of 20
Low-latency Gravitational-wave Alerts for Multimessenger Astronomy during the
Second Advanced LIGO and Virgo Observing Run
B. P. Abbott
1
, R. Abbott
1
, T. D. Abbott
2
, S. Abraham
3
, F. Acernese
4
,
5
, K. Ackley
6
, C. Adams
7
, R. X. Adhikari
1
, V. B. Adya
8
,
9
,
C. Affeldt
8
,
9
, M. Agathos
10
, K. Agatsuma
11
, N. Aggarwal
12
, O. D. Aguiar
13
, L. Aiello
14
,
15
, A. Ain
3
, P. Ajith
16
, G. Allen
17
,
A. Allocca
18
,
19
, M. A. Aloy
20
, P. A. Altin
21
, A. Amato
22
, A. Ananyeva
1
, S. B. Anderson
1
, W. G. Anderson
23
, S. V. Angelova
24
,
S. Antier
25
, S. Appert
1
, K. Arai
1
, M. C. Araya
1
, J. S. Areeda
26
, M. Arène
27
, N. Arnaud
25
,
28
, S. Ascenzi
29
,
30
, G. Ashton
6
,
S. M. Aston
7
, P. Astone
31
, F. Aubin
32
, P. Aufmuth
9
, K. AultONeal
33
, C. Austin
2
, V. Avendano
34
, A. Avila-Alvarez
26
,
S. Babak
27
,
35
, P. Bacon
27
, F. Badaracco
14
,
15
, M. K. M. Bader
36
, S. Bae
37
, P. T. Baker
38
, F. Baldaccini
39
,
40
, G. Ballardin
28
,
S. W. Ballmer
41
, S. Banagiri
42
, J. C. Barayoga
1
, S. E. Barclay
43
, B. C. Barish
1
, D. Barker
44
, K. Barkett
45
, S. Barnum
12
, F. Barone
4
,
5
,
B. Barr
43
, L. Barsotti
12
, M. Barsuglia
27
, D. Barta
46
, J. Bartlett
44
, I. Bartos
47
, R. Bassiri
48
, A. Basti
18
,
19
, M. Bawaj
40
,
49
,
J. C. Bayley
43
, M. Bazzan
50
,
51
, B. Bécsy
52
, M. Bejger
27
,
53
, I. Belahcene
25
, A. S. Bell
43
, D. Beniwal
54
, B. K. Berger
48
,
G. Bergmann
8
,
9
, S. Bernuzzi
55
,
56
, J. J. Bero
57
, C. P. L. Berry
58
, D. Bersanetti
59
, A. Bertolini
36
, J. Betzwieser
7
, R. Bhandare
60
,
J. Bidler
26
, I. A. Bilenko
61
, S. A. Bilgili
38
, G. Billingsley
1
, J. Birch
7
, R. Birney
24
, O. Birnholtz
57
, S. Biscans
1
,
12
, S. Biscoveanu
6
,
A. Bisht
9
, M. Bitossi
19
,
28
, M. A. Bizouard
25
, J. K. Blackburn
1
, C. D. Blair
7
, D. G. Blair
62
, R. M. Blair
44
, S. Bloemen
63
, N. Bode
8
,
9
,
M. Boer
64
, Y. Boetzel
65
, G. Bogaert
64
, F. Bondu
66
, E. Bonilla
48
, R. Bonnand
32
, P. Booker
8
,
9
, B. A. Boom
36
, C. D. Booth
67
,
R. Bork
1
, V. Boschi
28
, S. Bose
3
,
68
, K. Bossie
7
, V. Bossilkov
62
, J. Bosveld
62
, Y. Bouffanais
27
, A. Bozzi
28
, C. Bradaschia
19
,
P. R. Brady
23
, A. Bramley
7
, M. Branchesi
14
,
15
, J. E. Brau
69
, T. Briant
70
, J. H. Briggs
43
, F. Brighenti
71
,
72
, A. Brillet
64
,
M. Brinkmann
8
,
9
, V. Brisson
25
,
178
, P. Brockill
23
, A. F. Brooks
1
, D. D. Brown
54
, S. Brunett
1
, A. Buikema
12
, T. Bulik
73
,
H. J. Bulten
36
,
74
, A. Buonanno
35
,
75
, D. Buskulic
32
, C. Buy
27
, R. L. Byer
48
, M. Cabero
8
,
9
, L. Cadonati
76
, G. Cagnoli
22
,
77
,
C. Cahillane
1
, J. Calderón Bustillo
6
, T. A. Callister
1
, E. Calloni
5
,
78
, J. B. Camp
79
, W. A. Campbell
6
, M. Canepa
59
,
80
,
K. C. Cannon
81
, H. Cao
54
, J. Cao
82
, E. Capocasa
27
, F. Carbognani
28
, S. Caride
83
, M. F. Carney
58
, G. Carullo
18
,
J. Casanueva Diaz
19
, C. Casentini
29
,
30
, S. Caudill
36
, M. Cavaglià
84
, F. Cavalier
25
, R. Cavalieri
28
, G. Cella
19
, P. Cerdá-Durán
20
,
G. Cerretani
18
,
19
, E. Cesarini
30
,
85
, O. Chaibi
64
, K. Chakravarti
3
, S. J. Chamberlin
86
, M. Chan
43
, S. Chao
87
, P. Charlton
88
,
E. A. Chase
58
, E. Chassande-Mottin
27
, D. Chatterjee
23
, M. Chaturvedi
60
, B. D. Cheeseboro
38
, H. Y. Chen
89
, X. Chen
62
, Y. Chen
45
,
H.-P. Cheng
47
, C. K. Cheong
90
, H. Y. Chia
47
, A. Chincarini
59
, A. Chiummo
28
, G. Cho
91
,H.S.Cho
92
, M. Cho
75
,
N. Christensen
64
,
93
, Q. Chu
62
, S. Chua
70
, K. W. Chung
90
, S. Chung
62
, G. Ciani
50
,
51
, A. A. Ciobanu
54
, R. Ciol
fi
94
,
95
, F. Cipriano
64
,
A. Cirone
59
,
80
, F. Clara
44
, J. A. Clark
76
, P. Clearwater
96
, F. Cleva
64
, C. Cocchieri
84
, E. Coccia
14
,
15
, P.-F. Cohadon
70
, D. Cohen
25
,
R. Colgan
97
, M. Colleoni
98
, C. G. Collette
99
, C. Collins
11
, L. R. Cominsky
100
, M. Constancio, Jr.
13
, L. Conti
51
, S. J. Cooper
11
,
P. Corban
7
, T. R. Corbitt
2
, I. Cordero-Carrión
101
, K. R. Corley
97
, N. Cornish
52
, A. Corsi
83
, S. Cortese
28
, C. A. Costa
13
, R. Cotesta
35
,
M. W. Coughlin
1
, S. B. Coughlin
58
,
67
, J.-P. Coulon
64
, S. T. Countryman
97
, P. Couvares
1
, P. B. Covas
98
, E. E. Cowan
76
,
D. M. Coward
62
, M. J. Cowart
7
, D. C. Coyne
1
, R. Coyne
102
, J. D. E. Creighton
23
, T. D. Creighton
103
, J. Cripe
2
, M. Croquette
70
,
S. G. Crowder
104
, T. J. Cullen
2
, A. Cumming
43
, L. Cunningham
43
, E. Cuoco
28
, T. Dal Canton
79
, G. Dálya
105
, S. L. Danilishin
8
,
9
,
S. D
Antonio
30
, K. Danzmann
8
,
9
, A. Dasgupta
106
, C. F. Da Silva Costa
47
, L. E. H. Datrier
43
, V. Dattilo
28
, I. Dave
60
, M. Davier
25
,
D. Davis
41
, E. J. Daw
107
, D. DeBra
48
, M. Deenadayalan
3
, J. Degallaix
22
, M. De Laurentis
5
,
78
, S. Deléglise
70
, W. Del Pozzo
18
,
19
,
L. M. DeMarchi
58
, N. Demos
12
, T. Dent
8
,
9
,
108
, R. De Pietri
56
,
109
, J. Derby
26
, R. De Rosa
5
,
78
, C. De Rossi
22
,
28
, R. DeSalvo
110
,
O. de Varona
8
,
9
, S. Dhurandhar
3
, M. C. Díaz
103
, T. Dietrich
36
, L. Di Fiore
5
, M. Di Giovanni
95
,
111
, T. Di Girolamo
5
,
78
,
A. Di Lieto
18
,
19
, B. Ding
99
, S. Di Pace
31
,
112
, I. Di Palma
31
,
112
, F. Di Renzo
18
,
19
, A. Dmitriev
11
, Z. Doctor
89
, F. Donovan
12
,
K. L. Dooley
67
,
84
, S. Doravari
8
,
9
, I. Dorrington
67
, T. P. Downes
23
, M. Drago
14
,
15
, J. C. Driggers
44
,Z.Du
82
, J.-G. Ducoin
25
,
P. Dupej
43
, S. E. Dwyer
44
, P. J. Easter
6
, T. B. Edo
107
, M. C. Edwards
93
,A.Ef
fl
er
7
, P. Ehrens
1
, J. Eichholz
1
, S. S. Eikenberry
47
,
M. Eisenmann
32
, R. A. Eisenstein
12
, R. C. Essick
89
, H. Estelles
98
, D. Estevez
32
, Z. B. Etienne
38
, T. Etzel
1
, M. Evans
12
,
T. M. Evans
7
, V. Fafone
14
,
29
,
30
, H. Fair
41
, S. Fairhurst
67
, X. Fan
82
, S. Farinon
59
, B. Farr
69
, W. M. Farr
11
, E. J. Fauchon-Jones
67
,
M. Favata
34
, M. Fays
107
, M. Fazio
113
, C. Fee
114
, J. Feicht
1
, M. M. Fejer
48
, F. Feng
27
, A. Fernandez-Galiana
12
, I. Ferrante
18
,
19
,
E. C. Ferreira
13
, T. A. Ferreira
13
, F. Ferrini
28
, F. Fidecaro
18
,
19
, I. Fiori
28
, D. Fiorucci
27
, M. Fishbach
89
, R. P. Fisher
41
,
115
,
J. M. Fishner
12
, M. Fitz-Axen
42
, R. Flaminio
32
,
116
, M. Fletcher
43
, E. Flynn
26
, H. Fong
117
, J. A. Font
20
,
118
, P. W. F. Forsyth
21
,
J.-D. Fournier
64
, S. Frasca
31
,
112
, F. Frasconi
19
, Z. Frei
105
, A. Freise
11
, R. Frey
69
, V. Frey
25
, P. Fritschel
12
, V. V. Frolov
7
, P. Fulda
47
,
M. Fyffe
7
, H. A. Gabbard
43
, B. U. Gadre
3
, S. M. Gaebel
11
, J. R. Gair
119
, L. Gammaitoni
39
, M. R. Ganija
54
, S. G. Gaonkar
3
,
A. Garcia
26
, C. García-Quirós
98
, F. Garu
fi
5
,
78
, B. Gateley
44
, S. Gaudio
33
, G. Gaur
120
, V. Gayathri
121
, G. Gemme
59
, E. Genin
28
,
A. Gennai
19
, D. George
17
, J. George
60
, L. Gergely
122
, V. Germain
32
, S. Ghonge
76
, Abhirup Ghosh
16
, Archisman Ghosh
36
,
S. Ghosh
23
, B. Giacomazzo
95
,
111
, J. A. Giaime
2
,
7
, K. D. Giardina
7
, A. Giazotto
19
,
179
, K. Gill
33
, G. Giordano
4
,
5
, L. Glover
110
,
P. Godwin
86
, E. Goetz
44
, R. Goetz
47
, B. Goncharov
6
, G. González
2
, J. M. Gonzalez Castro
18
,
19
, A. Gopakumar
123
,
M. L. Gorodetsky
61
, S. E. Gossan
1
, M. Gosselin
28
, R. Gouaty
32
, A. Grado
5
,
124
, C. Graef
43
, M. Granata
22
, A. Grant
43
, S. Gras
12
,
P. Grassia
1
, C. Gray
44
, R. Gray
43
, G. Greco
71
,
72
, A. C. Green
11
,
47
, R. Green
67
, E. M. Gretarsson
33
, P. Groot
63
, H. Grote
67
,
S. Grunewald
35
, P. Gruning
25
, G. M. Guidi
71
,
72
, H. K. Gulati
106
, Y. Guo
36
, A. Gupta
86
, M. K. Gupta
106
, E. K. Gustafson
1
,
R. Gustafson
125
, L. Haegel
98
, O. Halim
14
,
15
, B. R. Hall
68
, E. D. Hall
12
, E. Z. Hamilton
67
, G. Hammond
43
, M. Haney
65
,
The Astrophysical Journal,
875:161
(
20pp
)
, 2019 April 20
https:
//
doi.org
/
10.3847
/
1538-4357
/
ab0e8f
© 2019. The American Astronomical Society.
1
M. M. Hanke
8
,
9
, J. Hanks
44
, C. Hanna
86
, O. A. Hannuksela
90
, J. Hanson
7
, T. Hardwick
2
, K. Haris
16
, J. Harms
14
,
15
, G. M. Harry
126
,
I. W. Harry
35
, C.-J. Haster
117
, K. Haughian
43
, F. J. Hayes
43
, J. Healy
57
, A. Heidmann
70
, M. C. Heintze
7
, H. Heitmann
64
, P. Hello
25
,
G. Hemming
28
, M. Hendry
43
, I. S. Heng
43
, J. Hennig
8
,
9
, A. W. Heptonstall
1
, Francisco Hernandez Vivanco
6
, M. Heurs
8
,
9
, S. Hild
43
,
T. Hinderer
36
,
127
,
128
, D. Hoak
28
, S. Hochheim
8
,
9
, D. Hofman
22
, A. M. Holgado
17
, N. A. Holland
21
, K. Holt
7
, D. E. Holz
89
,
P. Hopkins
67
, C. Horst
23
, J. Hough
43
, E. J. Howell
62
, C. G. Hoy
67
, A. Hreibi
64
, E. A. Huerta
17
, D. Huet
25
, B. Hughey
33
, M. Hulko
1
,
S. Husa
98
, S. H. Huttner
43
, T. Huynh-Dinh
7
, B. Idzkowski
73
, A. Iess
29
,
30
, C. Ingram
54
, R. Inta
83
, G. Intini
31
,
112
, B. Irwin
114
,
H. N. Isa
43
, J.-M. Isac
70
, M. Isi
1
, B. R. Iyer
16
, K. Izumi
44
, T. Jacqmin
70
, S. J. Jadhav
129
, K. Jani
76
, N. N. Janthalur
129
,
P. Jaranowski
130
, A. C. Jenkins
131
, J. Jiang
47
, D. S. Johnson
17
, A. W. Jones
11
, D. I. Jones
132
, R. Jones
43
, R. J. G. Jonker
36
,L.Ju
62
,
J. Junker
8
,
9
, C. V. Kalaghatgi
67
, V. Kalogera
58
, B. Kamai
1
, S. Kandhasamy
84
, G. Kang
37
, J. B. Kanner
1
, S. J. Kapadia
23
,
S. Karki
69
, K. S. Karvinen
8
,
9
, R. Kashyap
16
, M. Kasprzack
1
, S. Katsanevas
28
, E. Katsavounidis
12
, W. Katzman
7
, S. Kaufer
9
,
K. Kawabe
44
, N. V. Keerthana
3
, F. Kéfélian
64
, D. Keitel
43
, R. Kennedy
107
,J.S.Key
133
, F. Y. Khalili
61
, H. Khan
26
, I. Khan
14
,
30
,
S. Khan
8
,
9
, Z. Khan
106
, E. A. Khazanov
134
, M. Khursheed
60
, N. Kijbunchoo
21
, Chunglee Kim
135
, J. C. Kim
136
, K. Kim
90
,
W. Kim
54
,W.S.Kim
137
, Y.-M. Kim
138
, C. Kimball
58
, E. J. King
54
, P. J. King
44
, M. Kinley-Hanlon
126
, R. Kirchhoff
8
,
9
,
J. S. Kissel
44
, L. Kleybolte
139
, J. H. Klika
23
, S. Klimenko
47
, T. D. Knowles
38
, P. Koch
8
,
9
, S. M. Koehlenbeck
8
,
9
,
G. Koekoek
36
,
140
, S. Koley
36
, V. Kondrashov
1
, A. Kontos
12
, N. Koper
8
,
9
, M. Korobko
139
, W. Z. Korth
1
, I. Kowalska
73
,
D. B. Kozak
1
, V. Kringel
8
,
9
, N. Krishnendu
141
, A. Królak
142
,
143
, G. Kuehn
8
,
9
, A. Kumar
129
, P. Kumar
144
, R. Kumar
106
, S. Kumar
16
,
L. Kuo
87
, A. Kutynia
142
, S. Kwang
23
, B. D. Lackey
35
,K.H.Lai
90
,T.L.Lam
90
, M. Landry
44
, B. B. Lane
12
, R. N. Lang
145
,
J. Lange
57
, B. Lantz
48
, R. K. Lanza
12
, A. Lartaux-Vollard
25
, P. D. Lasky
6
, M. Laxen
7
, A. Lazzarini
1
, C. Lazzaro
51
, P. Leaci
31
,
112
,
S. Leavey
8
,
9
, Y. K. Lecoeuche
44
, C. H. Lee
92
, H. K. Lee
146
, H. M. Lee
147
, H. W. Lee
136
, J. Lee
91
, K. Lee
43
, J. Lehmann
8
,
9
,
A. Lenon
38
, N. Leroy
25
, N. Letendre
32
, Y. Levin
6
,
97
,J.Li
82
,K.J.L.Li
90
,T.G.F.Li
90
,X.Li
45
,F.Lin
6
, F. Linde
36
, S. D. Linker
110
,
T. B. Littenberg
148
, J. Liu
62
, X. Liu
23
,R.K.L.Lo
1
,
90
, N. A. Lockerbie
24
, L. T. London
67
, A. Longo
149
,
150
, M. Lorenzini
14
,
15
,
V. Loriette
151
, M. Lormand
7
, G. Losurdo
19
, J. D. Lough
8
,
9
, C. O. Lousto
57
, G. Lovelace
26
, M. E. Lower
152
, H. Lück
8
,
9
,
D. Lumaca
29
,
30
, A. P. Lundgren
153
, R. Lynch
12
,Y.Ma
45
, R. Macas
67
, S. Macfoy
24
, M. MacInnis
12
, D. M. Macleod
67
,
A. Macquet
64
, F. Magaña-Sandoval
41
, L. Magaña Zertuche
84
, R. M. Magee
86
, E. Majorana
31
, I. Maksimovic
151
, A. Malik
60
,
N. Man
64
, V. Mandic
42
, V. Mangano
43
, G. L. Mansell
12
,
44
, M. Manske
21
,
23
, M. Mantovani
28
, F. Marchesoni
40
,
49
, F. Marion
32
,
S. Márka
97
, Z. Márka
97
, C. Markakis
10
,
17
, A. S. Markosyan
48
, A. Markowitz
1
, E. Maros
1
, A. Marquina
101
, S. Marsat
35
,
F. Martelli
71
,
72
, I. W. Martin
43
, R. M. Martin
34
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, 2019 April 20
Abbott et al.
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s Republic of China
83
Texas Tech University, Lubbock, TX 79409, USA
84
The University of Mississippi, University, MS 38677, USA
85
Museo Storico della Fisica e Centro Studi e Ricerche
Enrico Fermi,
I-00184 Roma, Italyrico Fermi, I-00184 Roma, Italy
86
The Pennsylvania State University, University Park, PA 16802, USA
87
National Tsing Hua University, Hsinchu City, 30013 Taiwan, Republic of China
88
Charles Sturt University, Wagga Wagga, New South Wales 2678, Australia
89
University of Chicago, Chicago, IL 60637, USA
90
The Chinese University of Hong Kong, Shatin, NT, Hong Kong
91
Seoul National University, Seoul 08826, Republic of Korea
92
Pusan National University, Busan 46241, Republic of Korea
93
Carleton College, North
fi
eld, MN 55057, USA
94
INAF, Osservatorio Astronomico di Padova, I-35122 Padova, Italy
95
INFN, Trento Institute for Fundamental Physics and Applications, I-38123 Povo, Trento, Italy
96
OzGrav, University of Melbourne, Parkville, Victoria 3010, Australia
97
Columbia University, New York, NY 10027, USA
98
Universitat de les Illes Balears, IAC3
IEEC, E-07122 Palma de Mallorca, Spain
99
Université Libre de Bruxelles, Brussels B-1050, Belgium
100
Sonoma State University, Rohnert Park, CA 94928, USA
101
Departamento de Matemáticas, Universitat de València, E-46100 Burjassot, València, Spain
102
University of Rhode Island, Kingston, RI 02881, USA
103
The University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
104
Bellevue College, Bellevue, WA 98007, USA
105
MTA-ELTE Astrophysics Research Group, Institute of Physics, Eötvös University, Budapest 1117, Hungary
106
Institute for Plasma Research, Bhat, Gandhinagar 382428, India
107
The University of Shef
fi
eld, Shef
fi
eld S10 2TN, UK
108
IGFAE, Campus Sur, Universidade de Santiago de Compostela, E-15782 Spain
109
Dipartimento di Scienze Matematiche, Fisiche e Informatiche, Università di Parma, I-43124 Parma, Italy
110
California State University, Los Angeles, 5151 State University Dr, Los Angeles, CA 90032, USA
111
Università di Trento, Dipartimento di Fisica, I-38123 Povo, Trento, Italy
112
Università di Roma
La Sapienza,
I-00185 Roma, Italy
113
Colorado State University, Fort Collins, CO 80523, USA
114
Kenyon College, Gambier, OH 43022, USA
4
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20pp
)
, 2019 April 20
Abbott et al.
115
Christopher Newport University, Newport News, VA 23606, USA
116
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
117
Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, Ontario M5S 3H8, Canada
118
Observatori Astronòmic, Universitat de València, E-46980 Paterna, València, Spain
119
School of Mathematics, University of Edinburgh, Edinburgh EH9 3FD, UK
120
Institute Of Advanced Research, Gandhinagar 382426, India
121
Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India
122
University of Szeged, Dóm tér 9, Szeged 6720, Hungary
123
Tata Institute of Fundamental Research, Mumbai 400005, India
124
INAF, Osservatorio Astronomico di Capodimonte, I-80131, Napoli, Italy
125
University of Michigan, Ann Arbor, MI 48109, USA
126
American University, Washington, DC 20016, USA
127
GRAPPA, Anton Pannekoek Institute for Astronomy and Institute of High-Energy Physics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam
,
The Netherlands
128
Delta Institute for Theoretical Physics, Science Park 904, 1090 GL Amsterdam, The Netherlands
129
Directorate of Construction, Services & Estate Management, Mumbai 400094, India
130
University of Bia
ł
ystok, 15-424 Bia
ł
ystok, Poland
131
King
s College London, University of London, London WC2R 2LS, UK
132
University of Southampton, Southampton SO17 1BJ, UK
133
University of Washington Bothell, Bothell, WA 98011, USA
134
Institute of Applied Physics, Nizhny Novgorod, 603950, Russia
135
Ewha Womans University, Seoul 03760, Republic of Korea
136
Inje University Gimhae, South Gyeongsang 50834, Republic of Korea
137
National Institute for Mathematical Sciences, Daejeon 34047, Republic of Korea
138
Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
139
Universität Hamburg, D-22761 Hamburg, Germany
140
Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
141
Chennai Mathematical Institute, Chennai 603103, India
142
NCBJ, 05-400
Ś
wierk-Otwock, Poland
143
Institute of Mathematics, Polish Academy of Sciences, 00656 Warsaw, Poland
144
Cornell University, Ithaca, NY 14850, USA
145
Hillsdale College, Hillsdale, MI 49242, USA
146
Hanyang University, Seoul 04763, Republic of Korea
147
Korea Astronomy and Space Science Institute, Daejeon 34055, Republic of Korea
148
NASA Marshall Space Flight Center, Huntsville, AL 35811, USA
149
Dipartimento di Matematica e Fisica, Università degli Studi Roma Tre, I-00146 Roma, Italy
150
INFN, Sezione di Roma Tre, I-00146 Roma, Italy
151
ESPCI, CNRS, F-75005 Paris, France
152
OzGrav, Swinburne University of Technology, Hawthorn VIC 3122, Australia
153
University of Portsmouth, Portsmouth, PO1 3FX, UK
154
Southern University and A&M College, Baton Rouge, LA 70813, USA
155
College of William and Mary, Williamsburg, VA 23187, USA
156
Centre Scienti
fi
que de Monaco, 8 quai Antoine Ier, MC-98000, Monaco
157
Indian Institute of Technology Madras, Chennai 600036, India
158
INFN Sezione di Torino, Via P. Giuria 1, I-10125 Torino, Italy
159
Institut des Hautes Etudes Scienti
fi
ques, F-91440 Bures-sur-Yvette, France
160
IISER-Kolkata, Mohanpur, West Bengal 741252, India
161
Whitman College, 345 Boyer Avenue, Walla Walla, WA 99362 USA
162
Université de Lyon, F-69361 Lyon, France
163
Hobart and William Smith Colleges, Geneva, NY 14456, USA
164
Janusz Gil Institute of Astronomy, University of Zielona Góra, 65-265 Zielona Góra, Poland
165
University of Washington, Seattle, WA 98195, USA
166
SUPA, University of the West of Scotland, Paisley PA1 2BE, UK
167
Indian Institute of Technology, Gandhinagar Ahmedabad Gujarat 382424, India
168
Université de Montréal
/
Polytechnique, Montreal, Quebec H3T 1J4, Canada
169
Indian Institute of Technology Hyderabad, Sangareddy, Khandi, Telangana 502285, India
170
International Institute of Physics, Universidade Federal do Rio Grande do Norte, Natal RN 59078-970, Brazil
171
Villanova University, 800 Lancaster Ave, Villanova, PA 19085, USA
172
Andrews University, Berrien Springs, MI 49104, USA
173
Max Planck Institute for Gravitationalphysik
(
Albert Einstein Institute
)
, D-14476 Potsdam-Golm, Germany
174
Università di Siena, I-53100 Siena, Italy
175
Trinity University, San Antonio, TX 78212, USA
176
Van Swinderen Institute for Particle Physics and Gravity, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands
177
Department of Physics, University of Texas, Austin, TX78712, USA
Received 2019 January 28; revised 2019 February 18; accepted 2019 February 18; published 2019 April 25
178
Deceased, 2018 February.
179
Deceased, 2017 November.
180
Deceased, 2018 July.
Original content from this work may be used under the terms
of the
Creative Commons Attribution 3.0 licence
. Any further
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(
s
)
and the title
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5
The Astrophysical Journal,
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(
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)
, 2019 April 20
Abbott et al.
Abstract
Advanced LIGO
s second observing run
(
O2
)
, conducted from 2016 November 30 to 2017 August 25, combined
with Advanced Virgo
s
fi
rst observations in 2017 August, witnessed the birth of gravitational-wave
multimessenger astronomy. The
fi
rst ever gravitational-wave detection from the coalescence of two neutron
stars, GW170817, and its gamma-ray counterpart, GRB 170817A, led to an electromagnetic follow-up of the event
at an unprecedented scale. Several teams from across the world searched for EM
/
neutrino counterparts to
GW170817, paving the way for the discovery of optical, X-ray, and radio counterparts. In this article, we describe
the online identi
fi
cation of gravitational-wave transients and the distribution of gravitational-wave alerts by the
LIGO and Virgo collaborations during O2. We also describe the gravitational-wave observables that were sent in
the alerts to enable searches for their counterparts. Finally, we give an overview of the online candidate alerts
shared with observing partners during O2. Alerts were issued for 14 candidates, 6 of which have been con
fi
rmed as
gravitational-wave events associated with the merger of black holes or neutron stars. Of the 14 alerts, 8 were issued
less than an hour after data acquisition.
Key words:
gravitational waves
methods: data analysis
1. Introduction
Gravitational-wave
(
GW
)
multimessenger astronomy pro-
vides a unique view of the cosmos. In this paper, we explain
the procedures used during the second observing run of the
advanced ground-based gravitational-wave-detector network to
issue alerts for multimessenger follow-up. We also include a
summary of all alerts issued to observing partners and an
update on the status of candidate events.
The Advanced Laser Interferometer Gravitational-wave
Observatory
(
LIGO
)
detectors
(
LIGO Scienti
fi
c Collaboration
et al.
2015
)
are installed in the US at Hanford, WA and
Livingston, LA, and the Advanced Virgo detector
(
Acernese
et al.
2015
)
is located in Cascina, Italy near Pisa. The detectors
use a modi
fi
ed Michelson laser interferometer design to
measure GW strain. A passing GW causes a differential length
change in the detector arms, producing interference of the laser
beams at the beam splitter, and giving an optical readout
proportional to the GW strain.
In 2015 September the two Advanced LIGO detectors began
their
fi
rst observing run
(
O1
)
, lasting four months. The
fi
rst
direct detection of gravitational waves, GW150914, from the
coalescence of binary black holes
(
BBHs; Abbott et al.
2016b
)
,
marked the beginning of gravitational-wave
(
GW
)
astronomy.
Two additional BBH merger signals, GW151012
181
(
Abbott
et al.
2016c
)
and GW151226
(
Abbott et al.
2016d
)
, were
identi
fi
ed before the end of O1. Following hardware and
software upgrades, the second Advanced LIGO observing run
(
O2
)
began on 2016 November 30. Advanced Virgo joined the
network in 2017 August for the last month of data acquisition.
A number of additional BBH coalescences were detected in
O2
(
see Abbott et al.
2017a
,
2017b
,
2017c
, LIGO Scienti
fi
c
Collaboration et al.
2018
)
. Furthermore, on 2017 August 17, at
12:41:04 UTC a binary neutron star
(
BNS
)
inspiral signal
(
GW170817
)
was observed
(
Abbott et al.
2017d
)
. Less than
two seconds later, the short gamma-ray burst
(
sGRB
)
GRB
170817A was detected by two space-based instruments: the
Gamma-ray Burst Monitor
(
GBM
)
on board
Fermi
(
Goldstein
et al.
2017
)
, and the spectrometer anti-coincidence shield
(
SPI-
ACS
)
on board
INTEGRAL
(
Savchenko et al.
2017
)
. This joint
observation provided the
fi
rst direct evidence that at least a
fraction of sGRBs have a BNS system as a progenitor, as
predicted by Eichler et al.
(
1989
)
, Paczynski
(
1986
)
, and
Paczynski
(
1991
)
. Short GRBs are typically expected to result
in a long-lasting, multiwavelength afterglow emission in X-ray,
optical, and radio bands
(
for a review see Nakar
2007
;
Berger
2014
;D
Avanzo
2015
)
.
The extensive electromagnetic
(
EM
)
observational campaign
using the well-constrained, three-detector skymap from the
detection of GW170817 led to the discovery of an optical
transient
(
SSS17a
/
AT 2017gfo
)
in the host galaxy NGC 4993
(
Coulter et al.
2017
)
; the counterpart was also detected at
ultraviolet and infrared wavelengths
(
Abbott et al.
2017e
)
.
Photometric and spectroscopic observations of the counterpart
support the hypothesis that BNS mergers are sites of r-process
nucleosynthesis of heavy elements that decay, thus powering
so-called kilonova emission in UV
/
optical
/
NIR
(
see, e.g., Li &
Paczy
ń
ski
1998
; Kulkarni
2005
; Tanaka
2016
; Evans
et al.
2017
; Kasen et al.
2017
; Metzger
2017
; Pian
et al.
2017
; Villar et al.
2017
)
. Several days after the BNS
merger, X-ray
(
Troja et al.
2017
)
and radio
(
Hallinan
et al.
2017a
)
emissions were also discovered at the transient
s
position
(
see also Abbott et al.
2017e
and references therein
)
.
These observations are consistent with the expected interaction
of merger ejecta with the interstellar medium on timescales of
up to years
(
see, e.g., Nakar & Piran
2011
; Hotokezaka &
Piran
2015
; Hotokezaka et al.
2016
)
. Data from exhaustive
follow-up in the X-ray, radio, and optical, covering almost one
year, allowed detailed modeling of emission mechanisms, such
as an off-axis structured jet
(
see, e.g., D
Avanzo et al.
2018
;
Dobie et al.
2018
; Margutti et al.
2018
; Mooley et al.
2018a
;
Ruan et al.
2018
)
. The degeneracy among the various models
has been broken with late-time radio observations that support
the emergence of a relativistic jet from the BNS merger
(
Ghirlanda et al.
2018
; Mooley et al.
2018b
)
.
Besides compact binary mergers, other transient GW sources
that may be observed by ground-based interferometers include
the core-collapse of massive stars, which are expected to emit
GWs if some asymmetry is present
(
see Kotake et al.
2006
;
Ott
2009
; Gossan et al.
2016
for an overview
)
. The core-
collapse of a massive star is accompanied by supernova
(
SN
)
emissions, starting in the ultraviolet and soft X-ray bands from
the shock breakout of the stellar surface
(
see, e.g., Falk &
Arnett
1977
; Klein & Chevalier
1978
; Ensman & Bur-
rows
1992
; Andreoni et al.
2016
)
, and followed by emissions
at optical and radio frequencies that typically start from days to
weeks after the collapse and last for weeks up to years.
Neutrinos are also emitted during core-collapse supernovae as
con
fi
rmed on 1987 February 23 when MeV neutrinos were
detected from SN 1987A in the Large Magellanic Cloud
(
at a
181
The candidate LVT151012 has been con
fi
rmed as a gravitational-wave
event, and is now called GW151012
(
LIGO Scienti
fi
c Collaboration et al.
2018
)
.
6
The Astrophysical Journal,
875:161
(
20pp
)
, 2019 April 20
Abbott et al.
distance of
50 kpc
)
by the Kamiokande-II
(
Hirata et al.
1987
)
and the Irvine
Michigan
Brookhaven
(
Bionta et al.
1987
)
neutrino detectors, a few hours before its optical counterpart
was discovered. In addition, GRBs and SNe are expected to
produce relativistic out
fl
ows in which particles
(
protons and
nuclei
)
can be accelerated and produce high-energy neutrinos
by interacting with the surrounding medium and radiation
(
see,
e.g., Murase
2018
)
.
Another class of transient GW sources is magnetars, i.e.,
rotating NSs with very intense magnetic
fi
elds
(
10
15
G
)
.
Theoretical models predict that when these stars undergo
starquakes, asymmetric strains can temporarily alter the
geometry of the star and GWs can be emitted
(
see, e.g., Corsi
& Owen
2011
)
. Electromagnetic phenomena possibly asso-
ciated with magnetar starquakes include soft gamma repeaters
(
SGRs
)
and anomalous X-ray pulsars
(
AXPs
)
, sources that
sporadically emit short bursts of gamma-rays and X-rays
(
see
Mereghetti
2008
for a review
)
. Starquakes can also cause
radio
/
X-ray pulsar glitches: sudden increases in the rotational
frequency of a highly magnetized, rotating NS
(
pulsar
)
followed by exponential decays, which bring the pulsar
rotational frequency back down to its initial value
(
see, e.g.,
Espinoza et al.
2011
)
.
During O1 and O2, extensive EM observing campaigns
searched for counterparts to GW candidates identi
fi
ed in low-
latency. Signi
fi
cant improvements were made between these
two observing runs regarding the data analysis software and
source modeling, allowing important additional information to
be distributed in low-latency during O2. For CBC events, 3D
sky localization maps were released, providing information
about the direction and the luminosity distance of the source
(
Singer et al.
2016a
)
, while in O1, only 2D sky localization
maps were provided, without distance information. During O2,
probabilities that at least one low-mass object was present in
the coalescing binary system and that tidally disrupted material
formed a massive accretion disk around the merged object were
reported. This information is useful for assessing the likelihood
that a merger could power an EM transient
(
Foucart
2012
;
Pannarale & Ohme
2014
)
.
During O1 and the
fi
rst part of O2, with the GW network
formed only by the two Advanced LIGO interferometers,
sources were typically localized in sky areas ranging from a
few hundreds to several thousands of square degrees
(
see, e.g.,
Abbott et al.
2017a
,
2016d
,
2016e
)
. Improvements in
localization areas have been made since Advanced Virgo
joined the gravitational-wave detector network starting 2017
August 1. For instance, GW170814 and GW170817 were
localized by the three-detector network within a few tens of
square degrees; see Abbott et al.
(
2017b
,
2017d
)
.
Jointly observing the same event in both gravitational waves
and electromagnetic radiation provides complementary insights
into the progenitor and its local environment. The GW signal is
key to determining several physical properties of the source
such as the masses and system properties
(
inclination,
orientation, spin, etc.
)
. The EM counterpart provides informa-
tion about radioactive decay, shocks, the emission mechanism
of the central engine, magnetic
fi
elds, and beaming; and also
probes the surrounding environment of the source
(
see, for
instance, Berger
2014
)
. The detection of an EM counterpart
also can give precise localization and lead to the identi
fi
cation
of the host galaxy of the source. The distance estimated from
the GW data, combined with the measured redshift of the host
galaxy, enables measurement of the Hubble constant
(
Schutz
1986
; Holz & Hughes
2005
; Nissanke et al.
2010
,
2013a
; Abbott et al.
2017f
; Hotokezaka et al.
2018
;
Seto & Kyutoku
2018
; Vitale & Chen
2018
)
. Precise
measurements of the host galaxy distance and the binary
inclination given by the EM observations can be used to reduce
the degeneracy in the GW parameter estimation
(
see, e.g.,
Guidorzi et al.
2017
; Cantiello et al.
2018
; Chen et al.
2018
;
Mandel
2018
)
. Furthermore, the detection of an EM counter-
part may increase the con
fi
dence in the astrophysical origin of a
weak GW signal
(
Kochanek & Piran
1993
)
. It also provides
constraints on the relative merger rates of the two classes of
compact binaries
(
BNS and NS
BH
)
, on the beaming angle of
sGRBs, and the NS equation of state
(
Abadie et al.
2010
; Chen
& Holz
2013
; Pannarale & Ohme
2014
; Clark et al.
2015
;
Dominik et al.
2015
; Regimbau et al.
2015
; Siellez et al.
2016
;
Radice et al.
2018
)
. Finally, joint GW and EM observations can
provide constraints on fundamental physics
(
Abbott
et al.
2017g
)
.
In this paper, we describe the identi
fi
cation of GW transients
and the distribution of GW alerts performed during O2 by the
LIGO and Virgo collaborations. We also detail the GW event
information shared with the astronomy community and give an
overview of the EM follow-up strategies.
In Section
2
we present an overview of the online GW
analysis, with a description of the online analysis detection
pipelines, and the vetting and approval processes for potential
GW events. In Section
3
we summarize the GW alerts that were
distributed during O2 and the properties of the gravitational-
wave candidates after the of
fl
ine analysis. We describe the
information that was shared with astronomers, including how
this was used during the electromagnetic
/
neutrino follow-up
activities. Finally, in Section
4
we present our conclusions.
Table 1
Major Parameters of the O2 Online Search Pipelines Based on Compact Binary
Merger Waveform Models
PyCBC Live
GstLAL
MBTAOnline
Total mass
2
M
e
500
M
e
a
2
M
e
150
M
e
a
2
M
e
100
M
e
Mass ratio
1
98
1
98
1
99
Minimum comp-
onent mass
1
M
e
1
M
e
1
M
e
Spin magni-
tude
(
m
<
2
M
e
)
0
0.05
0
0.05
0
0.05
Spin magni-
tude
(
m
>
2
M
e
)
0
0.998
0
0.999
0
0.9899
Single-detector S
/
N
threshold for
triggering
5.5
4
b
5.5
c
Notes.
a
The maximum total mass for PyCBC Live and GstLAL is in fact a function of
mass ratio and component spins
(
Dal Canton & Harry
2017
; Mukherjee
et al.
2018
)
and we indicate the highest total mass limit over all mass ratios and
spins. The of
fl
ine GstLAL search uses a template bank extended to a larger
maximum total mass of 400
M
e
.
b
This threshold was applied to the two LIGO detectors only for the online
GstLAL analysis. The minimum trigger S
/
N in Virgo was not determined by
an explicit threshold, but instead by a restriction to record at most 1 trigger per
second in a given template.
c
MBTAOnline uses a higher LIGO S
/
N threshold
(
6
)
to form coincidences
with Virgo.
7
The Astrophysical Journal,
875:161
(
20pp
)
, 2019 April 20
Abbott et al.
2. Online Gravitational-wave Analysis
In this section, we describe the two classes of searches for GW
transients, modeled and unmodeled, that contributed triggers for
low-latency EM follow-up
(
in Section
2.1
)
.Wealsopresent
the full vetting and validation process of candidate events
(
in Section
2.2
)
and distribution of low-latency alerts during O2
(
in Section
2.3
)
.Of
fl
ine search pipelines
182
also led to the
identi
fi
cation of additional candidate events GW170729 and
GW170818
(
see LIGO Scienti
fi
c Collaboration et al.
2018
)
.
2.1. Brief Description of Online Pipelines
The modeled
(
CBC
)
searches speci
fi
cally look for signals
from compact binary mergers of neutron stars and black holes
(
BNS, NS
BH, and BBH systems
)
. The unmodeled
(
burst
)
searches, on the other hand, are capable of detecting signals
from a wide variety of astrophysical sources in addition to
compact binary mergers: core-collapse of massive stars,
magnetar starquakes, and more speculative sources such as
intersecting cosmic strings or currently unknown GW sources.
2.1.1. Online Modeled Searches
GstLAL
(
Messick et al.
2017
)
, MBTAOnline
(
Multi-Band
Template Analysis, Adams et al.
2016
)
and PyCBC Live
(
Nitz
et al.
2018
)
are analysis pipelines designed to detect and report
compact binary merger events with sub-minute latencies. Such
pipelines use discrete banks of waveform templates to cover the
target parameter space of compact binaries and perform
matched
fi
ltering on the data using those templates, similar to
the of
fl
ine analyses
(
Usman et al.
2016
; Messick et al.
2017
)
that produced the O1 and O2 catalog of compact binaries
(
LIGO Scienti
fi
c Collaboration et al.
2018
)
. The online and
of
fl
ine analyses differ in various ways. The most important
con
fi
guration choices of online analyses are reviewed here.
The mass and spin parameter space considered by the online
pipelines in O2 is summarized in Table
1
. All pipelines assume
that, while the gravitational-wave signal dwells in the detector
sensitive band, the spins of the compact objects are aligned or
antialigned with the orbital angular momentum, and that orbital
eccentricity is negligible. Additional details of the PyCBC Live
and GstLAL banks can be found in Dal Canton & Harry
(
2017
)
and Mukherjee et al.
(
2018
)
, respectively. In the case of
PyCBC Live, the online and
fi
nal of
fl
ine analyses covered
exactly the same space. For GstLAL, the of
fl
ine bank extended
to a larger total mass of 400
M
e
.
A matched-
fi
ltering analysis is performed by each pipeline,
producing triggers for each detector
s data stream whenever the
matched-
fi
lter single-detector signal-to-noise ratio
(
S
/
N
)
peaks
above a threshold given in Table
1
. Due to the small probability
of a signal being detectable in Virgo and not in LIGO during
O2, PyCBC Live did not use Virgo to produce triggers; Virgo
s
data were nevertheless still analyzed and used for the sky
localization of candidates from LIGO.
Matched
fi
ltering alone is insuf
fi
cient in non-Gaussian
detector noise, producing frequent non-astrophysical triggers
with large S
/
N
(
Abbott et al.
2016f
)
. Pipelines can choose
among different techniques to mitigate this effect: calculating
additional statistics based on the template waveform
(
signal-
based vetoes
)
, explicitly zeroing out loud and short instru-
mental transients before matched-
fi
ltering
(
gating
)
, and vetoing
triggers based on known data quality issues that are reported
with the same latency as the strain data itself. In O2, all
matched-
fi
lter searches employed signal-based vetoes; PyCBC
Live and MBTAOnline applied vetoes based on low-latency
data quality information, while GstLAL applied gating.
The trigger lists produced by matched
fi
ltering and cleaned
via the aforementioned procedures are searched for coin-
cidences between detectors. Coincident triggers are ranked
based on their S
/
Ns and signal-based vetoes and the
consistency of their S
/
Ns, arrival times, and arrival phases at
the different detectors with an astrophysical signal. The
pipelines construct this ranking and convert it to a statistical
signi
fi
cance in different ways, described next. A measure of
signi
fi
cance produced by all pipelines for each candidate is the
estimated false-alarm rate
(
FAR
)
, i.e., the rate at which we
expect events with at least as high a ranking as the candidate to
be generated due to detector noise.
MBTAOnline constructs a background distribution of the
ranking statistic by generating every possible coincidence from
single-detector triggers over a few hours of recent data. It then
folds in the probability of a pair of triggers passing the time
coincidence test.
PyCBC Live
s ranking of coincident triggers in O2 was
somewhat simpler than the
fi
nal of
fl
ine analysis: it did not
account for the variation of background over the parameter
space
(
Nitz et al.
2017
)
and it did not include the sine-Gaussian
signal-based veto
(
Nitz
2018
)
. PyCBC Live estimated the
background of accidental coincidences using time shifts
between triggers from different detectors, as done by the
of
fl
ine analysis
(
Usman et al.
2016
)
. The amount of live time
used for background estimation in PyCBC Live was 5 hr, to
be compared with
5 days of the of
fl
ine analysis. This choice
limited the inverse FAR of online detections to
100 yr
maximum, insuf
fi
cient for claiming a very signi
fi
cant detection,
but adequate for generating rapid alerts for astronomers. On the
other hand, this choice gave the background estimation a faster
response to variations in noise characteristics, which is useful
considering the limited data quality
fl
ags available to the online
analysis.
GstLAL calculates the signi
fi
cance of triggers by construct-
ing a likelihood-ratio ranking statistic that models the
distribution of trigger properties for noise and GW events
(
Cannon et al.
2015
)
. The background is computed by
synthesizing likelihood ratios from a random sampling of a
probability density that is estimated using non-coincident
triggers accumulated over the course of an observing run,
which are taken to be noise.
2.1.2. Online Unmodeled Searches
The two unmodeled signal searches
(
burst
)
, cWB and oLIB,
work by looking for excess power in the time-frequency
(
TF
)
domain of the GW strain data
(
Klimenko et al.
2016
; Lynch
et al.
2017
)
. The cWB pipeline does this by creating TF maps at
multiple resolutions across the GW detector network and
identifying clusters of TF data samples with power above the
baseline detector noise. Excess power clusters in different
detectors that overlap in time and frequency indicate the
presence of a GW event. The signal waveforms and the source
sky location are reconstructed with the maximum likelihood
method by maximizing over all possible time-of-
fl
ight delays in
182
The of
fl
ine O2 results were obtained after a complete regeneration of O2
strain data with noise subtraction performed for the LIGO detectors
(
Davis
et al.
2018
)
.
8
The Astrophysical Journal,
875:161
(
20pp
)
, 2019 April 20
Abbott et al.