All-sky search for short gravitational-wave bursts in the first Advanced LIGO run
B. P. Abbott,
1
R. Abbott,
1
T. D. Abbott,
2
M. R. Abernathy,
3
F. Acernese,
4
,
5
K. Ackley,
6
C. Adams,
7
T. Adams,
8
P. Addesso,
9
R. X. Adhikari,
1
V. B. Adya,
10
C. Affeldt,
10
M. Agathos,
11
K. Agatsuma,
11
N. Aggarwal,
12
O. D. Aguiar,
13
L. Aiello,
14
,
15
A. Ain,
16
B. Allen,
10
,
17
,
18
A. Allocca,
19
,
20
P. A. Altin,
21
A. Ananyeva,
1
S. B. Anderson,
1
W. G. Anderson,
17
S. Appert,
1
K. Arai,
1
M. C. Araya,
1
J. S. Areeda,
22
N. Arnaud,
23
K. G. Arun,
24
S. Ascenzi,
25
,
15
G. Ashton,
10
M. Ast,
26
S. M. Aston,
7
P. Astone,
27
P. Aufmuth,
18
C. Aulbert,
10
A. Avila-Alvarez,
22
S. Babak,
28
P. Bacon,
29
M. K. M. Bader,
11
P. T. Baker,
30
F. Baldaccini,
31
,
32
G. Ballardin,
33
S. W. Ballmer,
34
J. C. Barayoga,
1
S. E. Barclay,
35
B. C. Barish,
1
D. Barker,
36
F. Barone,
4
,
5
B. Barr,
35
L. Barsotti,
12
M. Barsuglia,
29
D. Barta,
37
J. Bartlett,
36
I. Bartos,
38
R. Bassiri,
39
A. Basti,
19
,
20
J. C. Batch,
36
C. Baune,
10
V. Bavigadda,
33
M. Bazzan,
40
,
41
C. Beer,
10
M. Bejger,
42
I. Belahcene,
23
M. Belgin,
43
A. S. Bell,
35
B. K. Berger,
1
G. Bergmann,
10
C. P. L. Berry,
44
D. Bersanetti,
45
,
46
A. Bertolini,
11
J. Betzwieser,
7
S. Bhagwat,
34
R. Bhandare,
47
I. A. Bilenko,
48
G. Billingsley,
1
C. R. Billman,
6
J. Birch,
7
R. Birney,
49
O. Birnholtz,
10
S. Biscans,
12
,
1
A. Bisht,
18
M. Bitossi,
33
C. Biwer,
34
M. A. Bizouard,
23
J. K. Blackburn,
1
J. Blackman,
50
C. D. Blair,
51
D. G. Blair,
51
R. M. Blair,
36
S. Bloemen,
52
O. Bock,
10
M. Boer,
53
G. Bogaert,
53
A. Bohe,
28
F. Bondu,
54
R. Bonnand,
8
B. A. Boom,
11
R. Bork,
1
V. Boschi,
19
,
20
S. Bose,
55
,
16
Y. Bouffanais,
29
A. Bozzi,
33
C. Bradaschia,
20
P. R. Brady,
17
V. B. Braginsky
∗
,
48
M. Branchesi,
56
,
57
J. E. Brau,
58
T. Briant,
59
A. Brillet,
53
M. Brinkmann,
10
V. Brisson,
23
P. Brockill,
17
J. E. Broida,
60
A. F. Brooks,
1
D. A. Brown,
34
D. D. Brown,
44
N. M. Brown,
12
S. Brunett,
1
C. C. Buchanan,
2
A. Buikema,
12
T. Bulik,
61
H. J. Bulten,
62
,
11
A. Buonanno,
28
,
63
D. Buskulic,
8
C. Buy,
29
R. L. Byer,
39
M. Cabero,
10
L. Cadonati,
43
G. Cagnoli,
64
,
65
C. Cahillane,
1
J. Calder ́on Bustillo,
43
T. A. Callister,
1
E. Calloni,
66
,
5
J. B. Camp,
67
M. Canepa,
45
,
46
K. C. Cannon,
68
H. Cao,
69
J. Cao,
70
C. D. Capano,
10
E. Capocasa,
29
F. Carbognani,
33
S. Caride,
71
J. Casanueva Diaz,
23
C. Casentini,
25
,
15
S. Caudill,
17
M. Cavagli`a,
72
F. Cavalier,
23
R. Cavalieri,
33
G. Cella,
20
C. B. Cepeda,
1
L. Cerboni Baiardi,
56
,
57
G. Cerretani,
19
,
20
E. Cesarini,
25
,
15
S. J. Chamberlin,
73
M. Chan,
35
S. Chao,
74
P. Charlton,
75
E. Chassande-Mottin,
29
B. D. Cheeseboro,
30
H. Y. Chen,
76
Y. Chen,
50
H.-P. Cheng,
6
A. Chincarini,
46
A. Chiummo,
33
T. Chmiel,
77
H. S. Cho,
78
M. Cho,
63
J. H. Chow,
21
N. Christensen,
60
Q. Chu,
51
A. J. K. Chua,
79
S. Chua,
59
S. Chung,
51
G. Ciani,
6
F. Clara,
36
J. A. Clark,
43
F. Cleva,
53
C. Cocchieri,
72
E. Coccia,
14
,
15
P.-F. Cohadon,
59
A. Colla,
80
,
27
C. G. Collette,
81
L. Cominsky,
82
M. Constancio Jr.,
13
L. Conti,
41
S. J. Cooper,
44
T. R. Corbitt,
2
N. Cornish,
83
A. Corsi,
71
S. Cortese,
33
C. A. Costa,
13
M. W. Coughlin,
60
S. B. Coughlin,
84
J.-P. Coulon,
53
S. T. Countryman,
38
P. Couvares,
1
P. B. Covas,
85
E. E. Cowan,
43
D. M. Coward,
51
M. J. Cowart,
7
D. C. Coyne,
1
R. Coyne,
71
J. D. E. Creighton,
17
T. D. Creighton,
86
J. Cripe,
2
S. G. Crowder,
87
T. J. Cullen,
22
A. Cumming,
35
L. Cunningham,
35
E. Cuoco,
33
T. Dal Canton,
67
S. L. Danilishin,
35
S. D’Antonio,
15
K. Danzmann,
18
,
10
A. Dasgupta,
88
C. F. Da Silva Costa,
6
V. Dattilo,
33
I. Dave,
47
M. Davier,
23
G. S. Davies,
35
D. Davis,
34
E. J. Daw,
89
B. Day,
43
R. Day,
33
S. De,
34
D. DeBra,
39
G. Debreczeni,
37
J. Degallaix,
64
M. De Laurentis,
66
,
5
S. Del ́eglise,
59
W. Del Pozzo,
44
T. Denker,
10
T. Dent,
10
V. Dergachev,
28
R. De Rosa,
66
,
5
R. T. DeRosa,
7
R. DeSalvo,
90
J. Devenson,
49
R. C. Devine,
30
S. Dhurandhar,
16
M. C. D ́ıaz,
86
L. Di Fiore,
5
M. Di Giovanni,
91
,
92
T. Di Girolamo,
66
,
5
A. Di Lieto,
19
,
20
S. Di Pace,
80
,
27
I. Di Palma,
28
,
80
,
27
A. Di Virgilio,
20
Z. Doctor,
76
V. Dolique,
64
F. Donovan,
12
K. L. Dooley,
72
S. Doravari,
10
I. Dorrington,
93
R. Douglas,
35
M. Dovale
́
Alvarez,
44
T. P. Downes,
17
M. Drago,
10
R. W. P. Drever,
1
J. C. Driggers,
36
Z. Du,
70
M. Ducrot,
8
S. E. Dwyer,
36
T. B. Edo,
89
M. C. Edwards,
60
A. Effler,
7
H.-B. Eggenstein,
10
P. Ehrens,
1
J. Eichholz,
1
S. S. Eikenberry,
6
R. A. Eisenstein,
12
R. C. Essick,
12
Z. Etienne,
30
T. Etzel,
1
M. Evans,
12
T. M. Evans,
7
R. Everett,
73
M. Factourovich,
38
V. Fafone,
25
,
15
,
14
H. Fair,
34
S. Fairhurst,
93
X. Fan,
70
S. Farinon,
46
B. Farr,
76
W. M. Farr,
44
E. J. Fauchon-Jones,
93
M. Favata,
94
M. Fays,
93
H. Fehrmann,
10
M. M. Fejer,
39
A. Fern ́andez Galiana,
12
I. Ferrante,
19
,
20
E. C. Ferreira,
13
F. Ferrini,
33
F. Fidecaro,
19
,
20
I. Fiori,
33
D. Fiorucci,
29
R. P. Fisher,
34
R. Flaminio,
64
,
95
M. Fletcher,
35
H. Fong,
96
S. S. Forsyth,
43
J.-D. Fournier,
53
S. Frasca,
80
,
27
F. Frasconi,
20
Z. Frei,
97
A. Freise,
44
R. Frey,
58
V. Frey,
23
E. M. Fries,
1
P. Fritschel,
12
V. V. Frolov,
7
P. Fulda,
6
,
67
M. Fyffe,
7
H. Gabbard,
10
B. U. Gadre,
16
S. M. Gaebel,
44
J. R. Gair,
98
L. Gammaitoni,
31
S. G. Gaonkar,
16
F. Garufi,
66
,
5
G. Gaur,
99
V. Gayathri,
100
N. Gehrels,
67
G. Gemme,
46
E. Genin,
33
A. Gennai,
20
J. George,
47
L. Gergely,
101
V. Germain,
8
S. Ghonge,
102
Abhirup Ghosh,
102
Archisman Ghosh,
11
,
102
S. Ghosh,
52
,
11
J. A. Giaime,
2
,
7
K. D. Giardina,
7
A. Giazotto,
20
K. Gill,
103
A. Glaefke,
35
E. Goetz,
10
R. Goetz,
6
L. Gondan,
97
G. Gonz ́alez,
2
J. M. Gonzalez Castro,
19
,
20
A. Gopakumar,
104
M. L. Gorodetsky,
48
S. E. Gossan,
1
M. Gosselin,
33
R. Gouaty,
8
A. Grado,
105
,
5
C. Graef,
35
M. Granata,
64
A. Grant,
35
S. Gras,
12
C. Gray,
36
G. Greco,
56
,
57
A. C. Green,
44
P. Groot,
52
H. Grote,
10
S. Grunewald,
28
G. M. Guidi,
56
,
57
X. Guo,
70
A. Gupta,
16
M. K. Gupta,
88
K. E. Gushwa,
1
E. K. Gustafson,
1
R. Gustafson,
106
J. J. Hacker,
22
B. R. Hall,
55
E. D. Hall,
1
G. Hammond,
35
M. Haney,
104
M. M. Hanke,
10
J. Hanks,
36
C. Hanna,
73
J. Hanson,
7
T. Hardwick,
2
J. Harms,
56
,
57
G. M. Harry,
3
arXiv:1611.02972v1 [gr-qc] 9 Nov 2016
2
I. W. Harry,
28
M. J. Hart,
35
M. T. Hartman,
6
C.-J. Haster,
44
,
96
K. Haughian,
35
J. Healy,
107
A. Heidmann,
59
M. C. Heintze,
7
H. Heitmann,
53
P. Hello,
23
G. Hemming,
33
M. Hendry,
35
I. S. Heng,
35
J. Hennig,
35
J. Henry,
107
A. W. Heptonstall,
1
M. Heurs,
10
,
18
S. Hild,
35
D. Hoak,
33
D. Hofman,
64
K. Holt,
7
D. E. Holz,
76
P. Hopkins,
93
J. Hough,
35
E. A. Houston,
35
E. J. Howell,
51
Y. M. Hu,
10
E. A. Huerta,
108
D. Huet,
23
B. Hughey,
103
S. Husa,
85
S. H. Huttner,
35
T. Huynh-Dinh,
7
N. Indik,
10
D. R. Ingram,
36
R. Inta,
71
H. N. Isa,
35
J.-M. Isac,
59
M. Isi,
1
T. Isogai,
12
B. R. Iyer,
102
K. Izumi,
36
T. Jacqmin,
59
K. Jani,
43
P. Jaranowski,
109
S. Jawahar,
110
F. Jim ́enez-Forteza,
85
W. W. Johnson,
2
D. I. Jones,
111
R. Jones,
35
R. J. G. Jonker,
11
L. Ju,
51
J. Junker,
10
C. V. Kalaghatgi,
93
S. Kandhasamy,
72
G. Kang,
78
J. B. Kanner,
1
S. Karki,
58
K. S. Karvinen,
10
M. Kasprzack,
2
E. Katsavounidis,
12
W. Katzman,
7
S. Kaufer,
18
T. Kaur,
51
K. Kawabe,
36
F. K ́ef ́elian,
53
D. Keitel,
85
D. B. Kelley,
34
R. Kennedy,
89
J. S. Key,
112
F. Y. Khalili,
48
I. Khan,
14
S. Khan,
93
Z. Khan,
88
E. A. Khazanov,
113
N. Kijbunchoo,
36
Chunglee Kim,
114
J. C. Kim,
115
Whansun Kim,
116
W. Kim,
69
Y.-M. Kim,
117
,
114
S. J. Kimbrell,
43
E. J. King,
69
P. J. King,
36
R. Kirchhoff,
10
J. S. Kissel,
36
B. Klein,
84
L. Kleybolte,
26
S. Klimenko,
6
P. Koch,
10
S. M. Koehlenbeck,
10
S. Koley,
11
V. Kondrashov,
1
A. Kontos,
12
M. Korobko,
26
W. Z. Korth,
1
I. Kowalska,
61
D. B. Kozak,
1
C. Kr
̈
amer,
10
V. Kringel,
10
B. Krishnan,
10
A. Kr ́olak,
118
,
119
G. Kuehn,
10
P. Kumar,
96
R. Kumar,
88
L. Kuo,
74
A. Kutynia,
118
B. D. Lackey,
28
,
34
M. Landry,
36
R. N. Lang,
17
J. Lange,
107
B. Lantz,
39
R. K. Lanza,
12
A. Lartaux-Vollard,
23
P. D. Lasky,
120
M. Laxen,
7
A. Lazzarini,
1
C. Lazzaro,
41
P. Leaci,
80
,
27
S. Leavey,
35
E. O. Lebigot,
29
C. H. Lee,
117
H. K. Lee,
121
H. M. Lee,
114
K. Lee,
35
J. Lehmann,
10
A. Lenon,
30
M. Leonardi,
91
,
92
J. R. Leong,
10
N. Leroy,
23
N. Letendre,
8
Y. Levin,
120
T. G. F. Li,
122
A. Libson,
12
T. B. Littenberg,
123
J. Liu,
51
N. A. Lockerbie,
110
A. L. Lombardi,
43
L. T. London,
93
J. E. Lord,
34
M. Lorenzini,
14
,
15
V. Loriette,
124
M. Lormand,
7
G. Losurdo,
20
J. D. Lough,
10
,
18
C. O. Lousto,
107
G. Lovelace,
22
H. L
̈
uck,
18
,
10
A. P. Lundgren,
10
R. Lynch,
12
Y. Ma,
50
S. Macfoy,
49
B. Machenschalk,
10
M. MacInnis,
12
D. M. Macleod,
2
F. Maga ̃na-Sandoval,
34
E. Majorana,
27
I. Maksimovic,
124
V. Malvezzi,
25
,
15
N. Man,
53
V. Mandic,
125
V. Mangano,
35
G. L. Mansell,
21
M. Manske,
17
M. Mantovani,
33
F. Marchesoni,
126
,
32
F. Marion,
8
S. M ́arka,
38
Z. M ́arka,
38
A. S. Markosyan,
39
E. Maros,
1
F. Martelli,
56
,
57
L. Martellini,
53
I. W. Martin,
35
D. V. Martynov,
12
K. Mason,
12
A. Masserot,
8
T. J. Massinger,
1
M. Masso-Reid,
35
S. Mastrogiovanni,
80
,
27
F. Matichard,
12
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1
L. Matone,
38
N. Mavalvala,
12
N. Mazumder,
55
R. McCarthy,
36
D. E. McClelland,
21
S. McCormick,
7
C. McGrath,
17
S. C. McGuire,
127
G. McIntyre,
1
J. McIver,
1
D. J. McManus,
21
T. McRae,
21
S. T. McWilliams,
30
D. Meacher,
53
,
73
G. D. Meadors,
28
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10
J. Meidam,
11
A. Melatos,
128
G. Mendell,
36
D. Mendoza-Gandara,
10
R. A. Mercer,
17
E. L. Merilh,
36
M. Merzougui,
53
S. Meshkov,
1
C. Messenger,
35
C. Messick,
73
R. Metzdorff,
59
P. M. Meyers,
125
F. Mezzani,
27
,
80
H. Miao,
44
C. Michel,
64
H. Middleton,
44
E. E. Mikhailov,
129
L. Milano,
66
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5
A. L. Miller,
6
,
80
,
27
A. Miller,
84
B. B. Miller,
84
J. Miller,
12
M. Millhouse,
83
Y. Minenkov,
15
J. Ming,
28
S. Mirshekari,
130
C. Mishra,
102
S. Mitra,
16
V. P. Mitrofanov,
48
G. Mitselmakher,
6
R. Mittleman,
12
A. Moggi,
20
M. Mohan,
33
S. R. P. Mohapatra,
12
M. Montani,
56
,
57
B. C. Moore,
94
C. J. Moore,
79
D. Moraru,
36
G. Moreno,
36
S. R. Morriss,
86
B. Mours,
8
C. M. Mow-Lowry,
44
G. Mueller,
6
A. W. Muir,
93
Arunava Mukherjee,
102
D. Mukherjee,
17
S. Mukherjee,
86
N. Mukund,
16
A. Mullavey,
7
J. Munch,
69
E. A. M. Muniz,
22
P. G. Murray,
35
A. Mytidis,
6
K. Napier,
43
I. Nardecchia,
25
,
15
L. Naticchioni,
80
,
27
G. Nelemans,
52
,
11
T. J. N. Nelson,
7
M. Neri,
45
,
46
M. Nery,
10
A. Neunzert,
106
J. M. Newport,
3
G. Newton,
35
T. T. Nguyen,
21
S. Nissanke,
52
,
11
A. Nitz,
10
A. Noack,
10
F. Nocera,
33
D. Nolting,
7
M. E. N. Normandin,
86
L. K. Nuttall,
34
J. Oberling,
36
E. Ochsner,
17
E. Oelker,
12
G. H. Ogin,
131
J. J. Oh,
116
S. H. Oh,
116
F. Ohme,
93
,
10
M. Oliver,
85
P. Oppermann,
10
Richard J. Oram,
7
B. O’Reilly,
7
R. O’Shaughnessy,
107
D. J. Ottaway,
69
H. Overmier,
7
B. J. Owen,
71
A. E. Pace,
73
J. Page,
123
A. Pai,
100
S. A. Pai,
47
J. R. Palamos,
58
O. Palashov,
113
C. Palomba,
27
A. Pal-Singh,
26
H. Pan,
74
C. Pankow,
84
F. Pannarale,
93
B. C. Pant,
47
F. Paoletti,
33
,
20
A. Paoli,
33
M. A. Papa,
28
,
17
,
10
H. R. Paris,
39
W. Parker,
7
D. Pascucci,
35
A. Pasqualetti,
33
R. Passaquieti,
19
,
20
D. Passuello,
20
B. Patricelli,
19
,
20
B. L. Pearlstone,
35
M. Pedraza,
1
R. Pedurand,
64
,
132
L. Pekowsky,
34
A. Pele,
7
S. Penn,
133
C. J. Perez,
36
A. Perreca,
1
L. M. Perri,
84
H. P. Pfeiffer,
96
M. Phelps,
35
O. J. Piccinni,
80
,
27
M. Pichot,
53
F. Piergiovanni,
56
,
57
V. Pierro,
9
G. Pillant,
33
L. Pinard,
64
I. M. Pinto,
9
M. Pitkin,
35
M. Poe,
17
R. Poggiani,
19
,
20
P. Popolizio,
33
A. Post,
10
J. Powell,
35
J. Prasad,
16
J. W. W. Pratt,
103
V. Predoi,
93
T. Prestegard,
125
,
17
M. Prijatelj,
10
,
33
M. Principe,
9
S. Privitera,
28
G. A. Prodi,
91
,
92
L. G. Prokhorov,
48
O. Puncken,
10
M. Punturo,
32
P. Puppo,
27
M. P
̈
urrer,
28
H. Qi,
17
J. Qin,
51
S. Qiu,
120
V. Quetschke,
86
E. A. Quintero,
1
R. Quitzow-James,
58
F. J. Raab,
36
D. S. Rabeling,
21
H. Radkins,
36
P. Raffai,
97
S. Raja,
47
C. Rajan,
47
M. Rakhmanov,
86
P. Rapagnani,
80
,
27
V. Raymond,
28
M. Razzano,
19
,
20
V. Re,
25
J. Read,
22
T. Regimbau,
53
L. Rei,
46
S. Reid,
49
D. H. Reitze,
1
,
6
H. Rew,
129
S. D. Reyes,
34
E. Rhoades,
103
F. Ricci,
80
,
27
K. Riles,
106
M. Rizzo,
107
N. A. Robertson,
1
,
35
R. Robie,
35
F. Robinet,
23
A. Rocchi,
15
L. Rolland,
8
J. G. Rollins,
1
V. J. Roma,
58
R. Romano,
4
,
5
J. H. Romie,
7
D. Rosi ́nska,
134
,
42
S. Rowan,
35
A. R
̈
udiger,
10
P. Ruggi,
33
3
K. Ryan,
36
S. Sachdev,
1
T. Sadecki,
36
L. Sadeghian,
17
M. Sakellariadou,
135
L. Salconi,
33
M. Saleem,
100
F. Salemi,
10
A. Samajdar,
136
L. Sammut,
120
L. M. Sampson,
84
E. J. Sanchez,
1
V. Sandberg,
36
J. R. Sanders,
34
B. Sassolas,
64
B. S. Sathyaprakash,
73
,
93
P. R. Saulson,
34
O. Sauter,
106
R. L. Savage,
36
A. Sawadsky,
18
P. Schale,
58
J. Scheuer,
84
E. Schmidt,
103
J. Schmidt,
10
P. Schmidt,
1
,
50
R. Schnabel,
26
R. M. S. Schofield,
58
A. Sch
̈
onbeck,
26
E. Schreiber,
10
D. Schuette,
10
,
18
B. F. Schutz,
93
,
28
S. G. Schwalbe,
103
J. Scott,
35
S. M. Scott,
21
D. Sellers,
7
A. S. Sengupta,
137
D. Sentenac,
33
V. Sequino,
25
,
15
A. Sergeev,
113
Y. Setyawati,
52
,
11
D. A. Shaddock,
21
T. J. Shaffer,
36
M. S. Shahriar,
84
B. Shapiro,
39
P. Shawhan,
63
A. Sheperd,
17
D. H. Shoemaker,
12
D. M. Shoemaker,
43
K. Siellez,
43
X. Siemens,
17
M. Sieniawska,
42
D. Sigg,
36
A. D. Silva,
13
A. Singer,
1
L. P. Singer,
67
A. Singh,
28
,
10
,
18
R. Singh,
2
A. Singhal,
14
A. M. Sintes,
85
B. J. J. Slagmolen,
21
B. Smith,
7
J. R. Smith,
22
R. J. E. Smith,
1
E. J. Son,
116
B. Sorazu,
35
F. Sorrentino,
46
T. Souradeep,
16
A. P. Spencer,
35
A. K. Srivastava,
88
A. Staley,
38
M. Steinke,
10
J. Steinlechner,
35
S. Steinlechner,
26
,
35
D. Steinmeyer,
10
,
18
B. C. Stephens,
17
S. P. Stevenson,
44
R. Stone,
86
K. A. Strain,
35
N. Straniero,
64
G. Stratta,
56
,
57
S. E. Strigin,
48
R. Sturani,
130
A. L. Stuver,
7
T. Z. Summerscales,
138
L. Sun,
128
S. Sunil,
88
P. J. Sutton,
93
B. L. Swinkels,
33
M. J. Szczepa ́nczyk,
103
M. Tacca,
29
D. Talukder,
58
D. B. Tanner,
6
M. T ́apai,
101
A. Taracchini,
28
R. Taylor,
1
T. Theeg,
10
E. G. Thomas,
44
M. Thomas,
7
P. Thomas,
36
K. A. Thorne,
7
E. Thrane,
120
T. Tippens,
43
S. Tiwari,
14
,
92
V. Tiwari,
93
K. V. Tokmakov,
110
K. Toland,
35
C. Tomlinson,
89
M. Tonelli,
19
,
20
Z. Tornasi,
35
C. I. Torrie,
1
D. T
̈
oyr
̈
a,
44
F. Travasso,
31
,
32
G. Traylor,
7
D. Trifir`o,
72
J. Trinastic,
6
M. C. Tringali,
91
,
92
L. Trozzo,
139
,
20
M. Tse,
12
R. Tso,
1
M. Turconi,
53
D. Tuyenbayev,
86
D. Ugolini,
140
C. S. Unnikrishnan,
104
A. L. Urban,
1
S. A. Usman,
93
H. Vahlbruch,
18
G. Vajente,
1
G. Valdes,
86
N. van Bakel,
11
M. van Beuzekom,
11
J. F. J. van den Brand,
62
,
11
C. Van Den Broeck,
11
D. C. Vander-Hyde,
34
L. van der Schaaf,
11
J. V. van Heijningen,
11
A. A. van Veggel,
35
M. Vardaro,
40
,
41
V. Varma,
50
S. Vass,
1
M. Vas ́uth,
37
A. Vecchio,
44
G. Vedovato,
41
J. Veitch,
44
P. J. Veitch,
69
K. Venkateswara,
141
G. Venugopalan,
1
D. Verkindt,
8
F. Vetrano,
56
,
57
A. Vicer ́e,
56
,
57
A. D. Viets,
17
S. Vinciguerra,
44
D. J. Vine,
49
J.-Y. Vinet,
53
S. Vitale,
12
T. Vo,
34
H. Vocca,
31
,
32
C. Vorvick,
36
D. V. Voss,
6
W. D. Vousden,
44
S. P. Vyatchanin,
48
A. R. Wade,
1
L. E. Wade,
77
M. Wade,
77
M. Walker,
2
L. Wallace,
1
S. Walsh,
28
,
10
G. Wang,
14
,
57
H. Wang,
44
M. Wang,
44
Y. Wang,
51
R. L. Ward,
21
J. Warner,
36
M. Was,
8
J. Watchi,
81
B. Weaver,
36
L.-W. Wei,
53
M. Weinert,
10
A. J. Weinstein,
1
R. Weiss,
12
L. Wen,
51
P. Weßels,
10
T. Westphal,
10
K. Wette,
10
J. T. Whelan,
107
B. F. Whiting,
6
C. Whittle,
120
D. Williams,
35
R. D. Williams,
1
A. R. Williamson,
93
J. L. Willis,
142
B. Willke,
18
,
10
M. H. Wimmer,
10
,
18
W. Winkler,
10
C. C. Wipf,
1
H. Wittel,
10
,
18
G. Woan,
35
J. Woehler,
10
J. Worden,
36
J. L. Wright,
35
D. S. Wu,
10
G. Wu,
7
W. Yam,
12
H. Yamamoto,
1
C. C. Yancey,
63
M. J. Yap,
21
Hang Yu,
12
Haocun Yu,
12
M. Yvert,
8
A. Zadro ̇zny,
118
L. Zangrando,
41
M. Zanolin,
103
J.-P. Zendri,
41
M. Zevin,
84
L. Zhang,
1
M. Zhang,
129
T. Zhang,
35
Y. Zhang,
107
C. Zhao,
51
M. Zhou,
84
Z. Zhou,
84
S. J. Zhu,
28
,
10
X. J. Zhu,
51
M. E. Zucker,
1
,
12
and J. Zweizig
1
(LIGO Scientific Collaboration and Virgo Collaboration)
∗
Deceased, March 2016.
1
LIGO, California Institute of Technology, Pasadena, CA 91125, USA
2
Louisiana State University, Baton Rouge, LA 70803, USA
3
American University, Washington, D.C. 20016, USA
4
Universit`a di Salerno, Fisciano, I-84084 Salerno, Italy
5
INFN, Sezione di Napoli, Complesso Universitario di Monte S.Angelo, I-80126 Napoli, Italy
6
University of Florida, Gainesville, FL 32611, USA
7
LIGO Livingston Observatory, Livingston, LA 70754, USA
8
Laboratoire d’Annecy-le-Vieux de Physique des Particules (LAPP),
Universit ́e Savoie Mont Blanc, CNRS/IN2P3, F-74941 Annecy-le-Vieux, France
9
University of Sannio at Benevento, I-82100 Benevento,
Italy and INFN, Sezione di Napoli, I-80100 Napoli, Italy
10
Albert-Einstein-Institut, Max-Planck-Institut f
̈
ur Gravitationsphysik, D-30167 Hannover, Germany
11
Nikhef, Science Park, 1098 XG Amsterdam, The Netherlands
12
LIGO, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
13
Instituto Nacional de Pesquisas Espaciais, 12227-010 S ̃ao Jos ́e dos Campos, S ̃ao Paulo, Brazil
14
INFN, Gran Sasso Science Institute, I-67100 L’Aquila, Italy
15
INFN, Sezione di Roma Tor Vergata, I-00133 Roma, Italy
16
Inter-University Centre for Astronomy and Astrophysics, Pune 411007, India
17
University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
18
Leibniz Universit
̈
at Hannover, D-30167 Hannover, Germany
19
Universit`a di Pisa, I-56127 Pisa, Italy
20
INFN, Sezione di Pisa, I-56127 Pisa, Italy
21
Australian National University, Canberra, Australian Capital Territory 0200, Australia
4
22
California State University Fullerton, Fullerton, CA 92831, USA
23
LAL, Univ. Paris-Sud, CNRS/IN2P3, Universit ́e Paris-Saclay, F-91898 Orsay, France
24
Chennai Mathematical Institute, Chennai 603103, India
25
Universit`a di Roma Tor Vergata, I-00133 Roma, Italy
26
Universit
̈
at Hamburg, D-22761 Hamburg, Germany
27
INFN, Sezione di Roma, I-00185 Roma, Italy
28
Albert-Einstein-Institut, Max-Planck-Institut f
̈
ur Gravitationsphysik, D-14476 Potsdam-Golm, Germany
29
APC, AstroParticule et Cosmologie, Universit ́e Paris Diderot,
CNRS/IN2P3, CEA/Irfu, Observatoire de Paris,
Sorbonne Paris Cit ́e, F-75205 Paris Cedex 13, France
30
West Virginia University, Morgantown, WV 26506, USA
31
Universit`a di Perugia, I-06123 Perugia, Italy
32
INFN, Sezione di Perugia, I-06123 Perugia, Italy
33
European Gravitational Observatory (EGO), I-56021 Cascina, Pisa, Italy
34
Syracuse University, Syracuse, NY 13244, USA
35
SUPA, University of Glasgow, Glasgow G12 8QQ, United Kingdom
36
LIGO Hanford Observatory, Richland, WA 99352, USA
37
Wigner RCP, RMKI, H-1121 Budapest, Konkoly Thege Mikl ́os ́ut 29-33, Hungary
38
Columbia University, New York, NY 10027, USA
39
Stanford University, Stanford, CA 94305, USA
40
Universit`a di Padova, Dipartimento di Fisica e Astronomia, I-35131 Padova, Italy
41
INFN, Sezione di Padova, I-35131 Padova, Italy
42
Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, 00-716, Warsaw, Poland
43
Center for Relativistic Astrophysics and School of Physics,
Georgia Institute of Technology, Atlanta, GA 30332, USA
44
University of Birmingham, Birmingham B15 2TT, United Kingdom
45
Universit`a degli Studi di Genova, I-16146 Genova, Italy
46
INFN, Sezione di Genova, I-16146 Genova, Italy
47
RRCAT, Indore MP 452013, India
48
Faculty of Physics, Lomonosov Moscow State University, Moscow 119991, Russia
49
SUPA, University of the West of Scotland, Paisley PA1 2BE, United Kingdom
50
Caltech CaRT, Pasadena, CA 91125, USA
51
University of Western Australia, Crawley, Western Australia 6009, Australia
52
Department of Astrophysics/IMAPP, Radboud University Nijmegen,
P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
53
Artemis, Universit ́e Cˆote d’Azur, CNRS, Observatoire Cˆote d’Azur, CS 34229, F-06304 Nice Cedex 4, France
54
Institut de Physique de Rennes, CNRS, Universit ́e de Rennes 1, F-35042 Rennes, France
55
Washington State University, Pullman, WA 99164, USA
56
Universit`a degli Studi di Urbino ’Carlo Bo’, I-61029 Urbino, Italy
57
INFN, Sezione di Firenze, I-50019 Sesto Fiorentino, Firenze, Italy
58
University of Oregon, Eugene, OR 97403, USA
59
Laboratoire Kastler Brossel, UPMC-Sorbonne Universit ́es, CNRS,
ENS-PSL Research University, Coll`ege de France, F-75005 Paris, France
60
Carleton College, Northfield, MN 55057, USA
61
Astronomical Observatory Warsaw University, 00-478 Warsaw, Poland
62
VU University Amsterdam, 1081 HV Amsterdam, The Netherlands
63
University of Maryland, College Park, MD 20742, USA
64
Laboratoire des Mat ́eriaux Avanc ́es (LMA), CNRS/IN2P3, F-69622 Villeurbanne, France
65
Universit ́e Claude Bernard Lyon 1, F-69622 Villeurbanne, France
66
Universit`a di Napoli ’Federico II’, Complesso Universitario di Monte S.Angelo, I-80126 Napoli, Italy
67
NASA/Goddard Space Flight Center, Greenbelt, MD 20771, USA
68
RESCEU, University of Tokyo, Tokyo, 113-0033, Japan.
69
University of Adelaide, Adelaide, South Australia 5005, Australia
70
Tsinghua University, Beijing 100084, China
71
Texas Tech University, Lubbock, TX 79409, USA
72
The University of Mississippi, University, MS 38677, USA
73
The Pennsylvania State University, University Park, PA 16802, USA
74
National Tsing Hua University, Hsinchu City, 30013 Taiwan, Republic of China
75
Charles Sturt University, Wagga Wagga, New South Wales 2678, Australia
76
University of Chicago, Chicago, IL 60637, USA
77
Kenyon College, Gambier, OH 43022, USA
78
Korea Institute of Science and Technology Information, Daejeon 305-806, Korea
79
University of Cambridge, Cambridge CB2 1TN, United Kingdom
80
Universit`a di Roma ’La Sapienza’, I-00185 Roma, Italy
5
81
University of Brussels, Brussels 1050, Belgium
82
Sonoma State University, Rohnert Park, CA 94928, USA
83
Montana State University, Bozeman, MT 59717, USA
84
Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA),
Northwestern University, Evanston, IL 60208, USA
85
Universitat de les Illes Balears, IAC3—IEEC, E-07122 Palma de Mallorca, Spain
86
The University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
87
Bellevue College, Bellevue, WA 98007, USA
88
Institute for Plasma Research, Bhat, Gandhinagar 382428, India
89
The University of Sheffield, Sheffield S10 2TN, United Kingdom
90
California State University, Los Angeles, 5154 State University Dr, Los Angeles, CA 90032, USA
91
Universit`a di Trento, Dipartimento di Fisica, I-38123 Povo, Trento, Italy
92
INFN, Trento Institute for Fundamental Physics and Applications, I-38123 Povo, Trento, Italy
93
Cardiff University, Cardiff CF24 3AA, United Kingdom
94
Montclair State University, Montclair, NJ 07043, USA
95
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
96
Canadian Institute for Theoretical Astrophysics,
University of Toronto, Toronto, Ontario M5S 3H8, Canada
97
MTA E
̈
otv
̈
os University, “Lendulet” Astrophysics Research Group, Budapest 1117, Hungary
98
School of Mathematics, University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
99
University and Institute of Advanced Research, Gandhinagar, Gujarat 382007, India
100
IISER-TVM, CET Campus, Trivandrum Kerala 695016, India
101
University of Szeged, D ́om t ́er 9, Szeged 6720, Hungary
102
International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bengaluru 560089, India
103
Embry-Riddle Aeronautical University, Prescott, AZ 86301, USA
104
Tata Institute of Fundamental Research, Mumbai 400005, India
105
INAF, Osservatorio Astronomico di Capodimonte, I-80131, Napoli, Italy
106
University of Michigan, Ann Arbor, MI 48109, USA
107
Rochester Institute of Technology, Rochester, NY 14623, USA
108
NCSA, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
109
University of Bia lystok, 15-424 Bia lystok, Poland
110
SUPA, University of Strathclyde, Glasgow G1 1XQ, United Kingdom
111
University of Southampton, Southampton SO17 1BJ, United Kingdom
112
University of Washington Bothell, 18115 Campus Way NE, Bothell, WA 98011, USA
113
Institute of Applied Physics, Nizhny Novgorod, 603950, Russia
114
Seoul National University, Seoul 151-742, Korea
115
Inje University Gimhae, 621-749 South Gyeongsang, Korea
116
National Institute for Mathematical Sciences, Daejeon 305-390, Korea
117
Pusan National University, Busan 609-735, Korea
118
NCBJ, 05-400
́
Swierk-Otwock, Poland
119
Institute of Mathematics, Polish Academy of Sciences, 00656 Warsaw, Poland
120
Monash University, Victoria 3800, Australia
121
Hanyang University, Seoul 133-791, Korea
122
The Chinese University of Hong Kong, Shatin, NT, Hong Kong
123
University of Alabama in Huntsville, Huntsville, AL 35899, USA
124
ESPCI, CNRS, F-75005 Paris, France
125
University of Minnesota, Minneapolis, MN 55455, USA
126
Universit`a di Camerino, Dipartimento di Fisica, I-62032 Camerino, Italy
127
Southern University and A&M College, Baton Rouge, LA 70813, USA
128
The University of Melbourne, Parkville, Victoria 3010, Australia
129
College of William and Mary, Williamsburg, VA 23187, USA
130
Instituto de F ́ısica Te ́orica, University Estadual Paulista/ICTP South
American Institute for Fundamental Research, S ̃ao Paulo SP 01140-070, Brazil
131
Whitman College, 345 Boyer Avenue, Walla Walla, WA 99362 USA
132
Universit ́e de Lyon, F-69361 Lyon, France
133
Hobart and William Smith Colleges, Geneva, NY 14456, USA
134
Janusz Gil Institute of Astronomy, University of Zielona G ́ora, 65-265 Zielona G ́ora, Poland
135
King’s College London, University of London, London WC2R 2LS, United Kingdom
136
IISER-Kolkata, Mohanpur, West Bengal 741252, India
137
Indian Institute of Technology, Gandhinagar Ahmedabad Gujarat 382424, India
138
Andrews University, Berrien Springs, MI 49104, USA
139
Universit`a di Siena, I-53100 Siena, Italy
140
Trinity University, San Antonio, TX 78212, USA
141
University of Washington, Seattle, WA 98195, USA
6
142
Abilene Christian University, Abilene, TX 79699, USA
We present the results from an all-sky search for short-duration gravitational waves in the data
of the first run of the Advanced LIGO detectors between September 2015 and January 2016. The
search algorithms use minimal assumptions on the signal morphology, so they are sensitive to a wide
range of sources emitting gravitational waves. The analyses target transient signals with duration
ranging from milliseconds to seconds over the frequency band of 32 to 4096 Hz. The first observed
gravitational-wave event, GW150914, has been detected with high confidence in this search; other
known gravitational-wave events fall below the search’s sensitivity. Besides GW150914, all of the
search results are consistent with the expected rate of accidental noise coincidences. Finally, we
estimate rate-density limits for a broad range of non-BBH transient gravitational-wave sources as a
function of their gravitational radiation emission energy and their characteristic frequency. These
rate-density upper-limits are stricter than those previously published by an order-of-magnitude.
I. INTRODUCTION
The first observing period of the Advanced LIGO
detectors [1, 2] has been completed recently with the
most sensitive gravitational-wave (GW) detectors ever
built. The two LIGO observatories in Hanford, WA
and Livingston, LA achieved a major milestone in grav-
itational wave astronomy: the first direct detection of
gravitational waves on September 14, 2015, referred as
GW150914 [3]. Advanced LIGO is the first of a new gen-
eration of instruments, including GEO 600 [4], Advanced
Virgo [2], KAGRA [5] and LIGO-India [6].
This paper reports on a search for short-duration tran-
sient gravitational-wave events, commonly referred to as
GW bursts, during the first observing run (O1) of the Ad-
vanced LIGO detectors, from September 2015 to January
2016. The first 16 days of coincident data have been al-
ready analyzed, resulting in a high-significance detection
statement for the GW150914 event [7]. GW bursts can be
generated by a wide variety of astrophysical sources, such
as merging compact binary systems [8, 9], core-collapse
supernovae of massive stars [10], neutron stars collapsing
to form black holes, pulsar glitches, and cosmic string
cusps [11]. To search broadly for these phenomena, we
employ searches with minimal assumptions regarding the
expected waveform characteristics and the source direc-
tion. The search we report here is more sensitive than
the previous burst searches [12] because of both the in-
creased sensitivity of the Advanced detectors [13] and
improvements in the search algorithms in rejecting tran-
sient non-Gaussian noise artifacts (glitches) [14–17].
The described un-modeled all-sky search for GW
bursts consists of three different algorithms. This pa-
per shows the result of these algorithms, and gives limits
on the rate-density of transient GW events. All of these
algorithms have independently claimed high-significance
detections of GW150914 [7]. The lower-mass GW event,
GW151226 [18], and the LVT151012 candidate [19, 20]
were not detected by these searches.
The paper is organized as follows: in Section II we give
an overview of the O1 data set. In Section III we give a
brief overview of the three search algorithms. The sen-
sitivity of the search is described in Section IV. Finally,
Sections V and VI discuss the search results and their
implications.
II. OBSERVING RUN 1
Our data set extends over 130 calendar days from
September 12, 2015 to January 19, 2016. This first ob-
serving period (called O1) of Advanced LIGO began after
a series of major upgrades to both the Hanford and Liv-
ingston detectors [3].
In the most sensitive frequency band, 100-300 Hz, the
O1 LIGO detectors are 3 to 5 times more sensitive than
the initial LIGO detectors [13]. Future observing runs are
expected to increase sensitivity by an additional factor of
3 [6].
As in the previous LIGO/Virgo searches [21–23], in-
tervals of poor data quality are identified and excluded
from the analysis. To monitor environmental distur-
bances and their influence on the detectors, each observa-
tory is equipped with an array of sensors: seismometers,
accelerometers, microphones, magnetometers, radio re-
ceivers, weather sensors, ac-power line monitors, and a
cosmic-ray detector. Hundreds of thousands of auxiliary
channels within the instrument are also monitored. Char-
acterization of the relationship of the strain data to this
additional information allows many non-GW transients
to be removed with high statistical confidence [7, 24].
The livetime in which the two detectors were individ-
ually locked is about 79 days for H1 and 67 days for L1.
After data quality flags have been applied, the total ana-
lyzable time is about 75 days for H1 and 65 days for L1.
The coincident livetime between H1 and L1 is about 48
days. This livetime includes the 16 days of this coinci-
dent data that has already been analyzed in [7]. Finally,
the estimated calibration uncertainty (1
σ
) below 2 kHz is
less than 10% in amplitude and 10 degrees in phase [25].
The calibration uncertainty above 2 kHz is less certain,
although the limited data obtained at these frequencies
suggests upper bounds of 20% in amplitude and 10 de-
grees in phase. These estimates will be further refined
through future measurements and analyses [26].
III. SEARCHES
This search covers the most sensitive frequency band of
the involved detectors, i.e. 32 - 4096 Hz, and it consists
of the same three burst algorithms used to measure the
7
significance of GW150914 [7]. They consist of two end-
to-end algorithms: coherent Waveburst (cWB) [17, 27]
and omicron-LIB (oLIB) [16]; and a follow-up algorithm
applied to cWB events: BayesWave (BW) [28, 29]. Using
multiple search algorithms has two advantages: it can
provide independent validation of results, and it can also
improve the search sensitivity in regions of parameter
space where a single algorithm outperforms the others.
The three algorithms ran over the 48 days of coincident
data. However, due to internal segmentation
1
the cWB
and BW pipelines only actually analyzed 44 days of this
coincident data. The oLIB analysis loss-time is negligible
and thus oLIB analyzed close to the full 48 days.
The three algorithms also ran in low-latency mode dur-
ing O1. In this mode, both cWB and oLIB produced in-
dependent alerts of the GW150914 event and the result
was validated by a BW follow-up [30].
To characterize the statistical rate of transient noise
glitches occurring simultaneously at the two LIGO sites
by chance, this analysis uses the time-shift method: data
from one interferometer is shifted in time with respect to
the other interferometer by multiple delays much larger
than the maximum GW travel time between the inter-
ferometers. In this way, we can accumulate a significant
duration of estimated background that we use to estimate
the false-alarm rate (FAR) for each algorithm.
We set a FAR threshold of 1 in 100 years for identifying
a detection candidate, which roughly corresponds to a 3
sigma detection statement for the duration of our obser-
vation. If an event in this search were to have a FAR less
than this threshold, a refined analysis (i.e., more time-
shifts) would be performed to assign the appropriate sig-
nificance in the detection statement for this event.
A. Coherent WaveBurst
Coherent WaveBurst (cWB) has been used in multi-
ple searches for transient GWs [12, 23]. It calculates
a maximum-likelihood-ratio statistic for power excesses
identified in the time-frequency domain. A primary se-
lection cut is applied to the network correlation coeffi-
cient
c
c
, which measures the degree of correlation be-
tween the detectors. Events with
c
c
<
0
.
7 are discarded
from the analysis. Events are ranked according to their
coherent network signal-to-noise ratio (SNR)
η
c
, which is
related to the matched-filter SNR, favoring GW signals
correlated in both detectors and suppressing uncorrelated
glitches. A detailed explanation of the algorithm and the
definition of these statistics are given in [7].
The cWB analysis is divided in two frequency bands,
where the splitting frequency is 1024 Hz. For the low-
frequency band, the data is downsampled to reduce the
computational cost of the analysis.
1
The cWB algorithm requires at least 600 s of continuous data to
perform its analysis.
Low-frequency cWB events are divided into three
search classes according to their morphology, as described
in [7]. The
C
1 class is based on cuts which primarily
select so-called “blip” glitches and non-stationary power-
spectrum lines. The former are non-Gaussian noise tran-
sients of unknown origin consisting of a few cycles around
100 Hz. The
C
3 class is based on cuts that select events
whose frequency increases with time, i.e. those similar in
morphology to the merger of compact objects. The
C
2
class is composed of all the remaining events.
The FAR of each identified event is estimated using
the time-slide background distribution of similar class.
Since there are three independent classes, we apply a tri-
als factor of 3 to estimate the final significance. The
high-frequency analysis consists of only a single class.
About 1000 years of coincident background data were
accumulated for the cWB analysis. Fig. 1(a) and 1(b)
report the cumulative FAR as a function of
η
c
for the
low-frequency and high-frequency analyses, respectively,
including the three different classes for the low-frequency
case.
B. Omicron-LIB
Omicron-LIB (oLIB) is a hierarchical search algorithm
that first analyzes the data streams of individual detec-
tors, which we refer to as an incoherent analysis. It then
follows up stretches of data that are potentially correlated
across the detector network, which we refer to as a co-
herent analysis. The incoherent analysis (“Omicron”) [31]
flags stretches of coincident excess power. The coherent
follow-up (“LIB”) [16] models gravitational wave signals
and noise transients with a single sine-Gaussian, and it
produces two different Bayes factors. Each of these Bayes
factors is expressed as the natural logarithm of the ev-
idence ratio of two hypotheses: a GW signal
vs
Gaus-
sian noise (BSN) and a coherent GW signal
vs
incoher-
ent noise transients (BCI). The joint likelihood ratio Λ
of these two Bayes factors is used as ranking statistic to
assign a significance to each event. See [16] for further
technical details on the implementation of these steps.
For this analysis, oLIB events are divided into two
classes, based on the inferred parameters of the best-
fit sine-Gaussian. The exact parameter ranges of these
search classes are chosen in order to group noise tran-
sients of similar morphology together. Particularly noisy
regions of the parameter space are excluded from the
analysis entirely (e.g., events with median quality factor
Q >
108). Both classes contain only events whose median
frequency
f
0
, as estimated by LIB, lies within the range
of 48 - 1024 Hz. The first, analogous to cWB’s C1 class,
is a “low-Q” class that contains only events whose median
quality factor
Q
, lies within the range 0.1 - 2. The second,
analogous to the union of cWB’s C2 and C3 classes, is
a “high-Q” class that contains only events whose median
Q
lies within the range 2 - 108. In both classes, event
candidates were also required to have positive Bayes fac-
8
7
8
9
10
11
12
13
14
Coherent Network SNR,
η
c
10
−
4
10
−
3
10
−
2
10
−
1
10
0
10
1
10
2
10
3
10
4
False Alarm Rate (1/yr)
C1 Background
C2 Background
C3 Background
Search results
(a)
cWB
32-1024 Hz search classes:
C
1 (red),
C
2 (brown),
C
3
(yellow).
8
9
10
11
12
13
Coherent Network SNR,
η
c
10
−
4
10
−
3
10
−
2
10
−
1
10
0
10
1
10
2
10
3
False Alarm Rate (1/yr)
Background
Search results
(b)
cWB
1024-4096 Hz search class.
−
5
0
5
10
15
20
25
30
35
log Λ
10
−
3
10
−
2
10
−
1
10
0
10
1
10
2
10
3
False Alarm Rate
(1
/
yr)
High Q Background
Search results
Low Q Background
(c)
oLIB
48-1024 Hz low-
Q
(dashed) and high-
Q
(solid) search
classes.
−
10
−
5
0
5
10
15
20
25
ln
B
S
,
G
10
−
4
10
−
3
10
−
2
10
−
1
10
0
False Alarm Rate (1/yr)
Background
(d)
BayesWave
followup to cWB 32-1024 Hz search class.
FIG. 1. Search results and backgrounds as a function of the detection statistic for the different searches. The FAR refers to
the rate at which events more significant than the corresponding detection statistic occur. Apart from GW150914 (which is
not reported in these figures), the search results are consistent with the expectations of accidental noise coincidences.
tors, i.e., BSN
>
0 and BCI
>
0, meaning the evidence
for the signal model was greater than the evidences for
the noise models. A trials factor of 2 accounts for these
independent search classes.
The oLIB background analysis is performed using 456
years of background data.
We select single-detector
events with SNR
>
5.0. This is lower than the threshold
of 6.5 adopted in [7] and it is chosen to allow us to make a
significance estimation of low-SNR events. For this rea-
son, we cannot directly compare the two set of results
reported in [7] and in this study using the likelihood ra-
tios Λ, but we have to consider the reported FAR. The
results are presented in Fig. 1(c).
C. BayesWave Follow-up
BayesWave (BW) tests if the data in multiple detectors
are best explained by coincident glitches or a signal, and
it is used as a follow-up to events produced by cWB. It
has been shown that BW is able to increase the detection
confidence for GW signals of complex morphology[14].
The BW algorithm uses a variable number of sine-
Gaussian wavelets to reconstruct the data independently
for the signal and glitch models, then computes the natu-
ral logarithm of the Bayes factor between these two mod-
els, ln
B
sg
. The number of wavelets used is determined
by using a reversible jump Markov chain Monte Carlo,
9
with more complex signals requiring more wavelets [15].
The Bayes factor scales as ln
B
sg
∼
N
ln SNR, where
N
is number of wavelets used. This means the detection
statistic depends on waveform complexity in addition to
SNR. Full details of the algorithm can be found in [28].
In this search, BW followed up events produced by
cWB in any of the three low-frequency search classes
with a coherent network SNR of
η
c
≥
9
.
9 and correlation
coefficient of
c
c
>
0
.
7. There are no additional cuts per-
formed on the data, and all of these events (C1+C2+C3)
are analyzed as a single class. The cumulative FAR as a
function of ln
B
sg
is shown in Fig. 1(d).
IV. SENSITIVITY
The detection efficiency of the search is measured by
adding simulated signals into the detectors’ data and
evaluating whether or not they pass the selection cuts
explained in the Section III for the different search algo-
rithms. A variety of GW signal morphologies were tested,
spanning a wide range of amplitudes and duration, and
with characteristic frequencies within the sensitive band-
width of the detectors. We identify two different wave-
form sets: a set of generic bursts, and a set of simu-
lated astrophysical signals coming from the coalescence
and merging of binary black holes (BBH). All of the re-
sults in this section refer to a FAR detection threshold of
1 in 100 years.
A. Generic bursts
This family includes the waveform types described
in [22], all with elliptical polarization:
gaussian pulses
(GA)
, parametrized by their duration parameter
τ
;
sine-
Gaussian wavelets (SG)
, sinusoids within a Gaussian en-
velope, characterized by the frequency of the sinusoid
f
0
and a quality factor
Q
;
white-noise bursts (WNB)
, white
noise bounded in frequency over a bandwidth ∆
f
and
with a Gaussian envelope, described by the lower fre-
quency
f
low
, ∆
f
, and the duration
τ
. Table I lists the
waveforms that have been considered for this work.
The amplitudes of the test signals are chosen to cover
a wide range of values and are expressed in terms of the
root-mean-square strain amplitude at Earth (before ac-
counting for the detection response patterns), denoted
h
rss
[12]. For this search, we injected signals according
to the distance distribution
p
(
r
) =
r
+
A/r
where
A
is a
constant. The constant
A
is chosen to produce at least
several test events with large
h
rss
.
Table I, shows the
h
rss
value at which 50% of the injec-
tions are detected for each signal morphology and algo-
rithm. There are some morphology-dependent features
that affect each of the different algorithms at the FAR
threshold of 1 in 100 years. These features largely disap-
pear and the different algorithms’ results converge at de-
tection thesholds of higher FAR. For example, the detec-
Morphology
cWB
oLIB
BW
Gaussian pulses
τ
= 0
.
1 ms
34
N/A
N/A
τ
= 2
.
5 ms
33
7.4
N/A
sine-Gaussian wavelets
f
0
= 70 Hz,
Q
= 100
24
N/A
N/A
f
0
= 153 Hz,
Q
= 8
.
9
1.6
1.7
5.4
f
0
= 235 Hz,
Q
= 100
14
1.9
N/A
f
0
= 554 Hz,
Q
= 8
.
9
2.6
2.7
3.6
f
0
= 849 Hz,
Q
= 3
27
3.3
5.4
f
0
= 1615 Hz,
Q
= 100
5.5
-
-
f
0
= 2000 Hz,
Q
= 3
8.7
-
-
f
0
= 2477 Hz,
Q
= 8
.
9
11
-
-
f
0
= 3067 Hz,
Q
= 3
15
-
-
White-Noise Bursts
f
low
= 100 Hz, ∆
f
= 100 Hz,
τ
= 0
.
1 s
2.0
N/A
3.0
f
low
= 250 Hz, ∆
f
= 100 Hz,
τ
= 0
.
1 s
2.2
N/A
9.2
TABLE I. The
h
rss
values, in units of 10
−
22
Hz
−
1
/
2
, at which
50% detection efficiency is achieved at a FAR of 1 in 100 yr
for each of the algorithms, as a function of the injected signal
morphologies. “N/A” denotes that 50% detection efficiency
was not achieved. “-” denotes the waveform was not analyzed
by oLIB and BW because its characteristic frequency is higher
than 1024 Hz.
tion efficiencies are worse for cWB for low-Q morpholo-
gies and high-Q morphologies because these injections
are classified as C1 events. As shown in Fig. 1(a), the
C1 background extends to higher significances than in
the other bins, meaning these high-Q and low-Q events
must have large values of
η
c
to meet the FAR threshold
of 1 in 100 years. The oLIB detection efficiencies, while
non-negligible across all morphologies, never quite reach
50% for some non-sine-Gaussian morphologies because
the template mismatch residuals grow linearly with
h
rss
.
Finally, the detection efficiencies of BW suffers for high-
Q events since its prior range only extends to
Q
= 40.
However, almost every morphology can be detected effi-
ciently by at least one of the algorithms.
Another way to interpret the search sensitivities is to
map them into the minimum amount of energy that needs
to be emitted through GWs for at least half of the sources
to be detected within a given search volume. Assuming
a fixed amount of energy is radiated isotropically away
from the source in GWs of a fixed frequency
f
0
, this
distance
r
0
can be converted into a value of
h
rss
via the
relationship [12]:
E
GW
=
π
2
c
3
G
r
2
0
f
2
0
h
2
0
(1)
Here, we use the
h
rss
from Table I, the central frequency
of each morphology, and a fixed fiducial radius to calcu-
late this energy via Eq. 1. Figure 2 shows this energy as
a function of characteristic frequency assuming a galactic
source at a distance of 10 kpc. When taking into account
the results of all three algorithms, this emission energy is
not strongly dependent on the type of waveform (with ex-
ceptions on an algorithm-by-algorithm basis, as described