P.; Musella, I.; Noval, L.; Ordénovic, C.; Orrù, G.; Osinde, J.; Pagani, C.; Pagano, I.; Palaversa, L.; Palicio, P. A.; Panahi, A.; Pawlak, M.; Peñalosa Esteller, X.; Penttilä, A.; Piersimoni, A. M.; Pineau, F.-X.; Plachy, E.; Plum, G.; Poggio, E.; Poretti, E.; Poujoulet, E.; Prša, A.; Pulone, L.; Racero, E.; Ragaini, S.; Rainer, M.; Raiteri, C. M.; Rambaux, N.; Ramos, P.; Ramos-Lerate, M.; Re Fiorentin, P.; Regibo, S.; Ripepi, V.; Riva, A.; Rixon, G.; Robichon, N.; Robin, C.; Roelens, M.; Rohrbasser, L.; Romero-Gómez, M.; Rowell, N.; Royer, F.; Rybicki, K. A.; Sadowski, G.; Sagristà Sellés, A.; Salgado, J.; Salguero, E.; Samaras, N.; Sanchez Gimenez, V.; Sanna, N.; Santoveña, R.; Sarasso, M.; Schultheis, M.; Sciacca, E.; Segol, M.; Segovia, J. C.; Ségransan, D.; Semeux, D.; Shahaf, S.; Siddiqui, H. I.; Siebert, A.; Siltala, L.; Slezak, E.; Solano, E.; Solitro, F.; Souami, D.; Souchay, J.; Spagna, A.; Spoto, F.; Steele, I. A.; Steidelmüller, H.; Stephenson, C. A.; Süveges, 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, Ł.; Yoldas, A.; Yvard, P.; Zhao, H.; Zorec, J.; Zucker, S.; Zurbach, C.; Zwitter, T.; Gaia Collaboration

Abstract

Aims. We produce a clean and well-characterised catalogue of objects within 100 pc of the Sun from the Gaia Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. Methods. Theselection of objects within 100 pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100 pc is included in the catalogue. Results. We have produced a catalogue of 331 312 objects that we estimate contains at least 92% of stars of stellar type M9 within 100 pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100 pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of Gaia Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10 pc of the Sun. Conclusions. We provide the community with a large, well-characterised catalogue of objects in the solar neighbourhood. This is a primary benchmark for measuring and understanding fundamental parameters and descriptive functions in astronomy.

Additional Information

© ESO 2021. Received 22 September 2020; Accepted 30 October 2020; Published online 28 April 2021. We thank the anonymous referee for comments and suggestions that improved this article. This work presents results from the European Space Agency (ESA) space mission Gaia. Gaia data are being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia MultiLateral Agreement (MLA). The Gaia mission website is https://www.cosmos.esa.int/gaia. The Gaia archive website is https://archives.esac.esa.int/gaia. The Gaia mission and data processing have financially been supported by, in alphabetical order by country: the Algerian Centre de Recherche en Astronomie, Astrophysique et Géophysique of Bouzareah Observatory; the Austrian Fonds zur Förderung der wissenschaftlichen Forschung (FWF) Hertha Firnberg Programme through grants T359, P20046, and P23737; the BELgian federal Science Policy Office (BELSPO) through various PROgramme de Développement d'Expériences scientifiques (PRODEX) grants and the Polish Academy of Sciences – Fonds Wetenschappelijk Onderzoek through grant VS.091.16N, and the Fonds de la Recherche Scientifique (FNRS); the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES) – Comité Français d'Evaluation de la Coopération Universitaire et Scientifique avec le Brésil (COFECUB); the National Science Foundation of China (NSFC) through grants 11573054 and 11703065 and the China Scholarship Council through grant 201806040200; the Tenure Track Pilot Programme of the Croatian Science Foundation and the École Polytechnique Fédérale de Lausanne and the project TTP-2018-07-1171 "Mining the Variable Sky", with the funds of the Croatian-Swiss Research Programme; the Czech-Republic Ministry of Education, Youth, and Sports through grant LG 15010 and INTER-EXCELLENCE grant LTAUSA18093, and the Czech Space Office through ESA PECS contract 98058; the Danish Ministry of Science; the Estonian Ministry of Education and Research through grant IUT40-1; the European Commission's Sixth Framework Programme through the European Leadership in Space Astrometry (ELSA) Marie Curie Research Training Network (MRTN-CT-2006-033481), through Marie Curie project PIOF-GA-2009-255267 (Space AsteroSeismology & RR Lyrae stars, SAS-RRL), and through a Marie Curie Transfer-of-Knowledge (ToK) fellowship (MTKD-CT-2004-014188); the European Commission's Seventh Framework Programme through grant FP7-606740 (FP7-SPACE-2013-1) for the Gaia European Network for Improved data User Services (GENIUS) and through grant 264895 for the Gaia Research for European Astronomy Training (GREAT-ITN) network; the European Research Council (ERC) through grants 320360 and 647208 and through the European Union's Horizon 2020 research and innovation and excellent science programmes through Marie Skłodowska-Curie grant 745617 as well as grants 670519 (Mixing and Angular Momentum tranSport of massIvE stars – MAMSIE), 687378 (Small Bodies: Near and Far), 682115 (Using the Magellanic Clouds to Understand the Interaction of Galaxies), and 695099 (A sub-percent distance scale from binaries and Cepheids – CepBin); the European Science Foundation (ESF), in the framework of the Gaia Research for European Astronomy Training Research Network Programme (GREAT-ESF); the European Space Agency (ESA) in the framework of the Gaia project, through the Plan for European Cooperating States (PECS) programme through grants for Slovenia, through contracts C98090 and 4000106398/12/NL/KML for Hungary, and through contract 4000115263/15/NL/IB for Germany; the Academy of Finland and the Magnus Ehrnrooth Foundation; the French Centre National d'Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR) through grant ANR-10-IDEX-0001-02 for the "Investissements d'avenir" programme, through grant ANR-15-CE31-0007 for project "Modelling the Milky Way in the Gaia era" (MOD4Gaia), through grant ANR-14-CE33-0014-01 for project "The Milky Way disc formation in the Gaia era" (ARCHEOGAL), and through grant ANR-15-CE31-0012-01 for project "Unlocking the potential of Cepheids as primary distance calibrators" (UnlockCepheids), the Centre National de la Recherche Scientifique (CNRS) and its SNO Gaia of the Institut des Sciences de l'Univers (INSU), the "Action Fédératrice Gaia" of the Observatoire de Paris, the Région de Franche-Comté, and the Programme National de Gravitation, Références, Astronomie,et Métrologie (GRAM) of CNRS/INSU with the Institut National Polytechnique (INP) and the Institut National de Physique nucléaire et de Physique des Particules (IN2P3) co-funded by CNES; the German Aerospace Agency (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) through grants 50QG0501, 50QG0601, 50QG0602, 50QG0701, 50QG0901, 50QG1001, 50QG1101, 50QG1401, 50QG1402, 50QG1403, 50QG1404, and 50QG1904 and the Centre for Information Services and High Performance Computing (ZIH) at the Technische Universität (TU) Dresden for generous allocations of computer time; the Hungarian Academy of Sciences through the Lendület Programme grants LP2014-17 and LP2018-7 and through the Premium Postdoctoral Research Programme (L. Molnár), and the Hungarian National Research, Development, and Innovation Office (NKFIH) through grant KH_18-130405; the Science Foundation Ireland (SFI) through a Royal Society - SFI University Research Fellowship (M. Fraser); the Israel Science Foundation (ISF) through grant 848/16; the Agenzia Spaziale Italiana (ASI) through contracts I/037/08/0, I/058/10/0, 2014-025-R.0, 2014-025-R.1.2015, and 2018-24-HH.0 to the Italian Istituto Nazionale di Astrofisica (INAF), contract 2014-049-R.0/1/2 to INAF for the Space Science Data Centre (SSDC, formerly known as the ASI Science Data Center, ASDC), contracts I/008/10/0, 2013/030/I.0, 2013-030-I.0.1-2015, and 2016-17-I.0 to the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.), INAF, and the Italian Ministry of Education, University, and Research (Ministero dell'Istruzione, dell'Università e della Ricerca) through the Premiale project "MIning The Cosmos Big Data and Innovative Italian Technology for Frontier Astrophysics and Cosmology" (MITiC); the Netherlands Organisation for Scientific Research (NWO) through grant NWO-M-614.061.414, through a VICI grant (A. Helmi), and through a Spinoza prize (A. Helmi), and the Netherlands Research School for Astronomy (NOVA); the Polish National Science Centre through HARMONIA grant 2018/06/M/ST9/00311, DAINA grant 2017/27/L/ST9/03221, and PRELUDIUM grant 2017/25/N/ST9/01253, and the Ministry of Science and Higher Education (MNiSW) through grant DIR/WK/2018/12; the Portugese Fundação para a Ciência e a Tecnologia (FCT) through grants SFRH/BPD/74697/2010 and SFRH/BD/128840/2017 and the Strategic Programme UID/FIS/00099/2019 for CENTRA; the Slovenian Research Agency through grant P1-0188; the Spanish Ministry of Economy (MINECO/FEDER, UE) through grants ESP2016-80079-C2-1-R, ESP2016-80079-C2-2-R, RTI2018-095076-B-C21, RTI2018-095076-B-C22, BES-2016-078499, and BES-2017-083126 and the Juan de la Cierva formación 2015 grant FJCI-2015-2671, the Spanish Ministry of Education, Culture, and Sports through grant FPU16/03827, the Spanish Ministry of Science and Innovation (MICINN) through grant AYA2017-89841P for project "Estudio de las propiedades de los fósiles estelares en el entorno del Grupo Local" and through grant TIN2015-65316-P for project "Computación de Altas Prestaciones VII", the Severo Ochoa Centre of Excellence Programme of the Spanish Government through grant SEV2015-0493, the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia "María de Maeztu") through grants MDM-2014-0369 and CEX2019-000918-M, the University of Barcelona's official doctoral programme for the development of an R+D+i project through an Ajuts de Personal Investigador en Formació (APIF) grant, the Spanish Virtual Observatory through project AyA2017-84089, the Galician Regional Government, Xunta de Galicia, through grants ED431B-2018/42 and ED481A-2019/155, support received from the Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC) funded by the Xunta de Galicia, the Xunta de Galicia and the Centros Singulares de Investigación de Galicia for the period 2016-2019 through CITIC, the European Union through the European Regional Development Fund (ERDF) / Fondo Europeo de Desenvolvemento Rexional (FEDER) for the Galicia 2014-2020 Programme through grant ED431G-2019/01, the Red Española de Supercomputación (RES) computer resources at MareNostrum, the Barcelona Supercomputing Centre – Centro Nacional de Supercomputación (BSC-CNS) through activities AECT-2016-1-0006, AECT-2016-2-0013, AECT-2016-3-0011, and AECT-2017-1-0020, the Departament d'Innovació, Universitats i Empresa de la Generalitat de Catalunya through grant 2014-SGR-1051 for project "Models de Programació i Entorns d'Execució Parallels" (MPEXPAR), and Ramon y Cajal Fellowship RYC2018-025968-I; the Swedish National Space Agency (SNSA/Rymdstyrelsen); the Swiss State Secretariat for Education, Research, and Innovation through the Mesures d'Accompagnement, the Swiss Activités Nationales Complémentaires, and the Swiss National Science Foundation; the United Kingdom Particle Physics and Astronomy Research Council (PPARC), the United Kingdom Science and Technology Facilities Council (STFC), and the United Kingdom Space Agency (UKSA) through the following grants to the University of Bristol, the University of Cambridge, the University of Edinburgh, the University of Leicester, the Mullard Space Sciences Laboratory of University College London, and the United Kingdom Rutherford Appleton Laboratory (RAL): PP/D006511/1, PP/D006546/1, PP/D006570/1, ST/I000852/1, ST/J005045/1, ST/K00056X/1, ST/K000209/1, ST/K000756/1, ST/L006561/1, ST/N000595/1, ST/N000641/1, ST/N000978/1, ST/N001117/1, ST/S000089/1, ST/S000976/1, ST/S001123/1, ST/S001948/1, ST/S002103/1, and ST/V000969/1. The Gaia project, data processing and this contribution have made use of: the Set of Identifications, Measurements, and Bibliography for Astronomical Data (SIMBAD, Wenger et al. 2000), the "Aladin sky atlas" (Bonnarel et al. 2000; Boch & Fernique 2014), and the VizieR catalogue access tool (Ochsenbein et al. 2000), all operated at the Centre de Données astronomiques de Strasbourg (CDS); the National Aeronautics and Space Administration (NASA) Astrophysics Data System (ADS); the software products TOPCAT, and STILTS (Taylor 2005, 2006); Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration 2018); data products from the Two Micron All Sky Survey (2MASS, Skrutskie et al. 2006), which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center (IPAC) / CaliforniaInstitute of Technology, funded by the National Aeronautics and Space Administration (NASA) and the National Science Foundation (NSF) of the USA; the first data release of the Pan-STARRS survey (Chambers et al. 2016)The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute forExtraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres ObservatoryGlobal Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration (NASA) through grant NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation through grant AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation; data products from the Wide-field Infrared Survey Explorer (WISE), which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, and NEOWISE, which is a project of the Jet Propulsion Laboratory/California Institute of Technology. WISE and NEOWISE are funded by the National Aeronautics and Space Administration (NASA); the fifth data release of the Radial Velocity Experiment (RAVE DR5, Kunder et al. 2017). Funding for RAVE has been provided by the Australian Astronomical Observatory, the Leibniz-Institut für Astrophysik Potsdam (AIP), the Australian National University, the Australian Research Council, the French National Research Agency, the German Research Foundation (SPP 1177 and SFB 881), the European Research Council (ERC-StG 240271 Galactica), the Istituto Nazionale di Astrofisica at Padova, The Johns Hopkins University, the National Science Foundation of the USA (AST-0908326), the W. M. Keck foundation, the Macquarie University, the Netherlands Research School for Astronomy, the Natural Sciences and Engineering Research Council of Canada, the Slovenian Research Agency, the Swiss National Science Foundation, the Science & Technology Facilities Council of the UK, Opticon, Strasbourg Observatory, and the Universities of Groningen, Heidelberg, and Sydney. The RAVE website is at https://www.rave-survey.org/; the thirteenth release of the Sloan Digital Sky Survey (SDSS DR13, Albareti et al. 2017). Funding for SDSS-IV has been provided by the Alfred P. Sloan Foundation, the United States Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is https://www.sdss.org/. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University; the second release of the SkyMapper catalogue (SkyMapper DR2, Onken et al. 2019, Digital Object Identifier 10.25914/5ce60d31ce759). The national facility capability for SkyMapper has been funded through grant LE130100104 from the Australian Research Council (ARC) Linkage Infrastructure, Equipment, and Facilities (LIEF) programme, awarded to the University of Sydney, the Australian National University, Swinburne University of Technology, the University of Queensland, the University of Western Australia, the University of Melbourne, Curtin University of Technology, Monash University, and the Australian Astronomical Observatory. SkyMapper is owned and operated by The Australian National University's Research School of Astronomy and Astrophysics. The survey data were processed and provided by the SkyMapper Team at the Australian National University. The SkyMapper node of the All-Sky Virtual Observatory (ASVO) is hosted at the National Computational Infrastructure (NCI). Development and support the SkyMapper node of the ASVO has been funded in part by Astronomy Australia Limited (AAL) and the Australian Government through the Commonwealth's Education Investment Fund (EIF) and National Collaborative Research Infrastructure Strategy (NCRIS), particularly the National eResearch Collaboration Tools and Resources (NeCTAR) and the Australian National Data Service Projects (ANDS).

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