arXiv:1711.06843v1 [gr-qc] 18 Nov 2017
All-sky search for long-duration gravitational wave trans
ients in the first Advanced
LIGO observing 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
P. Ajith,
17
B. Allen,
10
,
18
,
19
A. Allocca,
20
,
21
P. A. Altin,
22
A. Ananyeva,
1
S. B. Anderson,
1
W. G. Anderson,
18
S. Appert,
1
K. Arai,
1
M. C. Araya,
1
J. S. Areeda,
23
N. Arnaud,
24
K. G. Arun,
25
S. Ascenzi,
26
,
15
G. Ashton,
10
M. Ast,
27
S. M. Aston,
7
P. Astone,
28
P. Aufmuth,
19
C. Aulbert,
10
A. Avila-Alvarez,
23
S. Babak,
29
P. Bacon,
30
M. K. M. Bader,
11
P. T. Baker,
31
,
32
F. Baldaccini,
33
,
34
G. Ballardin,
35
S. W. Ballmer,
36
J. C. Barayoga,
1
S. E. Barclay,
37
B. C. Barish,
1
D. Barker,
38
F. Barone,
4
,
5
B. Barr,
37
L. Barsotti,
12
M. Barsuglia,
30
D. Barta,
39
J. Bartlett,
38
I. Bartos,
40
R. Bassiri,
41
A. Basti,
20
,
21
J. C. Batch,
38
C. Baune,
10
V. Bavigadda,
35
M. Bazzan,
42
,
43
C. Beer,
10
M. Bejger,
44
I. Belahcene,
24
M. Belgin,
45
A. S. Bell,
37
B. K. Berger,
1
G. Bergmann,
10
C. P. L. Berry,
46
D. Bersanetti,
47
,
48
A. Bertolini,
11
J. Betzwieser,
7
S. Bhagwat,
36
R. Bhandare,
49
I. A. Bilenko,
50
G. Billingsley,
1
C. R. Billman,
6
J. Birch,
7
R. Birney,
51
O. Birnholtz,
10
S. Biscans,
12
,
1
A. Bisht,
19
M. Bitossi,
35
C. Biwer,
36
M. A. Bizouard,
24
J. K. Blackburn,
1
J. Blackman,
52
C. D. Blair,
53
D. G. Blair,
53
R. M. Blair,
38
S. Bloemen,
54
O. Bock,
10
M. Boer,
55
G. Bogaert,
55
A. Bohe,
29
F. Bondu,
56
R. Bonnand,
8
B. A. Boom,
11
R. Bork,
1
V. Boschi,
20
,
21
S. Bose,
57
,
16
Y. Bouffanais,
30
A. Bozzi,
35
C. Bradaschia,
21
P. R. Brady,
18
V. B. Braginsky
†
,
50
M. Branchesi,
58
,
59
J. E. Brau,
60
T. Briant,
61
A. Brillet,
55
M. Brinkmann,
10
V. Brisson,
24
P. Brockill,
18
J. E. Broida,
62
A. F. Brooks,
1
D. A. Brown,
36
D. D. Brown,
46
N. M. Brown,
12
S. Brunett,
1
C. C. Buchanan,
2
A. Buikema,
12
T. Bulik,
63
H. J. Bulten,
64
,
11
A. Buonanno,
29
,
65
D. Buskulic,
8
C. Buy,
30
R. L. Byer,
41
M. Cabero,
10
L. Cadonati,
45
G. Cagnoli,
66
,
67
C. Cahillane,
1
J. Calder ́on Bustillo,
45
T. A. Callister,
1
E. Calloni,
68
,
5
J. B. Camp,
69
M. Canepa,
47
,
48
K. C. Cannon,
70
H. Cao,
71
J. Cao,
72
C. D. Capano,
10
E. Capocasa,
30
F. Carbognani,
35
S. Caride,
73
J. Casanueva Diaz,
24
C. Casentini,
26
,
15
S. Caudill,
18
M. Cavagli`a,
74
F. Cavalier,
24
R. Cavalieri,
35
G. Cella,
21
C. B. Cepeda,
1
L. Cerboni Baiardi,
58
,
59
G. Cerretani,
20
,
21
E. Cesarini,
26
,
15
S. J. Chamberlin,
75
M. Chan,
37
S. Chao,
76
P. Charlton,
77
E. Chassande-Mottin,
30
B. D. Cheeseboro,
31
,
32
H. Y. Chen,
78
Y. Chen,
52
H.-P. Cheng,
6
A. Chincarini,
48
A. Chiummo,
35
T. Chmiel,
79
H. S. Cho,
80
M. Cho,
65
J. H. Chow,
22
N. Christensen,
62
Q. Chu,
53
A. J. K. Chua,
81
S. Chua,
61
S. Chung,
53
G. Ciani,
6
F. Clara,
38
J. A. Clark,
45
F. Cleva,
55
C. Cocchieri,
74
E. Coccia,
14
,
15
P.-F. Cohadon,
61
A. Colla,
82
,
28
C. G. Collette,
83
L. Cominsky,
84
M. Constancio Jr.,
13
L. Conti,
43
S. J. Cooper,
46
T. R. Corbitt,
2
N. Cornish,
85
A. Corsi,
73
S. Cortese,
35
C. A. Costa,
13
M. W. Coughlin,
62
S. B. Coughlin,
86
J.-P. Coulon,
55
S. T. Countryman,
40
P. Couvares,
1
P. B. Covas,
87
E. E. Cowan,
45
D. M. Coward,
53
M. J. Cowart,
7
D. C. Coyne,
1
R. Coyne,
73
J. D. E. Creighton,
18
T. D. Creighton,
88
J. Cripe,
2
S. G. Crowder,
89
T. J. Cullen,
23
A. Cumming,
37
L. Cunningham,
37
E. Cuoco,
35
T. Dal Canton,
69
S. L. Danilishin,
37
S. D’Antonio,
15
K. Danzmann,
19
,
10
A. Dasgupta,
90
C. F. Da Silva Costa,
6
V. Dattilo,
35
I. Dave,
49
M. Davier,
24
G. S. Davies,
37
D. Davis,
36
E. J. Daw,
91
B. Day,
45
R. Day,
35
S. De,
36
D. DeBra,
41
G. Debreczeni,
39
J. Degallaix,
66
M. De Laurentis,
68
,
5
S. Del ́eglise,
61
W. Del Pozzo,
46
T. Denker,
10
T. Dent,
10
V. Dergachev,
29
R. De Rosa,
68
,
5
R. T. DeRosa,
7
R. DeSalvo,
92
R. C. Devine,
31
,
32
S. Dhurandhar,
16
M. C. D ́ıaz,
88
L. Di Fiore,
5
M. Di Giovanni,
93
,
94
T. Di Girolamo,
68
,
5
A. Di Lieto,
20
,
21
S. Di Pace,
82
,
28
I. Di Palma,
29
,
82
,
28
A. Di Virgilio,
21
Z. Doctor,
78
V. Dolique,
66
F. Donovan,
12
K. L. Dooley,
74
S. Doravari,
10
I. Dorrington,
95
R. Douglas,
37
M. Dovale
́
Alvarez,
46
T. P. Downes,
18
M. Drago,
10
R. W. P. Drever,
1
J. C. Driggers,
38
Z. Du,
72
M. Ducrot,
8
S. E. Dwyer,
38
T. B. Edo,
91
M. C. Edwards,
62
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,
31
,
32
T. Etzel,
1
M. Evans,
12
T. M. Evans,
7
R. Everett,
75
M. Factourovich,
40
V. Fafone,
26
,
15
,
14
H. Fair,
36
S. Fairhurst,
95
X. Fan,
72
S. Farinon,
48
B. Farr,
78
W. M. Farr,
46
E. J. Fauchon-Jones,
95
M. Favata,
96
M. Fays,
95
H. Fehrmann,
10
M. M. Fejer,
41
A. Fern ́andez Galiana,
12
I. Ferrante,
20
,
21
E. C. Ferreira,
13
F. Ferrini,
35
F. Fidecaro,
20
,
21
I. Fiori,
35
D. Fiorucci,
30
R. P. Fisher,
36
R. Flaminio,
66
,
97
M. Fletcher,
37
H. Fong,
98
S. S. Forsyth,
45
J.-D. Fournier,
55
S. Frasca,
82
,
28
F. Frasconi,
21
Z. Frei,
99
A. Freise,
46
R. Frey,
60
V. Frey,
24
E. M. Fries,
1
P. Fritschel,
12
V. V. Frolov,
7
P. Fulda,
6
,
69
M. Fyffe,
7
H. Gabbard,
10
B. U. Gadre,
16
S. M. Gaebel,
46
J. R. Gair,
100
L. Gammaitoni,
33
S. G. Gaonkar,
16
F. Garufi,
68
,
5
G. Gaur,
101
V. Gayathri,
102
N. Gehrels,
69
G. Gemme,
48
E. Genin,
35
A. Gennai,
21
J. George,
49
L. Gergely,
103
V. Germain,
8
S. Ghonge,
17
Abhirup Ghosh,
17
Archisman Ghosh,
11
,
17
S. Ghosh,
54
,
11
J. A. Giaime,
2
,
7
K. D. Giardina,
7
A. Giazotto,
21
K. Gill,
104
A. Glaefke,
37
E. Goetz,
10
R. Goetz,
6
L. Gondan,
99
G. Gonz ́alez,
2
J. M. Gonzalez Castro,
20
,
21
A. Gopakumar,
105
M. L. Gorodetsky,
50
S. E. Gossan,
1
M. Gosselin,
35
R. Gouaty,
8
A. Grado,
106
,
5
C. Graef,
37
M. Granata,
66
A. Grant,
37
S. Gras,
12
C. Gray,
38
G. Greco,
58
,
59
A. C. Green,
46
P. Groot,
54
H. Grote,
10
S. Grunewald,
29
G. M. Guidi,
58
,
59
X. Guo,
72
A. Gupta,
16
M. K. Gupta,
90
K. E. Gushwa,
1
2
E. K. Gustafson,
1
R. Gustafson,
107
J. J. Hacker,
23
B. R. Hall,
57
E. D. Hall,
1
G. Hammond,
37
M. Haney,
105
M. M. Hanke,
10
J. Hanks,
38
C. Hanna,
75
J. Hanson,
7
T. Hardwick,
2
J. Harms,
58
,
59
G. M. Harry,
3
I. W. Harry,
29
M. J. Hart,
37
M. T. Hartman,
6
C.-J. Haster,
46
,
98
K. Haughian,
37
J. Healy,
108
A. Heidmann,
61
M. C. Heintze,
7
H. Heitmann,
55
P. Hello,
24
G. Hemming,
35
M. Hendry,
37
I. S. Heng,
37
J. Hennig,
37
J. Henry,
108
A. W. Heptonstall,
1
M. Heurs,
10
,
19
S. Hild,
37
D. Hoak,
35
D. Hofman,
66
K. Holt,
7
D. E. Holz,
78
P. Hopkins,
95
J. Hough,
37
E. A. Houston,
37
E. J. Howell,
53
Y. M. Hu,
10
E. A. Huerta,
109
D. Huet,
24
B. Hughey,
104
S. Husa,
87
S. H. Huttner,
37
T. Huynh-Dinh,
7
N. Indik,
10
D. R. Ingram,
38
R. Inta,
73
H. N. Isa,
37
J.-M. Isac,
61
M. Isi,
1
T. Isogai,
12
B. R. Iyer,
17
K. Izumi,
38
T. Jacqmin,
61
K. Jani,
45
P. Jaranowski,
110
S. Jawahar,
111
F. Jim ́enez-Forteza,
87
W. W. Johnson,
2
N. K. Johnson-McDaniel,
17
D. I. Jones,
112
R. Jones,
37
R. J. G. Jonker,
11
L. Ju,
53
J. Junker,
10
C. V. Kalaghatgi,
95
V. Kalogera,
86
S. Kandhasamy,
74
G. Kang,
80
J. B. Kanner,
1
S. Karki,
60
K. S. Karvinen,
10
M. Kasprzack,
2
E. Katsavounidis,
12
W. Katzman,
7
S. Kaufer,
19
T. Kaur,
53
K. Kawabe,
38
F. K ́ef ́elian,
55
D. Keitel,
87
D. B. Kelley,
36
R. Kennedy,
91
J. S. Key,
113
F. Y. Khalili,
50
I. Khan,
14
S. Khan,
95
Z. Khan,
90
E. A. Khazanov,
114
N. Kijbunchoo,
38
Chunglee Kim,
115
J. C. Kim,
116
Whansun Kim,
117
W. Kim,
71
Y.-M. Kim,
118
,
115
S. J. Kimbrell,
45
E. J. King,
71
P. J. King,
38
R. Kirchhoff,
10
J. S. Kissel,
38
B. Klein,
86
L. Kleybolte,
27
S. Klimenko,
6
P. Koch,
10
S. M. Koehlenbeck,
10
S. Koley,
11
V. Kondrashov,
1
A. Kontos,
12
M. Korobko,
27
W. Z. Korth,
1
I. Kowalska,
63
D. B. Kozak,
1
C. Kr ̈amer,
10
V. Kringel,
10
B. Krishnan,
10
A. Kr ́olak,
119
,
120
G. Kuehn,
10
P. Kumar,
98
R. Kumar,
90
L. Kuo,
76
A. Kutynia,
119
B. D. Lackey,
29
,
36
M. Landry,
38
R. N. Lang,
18
J. Lange,
108
B. Lantz,
41
R. K. Lanza,
12
A. Lartaux-Vollard,
24
P. D. Lasky,
121
M. Laxen,
7
A. Lazzarini,
1
C. Lazzaro,
43
P. Leaci,
82
,
28
S. Leavey,
37
E. O. Lebigot,
30
C. H. Lee,
118
H. K. Lee,
122
H. M. Lee,
115
K. Lee,
37
J. Lehmann,
10
A. Lenon,
31
,
32
M. Leonardi,
93
,
94
J. R. Leong,
10
N. Leroy,
24
N. Letendre,
8
Y. Levin,
121
T. G. F. Li,
123
A. Libson,
12
T. B. Littenberg,
124
J. Liu,
53
N. A. Lockerbie,
111
A. L. Lombardi,
45
L. T. London,
95
J. E. Lord,
36
M. Lorenzini,
14
,
15
V. Loriette,
125
M. Lormand,
7
G. Losurdo,
21
J. D. Lough,
10
,
19
G. Lovelace,
23
H. L ̈uck,
19
,
10
A. P. Lundgren,
10
R. Lynch,
12
Y. Ma,
52
S. Macfoy,
51
B. Machenschalk,
10
M. MacInnis,
12
D. M. Macleod,
2
F. Maga ̃na-Sandoval,
36
E. Majorana,
28
I. Maksimovic,
125
V. Malvezzi,
26
,
15
N. Man,
55
V. Mandic,
126
V. Mangano,
37
G. L. Mansell,
22
M. Manske,
18
M. Mantovani,
35
F. Marchesoni,
127
,
34
F. Marion,
8
S. M ́arka,
40
Z. M ́arka,
40
A. S. Markosyan,
41
E. Maros,
1
F. Martelli,
58
,
59
L. Martellini,
55
I. W. Martin,
37
D. V. Martynov,
12
K. Mason,
12
A. Masserot,
8
T. J. Massinger,
1
M. Masso-Reid,
37
S. Mastrogiovanni,
82
,
28
F. Matichard,
12
,
1
L. Matone,
40
N. Mavalvala,
12
N. Mazumder,
57
R. McCarthy,
38
D. E. McClelland,
22
S. McCormick,
7
C. McGrath,
18
S. C. McGuire,
128
G. McIntyre,
1
J. McIver,
1
D. J. McManus,
22
T. McRae,
22
S. T. McWilliams,
31
,
32
D. Meacher,
55
,
75
G. D. Meadors,
29
,
10
J. Meidam,
11
A. Melatos,
129
G. Mendell,
38
D. Mendoza-Gandara,
10
R. A. Mercer,
18
E. L. Merilh,
38
M. Merzougui,
55
S. Meshkov,
1
C. Messenger,
37
C. Messick,
75
R. Metzdorff,
61
P. M. Meyers,
126
F. Mezzani,
28
,
82
H. Miao,
46
C. Michel,
66
H. Middleton,
46
E. E. Mikhailov,
130
L. Milano,
68
,
5
A. L. Miller,
6
,
82
,
28
A. Miller,
86
B. B. Miller,
86
J. Miller,
12
M. Millhouse,
85
Y. Minenkov,
15
J. Ming,
29
S. Mirshekari,
131
C. Mishra,
17
S. Mitra,
16
V. P. Mitrofanov,
50
G. Mitselmakher,
6
R. Mittleman,
12
A. Moggi,
21
M. Mohan,
35
S. R. P. Mohapatra,
12
M. Montani,
58
,
59
B. C. Moore,
96
C. J. Moore,
81
D. Moraru,
38
G. Moreno,
38
S. R. Morriss,
88
B. Mours,
8
C. M. Mow-Lowry,
46
G. Mueller,
6
A. W. Muir,
95
Arunava Mukherjee,
17
D. Mukherjee,
18
S. Mukherjee,
88
N. Mukund,
16
A. Mullavey,
7
J. Munch,
71
E. A. M. Muniz,
23
P. G. Murray,
37
A. Mytidis,
6
K. Napier,
45
I. Nardecchia,
26
,
15
L. Naticchioni,
82
,
28
G. Nelemans,
54
,
11
T. J. N. Nelson,
7
M. Neri,
47
,
48
M. Nery,
10
A. Neunzert,
107
J. M. Newport,
3
G. Newton,
37
T. T. Nguyen,
22
A. B. Nielsen,
10
S. Nissanke,
54
,
11
A. Nitz,
10
A. Noack,
10
F. Nocera,
35
D. Nolting,
7
M. E. N. Normandin,
88
L. K. Nuttall,
36
J. Oberling,
38
E. Ochsner,
18
E. Oelker,
12
G. H. Ogin,
132
J. J. Oh,
117
S. H. Oh,
117
F. Ohme,
95
,
10
M. Oliver,
87
P. Oppermann,
10
Richard J. Oram,
7
B. O’Reilly,
7
R. O’Shaughnessy,
108
D. J. Ottaway,
71
H. Overmier,
7
B. J. Owen,
73
A. E. Pace,
75
J. Page,
124
A. Pai,
102
S. A. Pai,
49
J. R. Palamos,
60
O. Palashov,
114
C. Palomba,
28
A. Pal-Singh,
27
H. Pan,
76
C. Pankow,
86
F. Pannarale,
95
B. C. Pant,
49
F. Paoletti,
35
,
21
A. Paoli,
35
M. A. Papa,
29
,
18
,
10
H. R. Paris,
41
W. Parker,
7
D. Pascucci,
37
A. Pasqualetti,
35
R. Passaquieti,
20
,
21
D. Passuello,
21
B. Patricelli,
20
,
21
B. L. Pearlstone,
37
M. Pedraza,
1
R. Pedurand,
66
,
133
L. Pekowsky,
36
A. Pele,
7
S. Penn,
134
C. J. Perez,
38
A. Perreca,
1
L. M. Perri,
86
H. P. Pfeiffer,
98
M. Phelps,
37
O. J. Piccinni,
82
,
28
M. Pichot,
55
F. Piergiovanni,
58
,
59
V. Pierro,
9
G. Pillant,
35
L. Pinard,
66
I. M. Pinto,
9
M. Pitkin,
37
M. Poe,
18
R. Poggiani,
20
,
21
P. Popolizio,
35
A. Post,
10
J. Powell,
37
J. Prasad,
16
J. W. W. Pratt,
104
V. Predoi,
95
T. Prestegard,
126
,
18
M. Prijatelj,
10
,
35
M. Principe,
9
S. Privitera,
29
R. Prix,
10
G. A. Prodi,
93
,
94
L. G. Prokhorov,
50
O. Puncken,
10
M. Punturo,
34
P. Puppo,
28
M. P ̈urrer,
29
H. Qi,
18
J. Qin,
53
S. Qiu,
121
V. Quetschke,
88
E. A. Quintero,
1
R. Quitzow-James,
60
F. J. Raab,
38
D. S. Rabeling,
22
H. Radkins,
38
P. Raffai,
99
S. Raja,
49
C. Rajan,
49
M. Rakhmanov,
88
P. Rapagnani,
82
,
28
V. Raymond,
29
M. Razzano,
20
,
21
V. Re,
26
J. Read,
23
T. Regimbau,
55
L. Rei,
48
S. Reid,
51
D. H. Reitze,
1
,
6
H. Rew,
130
S. D. Reyes,
36
E. Rhoades,
104
F. Ricci,
82
,
28
K. Riles,
107
3
M. Rizzo,
108
N. A. Robertson,
1
,
37
R. Robie,
37
F. Robinet,
24
A. Rocchi,
15
L. Rolland,
8
J. G. Rollins,
1
V. J. Roma,
60
J. D. Romano,
88
R. Romano,
4
,
5
J. H. Romie,
7
D. Rosi ́nska,
135
,
44
S. Rowan,
37
A. R ̈udiger,
10
P. Ruggi,
35
K. Ryan,
38
S. Sachdev,
1
T. Sadecki,
38
L. Sadeghian,
18
M. Sakellariadou,
136
L. Salconi,
35
M. Saleem,
102
F. Salemi,
10
A. Samajdar,
137
L. Sammut,
121
L. M. Sampson,
86
E. J. Sanchez,
1
V. Sandberg,
38
J. R. Sanders,
36
B. Sassolas,
66
B. S. Sathyaprakash,
75
,
95
P. R. Saulson,
36
O. Sauter,
107
R. L. Savage,
38
A. Sawadsky,
19
P. Schale,
60
J. Scheuer,
86
E. Schmidt,
104
J. Schmidt,
10
P. Schmidt,
1
,
52
R. Schnabel,
27
R. M. S. Schofield,
60
A. Sch ̈onbeck,
27
E. Schreiber,
10
D. Schuette,
10
,
19
B. F. Schutz,
95
,
29
S. G. Schwalbe,
104
J. Scott,
37
S. M. Scott,
22
D. Sellers,
7
A. S. Sengupta,
138
D. Sentenac,
35
V. Sequino,
26
,
15
A. Sergeev,
114
Y. Setyawati,
54
,
11
D. A. Shaddock,
22
T. J. Shaffer,
38
M. S. Shahriar,
86
B. Shapiro,
41
P. Shawhan,
65
A. Sheperd,
18
D. H. Shoemaker,
12
D. M. Shoemaker,
45
K. Siellez,
45
X. Siemens,
18
M. Sieniawska,
44
D. Sigg,
38
A. D. Silva,
13
A. Singer,
1
L. P. Singer,
69
A. Singh,
29
,
10
,
19
R. Singh,
2
A. Singhal,
14
A. M. Sintes,
87
B. J. J. Slagmolen,
22
B. Smith,
7
J. R. Smith,
23
R. J. E. Smith,
1
E. J. Son,
117
B. Sorazu,
37
F. Sorrentino,
48
T. Souradeep,
16
A. P. Spencer,
37
A. K. Srivastava,
90
A. Staley,
40
M. Steinke,
10
J. Steinlechner,
37
S. Steinlechner,
27
,
37
D. Steinmeyer,
10
,
19
B. C. Stephens,
18
S. P. Stevenson,
46
R. Stone,
88
K. A. Strain,
37
N. Straniero,
66
G. Stratta,
58
,
59
S. E. Strigin,
50
R. Sturani,
131
A. L. Stuver,
7
T. Z. Summerscales,
139
L. Sun,
129
S. Sunil,
90
P. J. Sutton,
95
B. L. Swinkels,
35
M. J. Szczepa ́nczyk,
104
M. Tacca,
30
D. Talukder,
60
D. B. Tanner,
6
M. T ́apai,
103
A. Taracchini,
29
R. Taylor,
1
T. Theeg,
10
E. G. Thomas,
46
M. Thomas,
7
P. Thomas,
38
K. A. Thorne,
7
E. Thrane,
121
T. Tippens,
45
S. Tiwari,
14
,
94
V. Tiwari,
95
K. V. Tokmakov,
111
K. Toland,
37
C. Tomlinson,
91
M. Tonelli,
20
,
21
Z. Tornasi,
37
C. I. Torrie,
1
D. T ̈oyr ̈a,
46
F. Travasso,
33
,
34
G. Traylor,
7
D. Trifir`o,
74
J. Trinastic,
6
M. C. Tringali,
93
,
94
L. Trozzo,
140
,
21
M. Tse,
12
R. Tso,
1
M. Turconi,
55
D. Tuyenbayev,
88
D. Ugolini,
141
C. S. Unnikrishnan,
105
A. L. Urban,
1
S. A. Usman,
95
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19
G. Vajente,
1
G. Valdes,
88
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11
M. van Beuzekom,
11
J. F. J. van den Brand,
64
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11
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11
D. C. Vander-Hyde,
36
L. van der Schaaf,
11
J. V. van Heijningen,
11
A. A. van Veggel,
37
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42
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1
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39
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46
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43
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71
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142
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1
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8
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58
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58
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18
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55
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12
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36
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6
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1
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1
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22
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38
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8
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83
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X. J. Zhu,
53
M. E. Zucker,
1
,
12
and J. Zweizig
1
(LIGO Scientific Collaboration and Virgo Collaboration)
†
Deceased, March 2016.
∗
(Dated: 21st November 2017)
We present the results of a search for long-duration gravita
tional wave transients in the data of
the LIGO Hanford and LIGO Livingston second generation dete
ctors between
September 2015
and
January 2016
, with a total observational time of
49 days
. The search targets gravitational wave
transients of 10 – 500 s duration in a frequency band of 24 – 204
8 Hz, with minimal assumptions
about the signal waveform, polarization, source direction
, or time of occurrence. No significant
events were observed. As a result we set 90% confidence upper l
imits on the rate of long-duration
gravitational wave transients for different types of gravit
ational wave signals. We also show that the
search is sensitive to sources in the Galaxy emitting at leas
t
∼
10
−
8
M
⊙
c
2
in gravitational waves.
I. INTRODUCTION
The first observing runs of the Advanced LIGO and
Advanced Virgo detectors, with significant sensitivity im-
provements compared to the first generation detectors,
∗
lvc.publications@ligo.org
yielded in less than two years incredible discoveries and
major astrophysics results via gravitational wave (GW)
detections. The first observed GW signals corresponded
to the final moments of the coalescence of two stellar-
mass black holes and their final plunge. GW150914 and
GW151226 were observed with high confidence (
>
5
σ
),
while LVT151012 was identified with a lower signific-
ance (1
.
7
σ
) [1–5] during the first observing run (O1).
During the second observing run (O2), GW170104 and
4
GW170814 (which was detected simultaneously by the
three LIGO and Virgo detectors) have confirmed the es-
timated rate of stellar-mass black hole mergers [6, 7].
Lastly, the observation of a binary neutron star inspiral
by the LIGO and Virgo network [8] in association with a
gamma-ray burst [9] and a multitude of broadband elec-
tromagnetic counterpart observations [10] has opened up
a new era in multimessenger astronomy.
The searches that observed these binary compact ob-
ject systems were also targetting neutron star – black hole
mergers [11, 12] as well as intermediate-mass black hole
mergers of total mass up to 600 M
⊙
[13]. So far, only
O1 observing run results have been reported for these
sources, and no other compact binary coalescence, nor
any short duration signal targeted by unmodeled short
duration searches [12] have been observed.
In this paper, we present an all-sky search for un-
modeled long-duration (10–500s) transient GW events.
Astrophysical compact sources undergoing complex dy-
namics and hydrodynamic instabilities are expected to
emit long-lasting GWs. For example, fallback accre-
tion onto a newborn neutron star can lead to a non-
axisymmetric deformation which emits GWs until the
neutron star collapses to a black hole [14–17]. Non-
axisymmetric accretion disc fragmentation and instabil-
ities can lead to material spiraling into the central stellar-
mass black hole, emitting GWs [18–20]. Long-duration
GWs may also be emitted by non-axisymmetric deforma-
tions in magnetars [21, 22], which are possible progenitors
of long and short GRBs [23, 24]. Finally, core-collapse su-
pernovae simulations have shown that the turbulent and
chaotic fluid movements that occur in the proto-neutron
star formed a few hundred milliseconds after the core
collapse can excite long-lasting surface g-modes whose
frequency drifts over time [25, 26].
We extend the search for long-duration GW transi-
ents previously carried out on initial LIGO data from the
period 2005–2010 [27]. Four pipelines have been used to
double the frequency band coverage from (40–1000Hz)
to (24–2048Hz), and new waveform models have been
used to estimate the pipelines’ sensitivities. We expli-
citly demonstrate that the search is capable of efficiently
detecting three of the four potential sources mentioned
above. No significant events were detected and con-
sequently, upper limits have been set on the rate of long-
duration transient signals.
The organization of the paper is as follows. In Sec-
tion II, we describe the dataset. Section III is devoted
to a brief description of the pipelines, whose sensitivities
are presented in Section IV. In Section V, we give and
discuss the results, then we conclude in Section VI with
a discussion of future expectations.
II. DATA SET & DATA QUALITY
This O1 analysis uses data from
September 12, 2015
to
January 19, 2016
. The LIGO detectors in Hanford, WA
and Livingston, LA ran with
40%
coincident time. For
this long-duration transient search, about two days of co-
incident data have been discarded because they were af-
fected by major detector failures or problematic weather
conditions. The remaining
49 days
of coincident data
still contain many non-stationary short duration noise
events that can mimic a signal. These noise events, or
“glitches”, have a multitude of causes. For instance, low
frequency glitches are caused by surges in power lines
or seismic events, while many high frequency glitches
are caused by resonances in the test mass suspension
wires [28]. Many of these effects can be tracked in auxil-
iary sensors that we use to define the severity of the loss
of data quality [28–30].
The signals targeted by the long-duration transients
search have their energy spread over a large time span.
Consequently, even modest excesses of noise directly in-
fluence the signal reconstruction. In order to be con-
sidered as a potential real signal, events must be seen
coincidently in the two LIGO detectors. This require-
ment eliminates most of the noise events due to glitches.
An accurate background estimation using the data them-
selves is therefore necessary to measure the significance
of any coincident excess of energy. A false alarm rate
(FAR) is estimated after safe veto methods are applied
to get rid of as many glitch events as possible. While a
few families of these noise events can be suppressed by
vetoes based on auxiliary channels, each search pipeline
has its own background reduction strategy and its own
implementation of the time-slides method [31] to estim-
ate the FAR. It consists in introducing a time-shift in one
detector’s strain time series. Details on these topics are
provided in the next section.
III. PIPELINES
Four pipelines are used to analyze the data set and
search for long-duration GW transient signals. These
pipelines are described in the sub-sections that follow.
A. Coherent WaveBurst
Coherent WaveBurst (cWB) is a pipeline designed to
search for generic GW transients. Using a maximum-
likelihood-ratio statistic [32], it identifies coincident ex-
cess power events (triggers) in a time-frequency space.
The long-duration transient cWB search is implemented
with the same pipeline also used to search for short tran-
sient events [12] with a few specific changes: It operates
in the frequency range 24–2048Hz and only data which
pass the strictest data quality criteria are examined (see
Section II and [12]). Events are ranked according to
their detection statistic (
η
c
), which is related to the
event signal-to-noise ratio (SNR). A primary selection
is based on the network correlation coefficient
C
c
[32],
which measures the degree of correlation between the
5
detectors, and the energy-weighted duration of detected
triggers. Events with
C
c
<
0
.
6 or duration
<
1
.
5 s are
excluded from the analysis. The selection criterion based
on duration is specific to this long-duration search and it
is the most powerful selection criteria to suppress back-
ground triggers. To characterize the FAR, the data of
one interferometer is shifted in time (the so called time-
slides method) with respect to the other interferometer
by multiple delays of 1 s for an equivalent total time of
∼
70 years of coincident time.
B. The STAMP-AS pipeline
The all-sky STAMP-AS pipeline based on
the Stochastic Transient Analysis Multi-detector
Pipeline [27] cross-correlates data from two detectors
and builds coherent time-frequency maps (
tf
-maps) of
SNR with a pixel size of 1s
×
1Hz. The SNR is computed
for each second of data by estimating the mean noise
over the neighboring seconds on each side. Pixels in
frequency bins corresponding to known instrumental
lines are suppressed. Once the
tf
-maps are built,
overlapping clusters that pass a SNR threshold of 0.75
are grouped to form triggers. There are two variants
of STAMP-AS that differ in cluster grouping strategy:
Zebragard and Lonetrack.
1. Zebragard
Working with
tf
-maps of size 24-2000Hz
×
500 s,
Zebragard groups together pixels above a given SNR
threshold that lie within a 4 pixel distance from each
other. Because a sub-optimal number of sky positions are
targeted, a signal can be anti-coherent (negative SNR).
The algorithm addresses this in such a way that the loss
of efficiency due to the limited number of tested sky pos-
itions is less than 10% [33]. The trigger ranking statistic,
Θ
Γ
, is defined as the quadratic sum of the SNR of the
individual pixels. This analysis uses the same configura-
tion and the same background rejection strategy against
short-duration noise transient “glitches” (the fraction of
SNR in each time bin must be smaller than 0.5) as in [27].
In addition, the O1 data set contains an excess of back-
ground triggers that required developing additional ve-
toes. For example, using the fact that the two LIGO de-
tectors are almost aligned, triggers due to a loud glitch
in one detector are suppressed by demanding that the
SNR ratio between the two detectors is smaller than 3.
Mechanical resonances excited when the optical cavities
of the interferometer arms are locked generate an excess
of triggers at 39 Hz and 43 Hz at well identified times.
Finally, the remaining glitches are efficiently suppressed
by data quality vetoes based on auxiliary channels [34].
It has been verified that these vetoes minimally affect the
search for the targeted signals (less than 5% of simulated
signals are lost). The background is estimated by time-
shifting the data of one detector relative to the other
in steps of 250 s. Data quality investigations and veto
tuning are performed using a subset of the time-shifted
triggers. The background rate is estimated with 600 time
shift values between the detectors for an equivalent total
time of
∼
78 years of coincident time for the O1 data set.
2. Lonetrack
Lonetrack uses seedless clustering to integrate the
signal power along spectrogram tracks using templates
chosen to capture the salient features of a wide class of
signal models. Templates here are not meant to exactly
match the signal but rather to identify a few isolated
pixels that are part of the signals. B ́ezier curves [35–39],
a post-Newtonian expansion for time-frequency track of
circular compact binary coalescence signals [40], and an
analytic expression for low-to-moderate eccentric com-
pact binaries [41] have all been used previously as seed-
less clustering parametrizations. These parameteriza-
tions are used to create template banks of frequency-time
tracks. In this present search, B ́ezier curves were used in
order to be sensitive to as many signal models as possible.
The Lonetrack search hierarchically selects the most
promising triggers. This allows us to estimate the events’
significance at very low FAR (to reach the equivalent of
5
σ
detection probability). It begins by applying seedless
clustering to analyze spectrograms of a single-detector,
incoherent statistic [39]. For times that pass a threshold
on SNR of 6,
tf
-maps of cross-power SNR are construc-
ted using the tracks derived from the single detector, in-
coherent statistic. This analysis is carried out for 400
evenly spaced values of 0.05 ms time delay between the
detectors. The FAR is estimated with an equivalent total
time of
∼
12,000 years. The detection statistic to rank
triggers is the maximum SNR found per map.
C. X-SphRad
The X-pipeline Spherical Radiometer (X-SphRad) is
a fast cross-correlator in the spherical harmonic do-
main [42]. The spherical radiometry approach takes ad-
vantage of the fact that sky maps in GW searches show
strong correlations over large angular scales in a pattern
determined by the network geometry [43]. Computing
sky maps indirectly through their spherical harmonics
minimizes the number of redundant calculations, allow-
ing the data to be processed independently of sky posi-
tion. The pipeline is built on X-pipeline [44, 45] which
whitens the data in the pre-processing step and then
post-processes the event triggers output using the spher-
ical radiometer. The pipeline uses the ratio of the power
in the homogeneous polynomials of degree
l >
0 modes
to that in the
l
= 0 mode to rank triggers. This rank-
ing statistic provides a discriminatory power for rejecting
background glitches [46]. To estimate the background,