Gaia Data Release 3 Summary of the variability processing and analysis

被引：65

作者：

Eyer, L. ^{[1
]}

Audard, M. ^{[1
,2
]}

Holl, B. ^{[2
]}

Rimoldini, L. ^{[2
]}

Carnerero, M. I. ^{[3
]}

Clementini, G. ^{[4
]}

De Ridder, J. ^{[5
]}

Distefano, E. ^{[6
]}

Evans, D. W. ^{[7
]}

Gavras, P. ^{[8
]}

Gomel, R. ^{[9
]}

Lebzelter, T. ^{[10
]}

Marton, G. ^{[11
]}

Mowlavi, N. ^{[1
,2
]}

Panahi, A. ^{[9
]}

Ripepi, V. ^{[12
]}

Wyrzykowski, L. ^{[13
]}

Nienartowicz, K. ^{[2
,14
]}

de Fombelle, G. Jevardat ^{[2
]}

Lecoeur-Taibi, I. ^{[2
]}

Rohrbasser, L. ^{[2
]}

Riello, M. ^{[7
]}

Garcia-Lario, P. ^{[15
]}

Lanzafame, A. C. ^{[6
,16
]}

Mazeh, T. ^{[9
]}

Raiteri, C. M. ^{[3
]}

Zucker, S. ^{[17
]}

Abraham, P. ^{[11
,18
]}

Aerts, C. ^{[5
,19
,20
]}

Aguado, J. J. ^{[21
]}

Anderson, R. I. ^{[22
]}

Bashi, D. ^{[17
]}

Binnenfeld, A. ^{[17
]}

Faigler, S. ^{[9
]}

Garofalo, A. ^{[4
]}

Karbevska, L. ^{[23
]}

Kospal, A. ^{[11
,18
,20
]}

Kruszynska, K. ^{[13
]}

Kun, M. ^{[11
]}

Lanza, A. F. ^{[6
]}

Leccia, S. ^{[12
]}

Marconi, M. ^{[12
]}

Messina, S. ^{[6
]}

Molinaro, R. ^{[12
]}

Molnar, L. ^{[11
,18
,24
]}

Muraveva, T. ^{[4
]}

Musella, I. ^{[12
]}

Nagy, Z. ^{[11
]}

Pagano, I. ^{[6
]}

Palaversa, L. ^{[7
,25
]}

机构：

[1] Univ Geneva, Dept Astron, Chemin Pegasi 51, CH-1290 Versoix, Switzerland

[2] Univ Geneva, Dept Astron, Chemin Ecogia 16, CH-1290 Versoix, Switzerland

[3] INAF Osservatorio Astrofis Torino, Via Osservatorio 20, I-10025 Pino Torinese, TO, Italy

[4] INAF Osservatorio Astrofis & Sci Spazio Bologna, Via Piero Gobetti 93-3, I-40129 Bologna, Italy

[5] Katholieke Univ Leuven, Inst Sterrenkunde, Celestijnenlaan 200D, B-3001 Leuven, Belgium

[6] INAF Osservatorio Astrofis Catania, Via S Sofia 78, I-95123 Catania, Italy

[7] Univ Cambridge, Inst Astron, Madingley Rd, Cambridge CB3 0HA, England

[8] RHEA European Space Agcy ESA, Camino Bajo Castillo S-N, Villanueva De La Canada 28692, Madrid, Spain

[9] Tel Aviv Univ, Sch Phys & Astron, IL-6997801 Tel Aviv, Israel

[10] Univ Vienna, Dept Astrophys, Turkenschanzstr 17, A-1180 Vienna, Austria

[11] Konkoly Observ Budapest, Res Ctr Astron & Earth Sci, Eotvos Lorand Res Network ELKH, MTA Ctr Excellence, Konkoly Thege Miklos Ut 15-17, H-1121 Budapest, Hungary

[12] INAF Osservatorio Astron Capodimonte, Via Moiariello 16, I-80131 Naples, Italy

[13] Univ Warsaw, Astron Observ, Al Ujazdowskie 4, PL-00478 Warsaw, Poland

[14] Sednai Sarl, Geneva, Switzerland

[15] European Space Agcy ESA, European Space Astron Ctr ESAC, Camino Bajo Castillo S-N, Villanueva De La Canada 28692, Madrid, Spain

[16] Univ Catania, Dipartimento Fis & Astron Ettore Majorana, Via S Sofia 64, I-95123 Catania, Italy

[17] Tel Aviv Univ, Porter Sch Environm & Earth Sci, IL-6997801 Tel Aviv, Israel

[18] Eotvos Lorand Univ, Inst Phys, Pazmany Peter Setany 1A, H-1117 Budapest, Hungary

[19] Radboud Univ Nijmegen, Dept Astrophys IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands

[20] Max Planck Inst Astron, Konigstuhl 17, D-69117 Heidelberg, Germany

[21] UNED, Dpto Inteligencia Artificial, C Juan Rosal 16, Madrid 28040, Spain

[22] Observ Sauverny, Ecole Polytech Fed Lausanne EPFL, Lab Astrophys, Inst Phys, CH-1290 Versoix, Switzerland

[23] Univ Caen Normandie, Blvd Marechal Juin, F-14032 Caen, France

[24] Konkoly Observ Budapest, MTA CSFK Lendulet Near Field Cosmol Res Grp, MTA Res Ctr Astron & Earth Sci, Konkoly Thege Miklos Ut 15-17, H-1121 Budapest, Hungary

[25] Rudjer Boskovic Inst, Bijenicka Cesta 54, Zagreb 10000, Croatia

[26] Villanova Univ, Dept Astrophys & Planetary Sci, 800 E Lancaster Ave, Villanova, PA 19085 USA

[27] Weizmann Inst Sci, Dept Particle Phys & Astrophys, IL-7610001 Rehovot, Israel

[28] Univ Padua, Dept Phys & Astron G Galilei, Vicolo Osservatorio 3, I-35122 Padua, Italy

[29] Univ Geneva, Inst Global Hlth, Chemin Mines 9, CH-1202 Geneva, Switzerland

来源：

ASTRONOMY & ASTROPHYSICS | 2023年 / 674卷

关键词：

stars: variables: general; Galaxy: stellar content; catalogs; binaries: eclipsing; starspots; stars: oscillations; MAGELLANIC-CLOUD; VARIABLES; DISTANCE;

D O I：

10.1051/0004-6361/202244242

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

Context. Gaia has been in operations since 2014, and two full data releases (DR) have been delivered so far: DR1 in 2016 and DR2 in 2018. The third Gaia data release expands from the early data release (EDR3) in 2020, which contained the five-parameter astrometric solution and mean photometry for 1.8 billion sources by providing 34 months of multi-epoch observations that allowed us to systematically probe, characterise, and classify variable celestial phenomena. Aims. We present a summary of the variability processing and analysis of the photometric and spectroscopic time series of 1.8 billion sources carried out for Gaia DR3. Methods. We used statistical and machine learning methods to characterise and classify the variable sources. Training sets were built from a global revision of major published variable star catalogues. For a subset of classes, specific detailed studies were conducted to confirm their class membership and to derive parameters that are adapted to the peculiarity of the considered class. Results. In total, 10.5 million objects are identified as variable in Gaia DR3 and have associated time series in G, G(BP), and G(RP) and, in some cases, radial velocity time series. The DR3 variable sources subdivide into 9.5 million variable stars and 1 million active galactic nuclei or `quasars'. In addition, supervised classification identified 2.5 million galaxies thanks to spurious variability induced by the extent of these objects. The variability analysis output in the DR3 archive amounts to 17 tables, containing a total of 365 parameters. We publish 35 types and subtypes of variable objects. For 11 variable types, additional specific object parameters are published. Here, we provide an overview of the estimated completeness and contamination of most variability classes. Conclusions. Thanks to Gaia, we present the largest whole-sky variability analysis based on coherent photometric, astrometric, and spectroscopic data. Future Gaia data releases will more than double the span of time series and the number of observations, allowing the publication of an even richer catalogue.

引用

页数：19

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