A&A 595, A2 (2016)
DOI: 10.1051/0004-6361/201629512
c
ESO 2016
Astronomy
&
Astrophysics
Gaia Data Release 1 Special issue
Gaia Data Release 1
Summary of the astrometric, photometric, and survey properties
Gaia Collaboration, A. G. A. Brown
1,
⋆
, A. Vallenari
2
, T. Prusti
3
, J. H.J. de Bruijne
3
, F. Mignard
4
, R. Drimmel
5
,
C. Babusiaux
6
, C. A.L. Bailer-Jones
7
, U. Bastian
8
, M. Biermann
8
, D. W. Evans
9
, L. Eyer
10
, F. Jansen
11
, C. Jordi
12
,
D. Katz
6
, S. A. Klioner
13
, U. Lammers
14
, L. Lindegren
15
, X. Luri
12
, W. O’Mullane
14
, C. Panem
16
, D. Pourbaix
17, 18
,
S. Randich
19
, P. Sartoretti
6
, H. I. Siddiqui
20
, C. Soubiran
21
, V. Valette
16
, F. van Leeuwen
9
, N. A. Walton
9
,
C. Aerts
22, 23
, F. Arenou
6
, M. Cropper
24
, E. Høg
25
, M. G. Lattanzi
5
, E. K. Grebel
8
, A. D. Holland
26
, C. Huc
16
,
X. Passot
16
, M. Perryman
3
, L. Bramante
27
, C. Cacciari
28
, J. Castañeda
12
, L. Chaoul
16
, N. Cheek
29
, F. De Angeli
9
,
C. Fabricius
12
, R. Guerra
14
, J. Hernández
14
, A. Jean-Antoine-Piccolo
16
, E. Masana
12
, R. Messineo
27
, N. Mowlavi
10
,
K. Nienartowicz
30
, D. Ordóñez-Blanco
30
, P. Panuzzo
6
, J. Portell
12
, P. J. Richards
31
, M. Riello
9
, G. M. Seabroke
24
,
P. Tanga
4
, F. Thévenin
4
, J. Torra
12
, S. G. Els
32, 8
, G. Gracia-Abril
32, 12
, G. Comoretto
20
, M. Garcia-Reinaldos
14
,
T. Lock
14
, E. Mercier
32, 8
, M. Altmann
8, 33
, R. Andrae
7
, T. L. Astraatmadja
7
, I. Bellas-Velidis
34
, K. Benson
24
,
J. Berthier
35
, R. Blomme
36
, G. Busso
9
, B. Carry
4, 35
, A. Cellino
5
, G. Clementini
28
, S. Cowell
9
, O. Creevey
4, 37
,
J. Cuypers
36
, M. Davidson
38
, J. De Ridder
22
, A. de Torres
39
, L. Delchambre
40
, A. Dell’Oro
19
, C. Ducourant
21
,
Y. Frémat
36
, M. García-Torres
41
, E. Gosset
40, 18
, J.-L. Halbwachs
42
, N. C. Hambly
38
, D. L. Harrison
9, 43
, M. Hauser
8
,
D. Hestroffer
35
, S. T. Hodgkin
9
, H. E. Huckle
24
, A. Hutton
44
, G. Jasniewicz
45
, S. Jordan
8
, M. Kontizas
46
, A. J. Korn
47
,
A. C. Lanzafame
48, 49
, M. Manteiga
50
, A. Moitinho
51
, K. Muinonen
52, 53
, J. Osinde
54
, E. Pancino
19, 55
, T. Pauwels
36
,
J.-M. Petit
56
, A. Recio-Blanco
4
, A. C. Robin
56
, L. M. Sarro
57
, C. Siopis
17
, M. Smith
24
, K. W. Smith
7
, A. Sozzetti
5
,
W. Thuillot
35
, W. van Reeven
44
, Y. Viala
6
, U. Abbas
5
, A. Abreu Aramburu
58
, S. Accart
59
, J. J. Aguado
57
,
P. M. Allan
31
, W. Allasia
60
, G. Altavilla
28
, M. A. Álvarez
50
, J. Alves
61
, R. I. Anderson
62, 10
, A. H. Andrei
63, 64, 33
,
E. Anglada Varela
54, 29
, E. Antiche
12
, T. Antoja
3
, S. Antón
65, 66
, B. Arcay
50
, N. Bach
44
, S. G. Baker
24
,
L. Balaguer-Núñez
12
, C. Barache
33
, C. Barata
51
, A. Barbier
59
, F. Barblan
10
, D. Barrado y Navascués
67
, M. Barros
51
,
M. A. Barstow
68
, U. Becciani
49
, M. Bellazzini
28
, A. Bello García
69
, V. Belokurov
9
, P. Bendjoya
4
, A. Berihuete
70
,
L. Bianchi
60
, O. Bienaymé
42
, F. Billebaud
21
, N. Blagorodnova
9
, S. Blanco-Cuaresma
10, 21
, T. Boch
42
, A. Bombrun
39
,
R. Borrachero
12
, S. Bouquillon
33
, G. Bourda
21
, H. Bouy
67
, A. Bragaglia
28
, M. A. Breddels
71
, N. Brouillet
21
,
T. Brüsemeister
8
, B. Bucciarelli
5
, P. Burgess
9
, R. Burgon
26
, A. Burlacu
16
, D. Busonero
5
, R. Buzzi
5
, E. Caffau
6
,
J. Cambras
72
, H. Campbell
9
, R. Cancelliere
73
, T. Cantat-Gaudin
2
, T. Carlucci
33
, J. M. Carrasco
12
, M. Castellani
74
,
P. Charlot
21
, J. Charnas
30
, A. Chiavassa
4
, M. Clotet
12
, G. Cocozza
28
, R. S. Collins
38
, G. Costigan
1
, F. Crifo
6
,
N. J.G. Cross
38
, M. Crosta
5
, C. Crowley
39
, C. Dafonte
50
, Y. Damerdji
40, 75
, A. Dapergolas
34
, P. David
35
, M. David
76
,
P. De Cat
36
, F. de Felice
77
, P. de Laverny
4
, F. De Luise
78
, R. De March
27
, D. de Martino
79
, R. de Souza
80
,
J. Debosscher
22
, E. del Pozo
44
, M. Delbo
4
, A. Delgado
9
, H. E. Delgado
57
, P. Di Matteo
6
, S. Diakite
56
, E. Distefano
49
,
C. Dolding
24
, S. Dos Anjos
80
, P. Drazinos
46
, J. Duran
54
, Y. Dzigan
81, 82
, B. Edvardsson
47
, H. Enke
83
, N. W. Evans
9
,
G. Eynard Bontemps
59
, C. Fabre
84
, M. Fabrizio
55, 78
, S. Faigler
85
, A. J. Falcão
86
, M. Farràs Casas
12
, L. Federici
28
,
G. Fedorets
52
, J. Fernández-Hernández
29
, P. Fernique
42
, A. Fienga
87
, F. Figueras
12
, F. Filippi
27
, K. Findeisen
6
,
A. Fonti
27
, M. Fouesneau
7
, E. Fraile
88
, M. Fraser
9
, J. Fuchs
89
, M. Gai
5
, S. Galleti
28
, L. Galluccio
4
, D. Garabato
50
,
F. García-Sedano
57
, A. Garofalo
28
, N. Garralda
12
, P. Gavras
6, 34, 46
, J. Gerssen
83
, R. Geyer
13
, G. Gilmore
9
, S. Girona
90
,
G. Giuffrida
55
, M. Gomes
51
, A. González-Marcos
91
, J. González-Núñez
29, 92
, J. J. González-Vidal
12
, M. Granvik
52
,
A. Guerrier
59
, P. Guillout
42
, J. Guiraud
16
, A. Gúrpide
12
, R. Gutiérrez-Sánchez
20
, L. P. Guy
30
, R. Haigron
6
,
D. Hatzidimitriou
46
, M. Haywood
6
, U. Heiter
47
, A. Helmi
71
, D. Hobbs
15
, W. Hofmann
8
, B. Holl
10
, G. Holland
9
,
J. A.S. Hunt
24
, A. Hypki
1
, V. Icardi
27
, M. Irwin
9
, G. Jevardat de Fombelle
30
, P. Jofré
9, 21
, P. G. Jonker
93, 23
,
A. Jorissen
17
, F. Julbe
12
, A. Karampelas
46, 34
, A. Kochoska
94
, R. Kohley
14
, K. Kolenberg
95, 22, 96
, E. Kontizas
34
,
S. E. Koposov
9
, G. Kordopatis
83, 4
, P. Koubsky
89
, A. Krone-Martins
51
, M. Kudryashova
35
, I. Kull
85
, R. K. Bachchan
15
,
F. Lacoste-Seris
59
, A. F. Lanza
49
, J.-B. Lavigne
59
, C. Le Poncin-Lafitte
33
, Y. Lebreton
6, 97
, T. Lebzelter
61
, S. Leccia
79
,
N. Leclerc
6
, I. Lecoeur-Taibi
30
, V. Lemaitre
59
, H. Lenhardt
8
, F. Leroux
59
, S. Liao
5, 98
, E. Licata
60
,
H. E.P. Lindstrøm
25, 99
, T. A. Lister
100
, E. Livanou
46
, A. Lobel
36
, W. Löffler
8
, M. López
67
, D. Lorenz
61
,
I. MacDonald
38
, T. Magalhães Fernandes
86
, S. Managau
59
, R. G. Mann
38
, G. Mantelet
8
, O. Marchal
6
,
J. M. Marchant
101
, M. Marconi
79
, S. Marinoni
74, 55
, P. M. Marrese
74, 55
, G. Marschalkó
102, 103
, D. J. Marshall
104
,
J. M. Martín-Fleitas
44
, M. Martino
27
, N. Mary
59
, G. Matijevi
ˇ
c
83
, T. Mazeh
85
, P. J. McMillan
15
, S. Messina
49
,
⋆
Corresponding author: A. G. A. Brown, e-mail: brown@strw.leidenuniv.nl
Article published by EDP Sciences A2, page 1 of 23
A&A 595, A2 (2016)
D. Michalik
15
, N. R. Millar
9
, B. M. H. Miranda
51
, D. Molina
12
, R. Molinaro
79
, M. Molinaro
105
, L. Molnár
102
,
M. Moniez
106
, P. Montegriffo
28
, R. Mor
12
, A. Mora
44
, R. Morbidelli
5
, T. Morel
40
, S. Morgenthaler
107
, D. Morris
38
,
A. F. Mulone
27
, T. Muraveva
28
, I. Musella
79
, J. Narbonne
59
, G. Nelemans
23, 22
, L. Nicastro
108
, L. Noval
59
,
C. Ordénovic
4
, J. Ordieres-Meré
109
, P. Osborne
9
, C. Pagani
68
, I. Pagano
49
, F. Pailler
16
, H. Palacin
59
, L. Palaversa
10
,
P. Parsons
20
, M. Pecoraro
60
, R. Pedrosa
110
, H. Pentikäinen
52
, B. Pichon
4
, A. M. Piersimoni
78
, F.-X. Pineau
42
,
E. Plachy
102
, G. Plum
6
, E. Poujoulet
111
, A. Prša
112
, L. Pulone
74
, S. Ragaini
28
, S. Rago
5
, N. Rambaux
35
,
M. Ramos-Lerate
113
, P. Ranalli
15
, G. Rauw
40
, A. Read
68
, S. Regibo
22
, C. Reylé
56
, R. A. Ribeiro
86
, L. Rimoldini
30
,
V. Ripepi
79
, A. Riva
5
, G. Rixon
9
, M. Roelens
10
, M. Romero-Gómez
12
, N. Rowell
38
, F. Royer
6
, L. Ruiz-Dern
6
,
G. Sadowski
17
, T. Sagristà Sellés
8
, J. Sahlmann
14
, J. Salgado
54
, E. Salguero
54
, M. Sarasso
5
, H. Savietto
114
,
M. Schultheis
4
, E. Sciacca
49
, M. Segol
115
, J. C. Segovia
29
, D. Segransan
10
, I.-C. Shih
6
, R. Smareglia
105
, R. L. Smart
5
,
E. Solano
67, 116
, F. Solitro
27
, R. Sordo
2
, S. Soria Nieto
12
, J. Souchay
33
, A. Spagna
5
, F. Spoto
4
, U. Stampa
8
,
I. A. Steele
101
, H. Steidelmüller
13
, C. A. Stephenson
20
, H. Stoev
117
, F. F. Suess
9
, M. Süveges
30
, J. Surdej
40
,
L. Szabados
102
, E. Szegedi-Elek
102
, D. Tapiador
118, 119
, F. Taris
33
, G. Tauran
59
, M. B. Taylor
120
, R. Teixeira
80
,
D. Terrett
31
, B. Tingley
121
, S. C. Trager
71
, C. Turon
6
, A. Ulla
122
, E. Utrilla
44
, G. Valentini
78
, A. van Elteren
1
,
E. Van Hemelryck
36
, M. van Leeuwen
9
, M. Varadi
10, 102
, A. Vecchiato
5
, J. Veljanoski
71
, T. Via
72
, D. Vicente
90
,
S. Vogt
123
, H. Voss
12
, V. Votruba
89
, S. Voutsinas
38
, G. Walmsley
16
, M. Weiler
12
, K. Weingrill
83
, T. Wevers
23
,
Ł. Wyrzykowski
9, 124
, A. Yoldas
9
, M. Žerjal
94
, S. Zucker
81
, C. Zurbach
45
, T. Zwitter
94
, A. Alecu
9
, M. Allen
3
,
C. Allende Prieto
24, 125, 126
, A. Amorim
51
, G. Anglada-Escudé
12
, V. Arsenijevic
51
, S. Azaz
3
, P. Balm
20
, M. Beck
30
,
H.-H. Bernstein
†,8
, L. Bigot
4
, A. Bijaoui
4
, C. Blasco
127
, M. Bonfigli
78
, G. Bono
74
, S. Boudreault
24, 128
, A. Bressan
129
,
S. Brown
9
, P.-M. Brunet
16
, P. Bunclark
†,9
, R. Buonanno
74
, A. G. Butkevich
13
, C. Carret
110
, C. Carrion
57
,
L. Chemin
21, 130
, F. Chéreau
6
, L. Corcione
5
, E. Darmigny
16
, K. S. de Boer
131
, P. de Teodoro
29
, P. T. de Zeeuw
1, 132
,
C. Delle Luche
6, 59
, C. D. Domingues
133
, P. Dubath
30
, F. Fodor
16
, B. Frézouls
16
, A. Fries
12
, D. Fustes
50
, D. Fyfe
68
,
E. Gallardo
12
, J. Gallegos
29
, D. Gardiol
5
, M. Gebran
12, 134
, A. Gomboc
94, 135
, A. Gómez
6
, E. Grux
56
, A. Gueguen
6, 136
,
A. Heyrovsky
38
, J. Hoar
14
, G. Iannicola
74
, Y. Isasi Parache
12
, A.-M. Janotto
16
, E. Joliet
39, 137
, A. Jonckheere
36
,
R. Keil
138, 139
, D.-W. Kim
7
, P. Klagyivik
102
, J. Klar
83
, J. Knude
25
, O. Kochukhov
47
, I. Kolka
140
, J. Kos
94, 141
,
A. Kutka
89, 142
, V. Lainey
35
, D. LeBouquin
59
, C. Liu
7, 143
, D. Loreggia
5
, V. V. Makarov
144
, M. G. Marseille
59
,
C. Martayan
36, 145
, O. Martinez-Rubi
12
, B. Massart
4, 59, 146
, F. Meynadier
6, 33
, S. Mignot
6
, U. Munari
2
, A.-T. Nguyen
16
,
T. Nordlander
47
, P. Ocvirk
83, 42
, K. S. O’Flaherty
147
, A. Olias Sanz
148
, P. Ortiz
68
, J. Osorio
65
, D. Oszkiewicz
52, 149
,
A. Ouzounis
38
, M. Palmer
12
, P. Park
10
, E. Pasquato
17
, C. Peltzer
9
, J. Peralta
12
, F. Péturaud
6
, T. Pieniluoma
52
,
E. Pigozzi
27
, J. Poels
†,40
, G. Prat
150
, T. Prod’homme
1, 151
, F. Raison
152, 136
, J. M. Rebordao
133
, D. Risquez
1
,
B. Rocca-Volmerange
153
, S. Rosen
24, 68
, M. I. Ruiz-Fuertes
30
, F. Russo
5
, S. Sembay
68
, I. Serraller Vizcaino
154
,
A. Short
3
, A. Siebert
42, 83
, H. Silva
86
, D. Sinachopoulos
34
, E. Slezak
4
, M. Soffel
13
, D. Sosnowska
10
, V. Straižys
155
,
M. ter Linden
39, 156
, D. Terrell
157
, S. Theil
158
, C. Tiede
7, 159
, L. Troisi
55, 160
, P. Tsalmantza
7
, D. Tur
72
, M. Vaccari
161, 162
,
F. Vachier
35
, P. Valles
12
, W. Van Hamme
163
, L. Veltz
83, 37
, J. Virtanen
52, 53
, J.-M. Wallut
16
, R. Wichmann
164
,
M. I. Wilkinson
9, 68
, H. Ziaeepour
56
, and S. Zschocke
13
(Affiliations can be found after the references)
Received 10 August 2016 / Accepted 31 August 2016
ABSTRACT
Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry
for over 1 billion sources brighter than magnitude 20.7.
Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations
due to the preliminary nature of this release.
Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis
Consortium (DPAC) and turned into an astrometric and photometric catalogue.
Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions
for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric
Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is
the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid
and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the
typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr
−1
for the proper motions. A systematic component of
∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 Hipparcos stars in the primary data set, the proper motions are
much more precise at about 0.06 mas yr
−1
. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median
uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7.
Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources.
Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that
underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important
limitations to the data quality which should be carefully considered before drawing conclusions from the data.
Key words catalogs – astrometry – parallaxes – proper motions – surveys
A2, page 2 of
23
Gaia Collaboration (Brown, A. G. A., et al.): Gaia Data Release 1
1. Introduction
The Gaia satellite was launched at the end of 2013 to collect
data that will allow the determination of highly accurate po-
sitions, parallaxes, and proper motions for >1 billion sources
brighter than magnitude 20.7 in the white-light photometric
band G of Gaia (thus going deeper than the originally planned
limit of G = 20). The astrometry is complemented by multi-
colour photometry, measured for all sources observed by Gaia,
and radial velocities which are collected for stars brighter than
G ≈ 17. The scientific goals of the mission are summarised
in Gaia Collaboration (2016b), while a more extensive scientific
motivation for the mission is presented in
Perryman et al. (2001).
The spacecraft, its scientific instruments, and the observ-
ing strategy have been designed to meet the performance re-
quirement of 24 µas accuracy on the parallax of a 15th mag-
nitude solar-type star at the end of the nominal 5 yr mission life-
time. The entity entrusted with the data processing for the Gaia
mission, the Gaia Data Processing and Analysis Consortium
(DPAC, described in Gaia Collaboration 2016b), is expected to
deliver the final data products (at their ultimately achievable ac-
curacy) only at the end of post-operational phase of the mission,
currently foreseen for 2022–2023. It was therefore agreed at the
time of the creation of DPAC that the astronomical community
should have access to the Gaia data at an earlier stage through
intermediate data releases. It was understood that these interme-
diate releases are based on preliminary calibrations and only on
a subset of the measurements available at the end of the mission,
and therefore will not be representative of the end-of-mission
Gaia performance.
In this paper we present the first such intermediate Gaia data
release (Gaia Data Release 1, Gaia DR1), which is based on the
data collected during the first 14 months of the nominal mission
lifetime (60 months). In Sect.
2 we provide a short summary of
the Gaia instruments and the way the data are collected. We sum-
marise the astrometric, photometric and variable star contents of
Gaia DR1 in Sect. 3. A summary of the validation of the re-
sults is provided in Sect. 4 and a few illustrations of the contents
of Gaia DR1 are provided in Sect.
5. The known limitations of
this first release are presented in Sect. 6. In Sect. 7 we provide
pointers to the Gaia DR1 data access facilities and documenta-
tion available to the astronomical community. We conclude in
Sect. 8. Although Gaia DR1 is the first major catalogue release
with results from the Gaia mission, Gaia data has already been
made publicly available as “Science Alerts” on transient sources,
which for example led to the discovery of only the third known
eclipsing AM CVn-system (
Campbell et al. 2015).
We stress at the outset that Gaia DR1 represents a prelimi-
nary release of Gaia results with many shortcomings. We there-
fore strongly encourage a detailed reading of Sect. 6 and the
documentation associated with the release as well as carefully
taking into account the listed limitations when drawing conclu-
sions based on the data contained in Gaia DR1.
2. Gaia instruments and measurements
We provide a brief overview of the Gaia instruments and the way
measurements are collected in order to introduce some of the
technical terms used in the rest of the paper. A full description
of the Gaia spacecraft, instruments, and measurement principles
can be found in
Gaia Collaboration (2016b).
Gaia continuously scans the sky with two telescopes point-
ing in directions separated by the basic angle of 106.5
◦
. The
images produced by the telescopes are projected onto the same
focal plane composed of 106 CCDs which function as the detec-
tors of the various instruments in the Gaia payload. The scanning
is achieved through the continuous revolution of Gaia about its
spin axis with a period of 6 h. The spin axis direction precesses
around the direction to the Sun (as seen from Gaia), which al-
lows complete coverage of the sky. Statistics of the sky coverage
achieved for Gaia DR1 are presented in
Lindegren et al. (2016)
and
van Leeuwen et al. (2016), while the properties of the Gaia
scanning law with respect to variable star studies are described
in Eyer et al. (2016).
The spinning motion of the spacecraft results in the source
images moving across the focal plane. This necessitates the oper-
ation of the Gaia CCDs in time-delayed integration (TDI) mode
so as to allow the accumulation of charge as the images move
across the CCDs. The CCDs are not fully read out, only the pix-
els in a “window” around each source are read out and stored
for transmission to the ground. These windows come in various
sizes and sampling schemes.
The astrometric instrument takes up most of the focal
plane and collects source images in the Gaia white-light pass
band G (covering the range 330–1050 nm, Carrasco et al. 2016;
Jordi et al. 2010). The fundamental inputs to the astrometric data
processing consist of the precise times when the image centroids
pass a fiducial line on the CCD (Lindegren et al. 2012). The im-
age centroid and the flux contained in the image are determined
as part of the pre-processing (Fabricius et al. 2016). The sensi-
tivity of the astrometric instrument is such that sources brighter
than about G = 12 will lead to saturated images. This effect is
mitigated through the use of TDI gates, which are special struc-
tures on the CCDs that can be activated to inhibit charge transfer
and hence to effectively reduce the integration time for bright
sources.
The photometric instrument is realised through two prisms
dispersing the light entering the field of view of two dedicated
sets of CCDs. The Blue Photometer (BP) operates over the wave-
length range 330–680 nm, while the Red Photometer (RP) cov-
ers the wavelength range 640–1050 nm (
Carrasco et al. 2016;
Jordi et al. 2010). The data collected by the photometric instru-
ment consists of low resolution spectrophotometric measure-
ments of the source spectral energy distributions. This colour
information is intended for use in the astrometric processing (to
correct for chromatic effects) and to provide the astrophysical
characterisation of all sources observed by Gaia. The G-band
photometry is derived from the fluxes measured in the astromet-
ric instrument. Results from the photometric instrument are not
presented as part of Gaia DR1. The photometry in this first re-
lease only concerns the fluxes measured in the G band.
The spectroscopic instrument, also called the radial-velocity
spectrometer (RVS) collects medium resolution (R ∼ 11 700)
spectra over the wavelength range 845–872 nm, centred on the
Calcium triplet region (
Cropper & Katz 2011). The spectra are
collected for all sources to G ≈ 17 (16th magnitude in the
RVS filter band) and serve primarily to determine the radial ve-
locity of the sources, although at the bright end (G < 12.5,
Recio-Blanco et al. 2016) astrophysical information can be de-
rived directly from the spectra. Results from this instrument are
not contained in Gaia DR1.
Observations of sources by Gaia can be referred to in sev-
eral ways. “Focal plane transits” refer to a crossing of the entire
focal plane by a given source, which corresponds to a “visit” by
Gaia of a specific coordinate on the sky. “CCD transits” refer to
the crossing by a source of a particular CCD in the focal plane.
Thus the focal plane transit of the astrometric field typically con-
sists of 10 transits across individual CCDs, while a photometric
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A&A 595, A2 (2016)
instrument transit (BP or RP) consists of only one CCD transit,
and a transit across the RVS instrument consists of three CCD
transits (see
Gaia Collaboration 2016b; Crowley et al. 2016b, for
more details on the focal plane layout and functionalities, and
the in-flight performance of the Gaia CCDs). This distinction is
important when it comes to the difference between the number
of measurements (CCD transits) collected for a source and the
number of times it was observed (focal plane transits) by Gaia.
In the rest of the paper we will refer to an “observation” or a
“focal plane transit” to indicate that a source was observed by
Gaia and we refer to “CCD transit” whenever individual CCD
measurements are discussed.
Events on board Gaia are labelled by the so-called on board
mission time line (OBMT), which is a time scale defined by the
on board clock. This time scale is eventually transformed into the
physical barycentric coordinate time (TCB) (Gaia Collaboration
2016b; Lindegren et al. 2016). By convention OBMT is ex-
pressed in units of 6 h (21 600 s) spacecraft revolutions since
launch and this unit is often used in figures of some quantity ver-
sus time, including in the papers accompanying Gaia DR1 and
in the data release documentation (see Sect.
7). For the practical
interpretation of time lines expressed in OBMT the following ap-
proximate relation between the OBMT (in revolutions) and TCB
at Gaia (in Julian years) can be used:
TCB ≃ J2015.0 + (OBMT − 1717.6256 rev)/(1461 rev). (1)
This relation is precise to ±2 s and is valid only for
the time span corresponding to Gaia DR1. The time in-
terval covered by the observations used for Gaia DR1
starts at OBMT 1078.3795 rev = J2014.5624599 TCB (ap-
proximately 2014 July 25, 10:30:00 UTC), and ends at
OBMT 2751.3518 rev = J2015.7075471 TCB (approximately
2015 September 16, 16:20:00 UTC), thus spanning 418 days.
This time interval contains a significant number of gaps which
are caused by: events or operations on board Gaia that pre-
vent the collection of data or make the raw data unusable for a
while (such as the decontamination of the payload); problems in
the pre-processing leading to effective gaps in the available raw
Gaia data (which has to be reconstructed from the raw teleme-
try,
Fabricius et al. 2016); gaps in the spacecraft attitude solution
deliberately introduced around the times when micro-meteoroid
hits occurred (Lindegren et al. 2016). Telemetry losses along the
spacecraft to ground link are only a very minor contribution to
the data gaps. As a result of these gaps the amount of data pro-
cessed for Gaia DR1 comprises slightly less than 12 (out of the
above mentioned 14) months. The data gaps inevitably affect the
quality of the Gaia DR1 results. In future releases the gaps re-
lated to the on-ground processing will disappear.
3. Overview of the contents of
Gaia DR1
Gaia DR1 contains astrometry, G-band photometry, and a
modest number of variable star light curves, for a total of
1 142 679 769 sources. Basic statistics for Gaia DR1 are listed
in Table
1. The three main components of Gaia DR1 are:
1. The astrometric data set which consists of two subsets:
The primary astrometric data set contains the positions,
parallaxes, and mean proper motions for 2 057 050 stars
in common between the Gaia DR1, Hipparcos and Ty-
cho-2 catalogues. This data set represents the realisation of
the Tycho-Gaia astrometric solution (TGAS), of which the
principles were outlined and demonstrated in
Michalik et al.
Table 1. Basic statistics on the contents of Gaia DR1.
Source numbers
Total number of sources 1 142 679 769
No. of primary (TGAS) sources 2 057 050
Hipparcos 93 635
Tycho-2 (excluding Hipparcos stars) 1 963 415
No. of secondary sources 1 140 622 719
No. of sources with light curves 3194
Cepheids 599
RR Lyrae 2595
Magnitude distribution percentiles (G)
0.135% 11.2
2.275% 14.5
15.866% 17.1
50% 19.0
84.134% 20.1
97.725% 20.7
99.865% 21.0
(2015). The typical uncertainty is about 0.3 mas for the po-
sitions, and about 1 mas yr
−1
for the proper motions. For the
subset of 93 635 Hipparcos stars in the primary astrometric
data set the proper motions are much more precise, at about
0.06 mas yr
−1
. The typical uncertainty for the parallaxes is
0.3 mas, where it should be noted that a systematic compo-
nent of ∼0.3 mas should be added (see Sect. 6).
The secondary astrometric data set contains the positions for
an additional 1 140 622 719 sources. For the secondary data
set the typical uncertainty on the positions is ∼10 mas.
The positions and proper motions are given in a refer-
ence frame that is aligned with the International Celestial
Reference Frame (ICRF) to better than 0.1 mas at epoch
J2015.0, and non-rotating with respect to ICRF to within
0.03 mas yr
−1
. The detailed description of the production of
the astrometric solution, as well as a more detailed statistical
summary of the astrometry contained in Gaia DR1 can be
found in
Lindegren et al. (2016). An in-depth discussion of
the Gaia DR1 reference frame and the optical properties of
ICRF sources is presented in Mignard et al. (2016).
2. The photometric data set contains the mean Gaia G-band
magnitudes for all the sources contained in Gaia DR1.
The brightest source in Gaia DR1 has a magnitude G =
3.2, while the majority of the sources (99.7%) are in the
range 11.2 ≤ G ≤ 21. The small fraction of sources at
G > 21 (where the nominal survey limit is G = 20.7,
Gaia Collaboration 2016b) most likely have erroneously de-
termined G-band fluxes, but nevertheless passed the data
quality filters described in Sect. 4. The typical uncertainties
quoted on the mean value of G range from a milli-magnitude
or better at the bright end (G . 13), to about 0.03 mag at the
survey limit. The details of the photometric data set, includ-
ing the data processing and validation of the results is de-
scribed in
van Leeuwen et al. (2016), Carrasco et al. (2016),
Riello et al. (2016), Evans et al. (2016).
3. The Cepheids and RR Lyrae data set contains the G-band
light curves and characteristics of a modest sample of
599 Cepheid (43 newly discovered) and 2595 RR Lyrae
(343 new) variables located around the south ecliptic pole
and observed at high cadence during a special scanning
period in the first four weeks of the operational phase of
A2, page 4 of
23
Gaia Collaboration (Brown, A. G. A., et al.): Gaia Data Release 1
4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 2 2 2 4
Mean G [mag]
1
1 0
100
1000
1e4
1e5
1e6
1e7
Number
Gaia DR1
Tycho-2 (Excl. Hip)
Hipparcos
Fig. 1. Distribution of the mean values of G for all Gaia DR1 sources
shown as histograms with 0.1 mag wide bins. The distributions for the
Hipparcos and Tycho-2 (excluding the Hipparcos stars) subsets are
also shown. Note the lack of bright sources at G . 7.
Gaia. The variable star contents of Gaia DR1 are described
in detail in
Eyer et al. (2016) and Clementini et al. (2016).
The distribution of the sources in magnitude is shown in Fig.
1.
The magnitude distribution of the sources reveals a drop-off at
G . 7. Neither all Hipparcos nor all Tycho-2 sources are in-
cluded in Gaia DR1 and at the faint end the magnitude limit
is sky position dependent and ill-defined. At magnitudes be-
low G ∼ 5 the total number of sources in Gaia DR1 is larger
than the number of Hipparcos sources in Gaia DR1. This is
however only apparent as most of these sources are in fact in
common with the Hipparcos catalogue but have been treated
as secondary astrometric sources, because a good 5-parameter
astrometric solution could not be derived. The limitations of
Gaia DR1, including its completeness, are discussed in Sect.
6.
Of the 1141 million sources in the secondary astrometric
data set 685 million are in common with the Initial Gaia Source
List (IGSL,
Smart & Nicastro 2014) and 456 million are new
sources (Lindegren et al. 2016). The IGSL formed the starting
point for the process of assigning Gaia observations to sources
(Fabricius et al. 2016). Hence the term “new” should strictly
speaking be interpreted as referring to sources that could not be
matched to known IGSL sources. No attempt was made to estab-
lish how many sources are truly new discoveries by Gaia but this
is likely to be a substantial fraction (over 400 million) of the new
sources mentioned above. The IGSL has been publicly available
for some time and we caution that when looking up a source in
Gaia DR1 through its already known IGSL source identifier, it
should be kept in mind that a large fraction of the 1.2 billion
sources in the IGSL does not appear in Gaia DR1.
4.
Gaia DR1 validation and source filtering
A substantial effort was dedicated to the validation of the results
contained in Gaia DR1. This is a complex task which takes place
at various levels within the DPAC. The outputs produced by the
DPAC subsystems (described in
Gaia Collaboration 2016b) are
validated first through an “internal” quality control process. For
the astrometric data set in Gaia DR1 this internal validation is
described in Lindegren et al. (2016), while that for the photomet-
ric and variable star data sets is described in
Evans et al. (2016)
and Eyer et al. (2016), respectively. A second validation stage is
carried out by the DPAC unit responsible for the data publica-
tion (cf. Gaia Collaboration 2016b), which examines all the data
contained in Gaia DR1 together and thus provides an indepen-
dent quality check. This global validation process is described
in
Arenou et al. (2016). Here we summarise only the most im-
portant findings from the validation and provide complementary
illustrations of the quality of Gaia DR1 in Sect. 5.
Numerous tests were done during the validation stage of the
Gaia DR1 production, ranging from basic consistency checks
on the data values to the verification that the data is scientifi-
cally correct. No problems were revealed that would prevent the
timely publication of Gaia DR1. However, a number of minor
problems were found that have been addressed either by a filter-
ing of the available DPAC outputs before their incorporation into
the data release, or by documenting the issues found as known
limitations to Gaia DR1 (see Sect.
6). The filtering applied to
the astrometric and photometric processing outputs before the
global validation stage was as follows:
– For the primary astrometric data set only sources for which
the standard uncertainties on the parallaxes and positions are
less than 1 mas and 20 mas, respectively, were kept. In ad-
dition it was required that the sources have valid photomet-
ric data. For the secondary astrometric data set the sources
were filtered by requiring that they were observed by Gaia
at least 5 times (i.e. at least 5 focal plane transits), and that
their astrometric excess noise (which indicates the astromet-
ric modelling errors for a specific source) and position stan-
dard uncertainty are less than 20 mas and 100 mas, respec-
tively. More details can be found in
Lindegren et al. (2016).
We stress that no filtering was done on the actual value of the
source astrometric parameters.
– Although the photometric results were not explicitly filtered
before their incorporation into Gaia DR1, a number of filters
internal to the photometric data processing effectively leads
to filtering at the source level. In particular sources with ex-
tremely blue or red colours will not appear in Gaia DR1.
– The only filtering done on the outputs of the variable star
processing was to remove a handful of sources that were very
likely a duplicate of some other source (see below for more
discussion on duplicate sources).
The second validation stage (
Arenou et al. 2016) revealed the
following problems that were addressed through a further filter-
ing of the astrometric and photometric processing outputs before
their final incorporation into Gaia DR1. The filters described be-
low were thus applied after the filters above.
– Some 37 million source pairs were found which are sepa-
rated by less than 1 Gaia focal plane pixel size on the sky
(i.e. 59 mas), or are separated by less than 5 times their
combined positional standard uncertainty (where the factor
5 accounts for a possible underestimation of the standard un-
certainties). The vast majority of these pairs are created dur-
ing the cross-match stage, when observations (focal plane
transits) get grouped together and assigned to sources (see
Fabricius et al. 2016). The main underlying cause is sources
appearing twice in the IGSL, which was evident from the
many close pairs occurring along photographic survey plate
boundaries (the IGSL is based to a large extent on photo-
graphic surveys, Smart & Nicastro 2014). A large fraction of
these pairs are likely to be two instances of the same phys-
ical source (i.e. the source appears twice in the Gaia source
list with two different identifiers). One member of each of
these close pairs was filtered out of the Gaia DR1 source list
and the remaining sources were flagged as having a dupli-
cate associated to them in the Gaia source list. This flag thus
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