of 15
Search for continuous gravitational waves from neutron stars in globular cluster
NGC 6544
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
,
18
,
19
A. Allocca,
20
,
21
P. A. Altin,
22
S. B. Anderson,
1
W. G. Anderson,
18
K. Arai,
1
M. C. Araya,
1
C. C. Arceneaux,
23
J. S. Areeda,
24
N. Arnaud,
25
K. G. Arun,
26
S. Ascenzi,
27
,
15
G. Ashton,
28
M. Ast,
29
S. M. Aston,
7
P. Astone,
30
P. Aufmuth,
19
C. Aulbert,
10
S. Babak,
31
P. Bacon,
32
M. K. M. Bader,
11
P. T. Baker,
33
F. Baldaccini,
34
,
35
G. Ballardin,
36
S. W. Ballmer,
37
J. C. Barayoga,
1
S. E. Barclay,
38
B. C. Barish,
1
D. Barker,
39
F. Barone,
4
,
5
B. Barr,
38
L. Barsotti,
12
M. Barsuglia,
32
D. Barta,
40
J. Bartlett,
39
I. Bartos,
41
R. Bassiri,
42
A. Basti,
20
,
21
J. C. Batch,
39
C. Baune,
10
V. Bavigadda,
36
M. Bazzan,
43
,
44
M. Bejger,
45
A. S. Bell,
38
B. K. Berger,
1
G. Bergmann,
10
C. P. L. Berry,
46
D. Bersanetti,
47
,
48
A. Bertolini,
11
J. Betzwieser,
7
S. Bhagwat,
37
R. Bhandare,
49
I. A. Bilenko,
50
G. Billingsley,
1
J. Birch,
7
R. Birney,
51
S. Biscans,
12
A. Bisht,
10
,
19
M. Bitossi,
36
C. Biwer,
37
M. A. Bizouard,
25
J. K. Blackburn,
1
C. D. Blair,
52
D. G. Blair,
52
R. M. Blair,
39
S. Bloemen,
53
O. Bock,
10
M. Boer,
54
G. Bogaert,
54
C. Bogan,
10
A. Bohe,
31
C. Bond,
46
F. Bondu,
55
R. Bonnand,
8
B. A. Boom,
11
R. Bork,
1
V. Boschi,
20
,
21
S. Bose,
56
,
16
Y. Bouffanais,
32
A. Bozzi,
36
C. Bradaschia,
21
P. R. Brady,
18
V. B. Braginsky
,
50
M. Branchesi,
57
,
58
J. E. Brau,
59
T. Briant,
60
A. Brillet,
54
M. Brinkmann,
10
V. Brisson,
25
P. Brockill,
18
J. E. Broida,
61
A. F. Brooks,
1
D. A. Brown,
37
D. D. Brown,
46
N. M. Brown,
12
S. Brunett,
1
C. C. Buchanan,
2
A. Buikema,
12
T. Bulik,
62
H. J. Bulten,
63
,
11
A. Buonanno,
31
,
64
D. Buskulic,
8
C. Buy,
32
R. L. Byer,
42
M. Cabero,
10
L. Cadonati,
65
G. Cagnoli,
66
,
67
C. Cahillane,
1
J. Calder ́on Bustillo,
65
T. Callister,
1
E. Calloni,
68
,
5
J. B. Camp,
69
K. C. Cannon,
70
J. Cao,
71
C. D. Capano,
10
E. Capocasa,
32
F. Carbognani,
36
S. Caride,
72
J. Casanueva Diaz,
25
C. Casentini,
27
,
15
S. Caudill,
18
M. Cavagli`a,
23
F. Cavalier,
25
R. Cavalieri,
36
G. Cella,
21
C. B. Cepeda,
1
L. Cerboni Baiardi,
57
,
58
G. Cerretani,
20
,
21
E. Cesarini,
27
,
15
S. J. Chamberlin,
73
M. Chan,
38
S. Chao,
74
P. Charlton,
75
E. Chassande-Mottin,
32
B. D. Cheeseboro,
76
H. Y. Chen,
77
Y. Chen,
78
C. Cheng,
74
A. Chincarini,
48
A. Chiummo,
36
H. S. Cho,
79
M. Cho,
64
J. H. Chow,
22
N. Christensen,
61
Q. Chu,
52
S. Chua,
60
S. Chung,
52
G. Ciani,
6
F. Clara,
39
J. A. Clark,
65
F. Cleva,
54
E. Coccia,
27
,
14
P.-F. Cohadon,
60
A. Colla,
80
,
30
C. G. Collette,
81
L. Cominsky,
82
M. Constancio Jr.,
13
A. Conte,
80
,
30
L. Conti,
44
D. Cook,
39
T. R. Corbitt,
2
N. Cornish,
33
A. Corsi,
72
S. Cortese,
36
C. A. Costa,
13
M. W. Coughlin,
61
S. B. Coughlin,
83
J.-P. Coulon,
54
S. T. Countryman,
41
P. Couvares,
1
E. E. Cowan,
65
D. M. Coward,
52
M. J. Cowart,
7
D. C. Coyne,
1
R. Coyne,
72
K. Craig,
38
J. D. E. Creighton,
18
T. Creighton,
88
J. Cripe,
2
S. G. Crowder,
84
A. Cumming,
38
L. Cunningham,
38
E. Cuoco,
36
T. Dal Canton,
10
S. L. Danilishin,
38
S. D’Antonio,
15
K. Danzmann,
19
,
10
N. S. Darman,
85
A. Dasgupta,
86
C. F. Da Silva Costa,
6
V. Dattilo,
36
I. Dave,
49
M. Davier,
25
G. S. Davies,
38
E. J. Daw,
87
R. Day,
36
S. De,
37
D. DeBra,
42
G. Debreczeni,
40
J. Degallaix,
66
M. De Laurentis,
68
,
5
S. Del ́eglise,
60
W. Del Pozzo,
46
T. Denker,
10
T. Dent,
10
V. Dergachev,
1
R. De Rosa,
68
,
5
R. T. DeRosa,
7
R. DeSalvo,
9
R. C. Devine,
76
S. Dhurandhar,
16
M. C. D ́ıaz,
88
L. Di Fiore,
5
M. Di Giovanni,
89
,
90
T. Di Girolamo,
68
,
5
A. Di Lieto,
20
,
21
S. Di Pace,
80
,
30
I. Di Palma,
31
,
80
,
30
A. Di Virgilio,
21
V. Dolique,
66
F. Donovan,
12
K. L. Dooley,
23
S. Doravari,
10
R. Douglas,
38
T. P. Downes,
18
M. Drago,
10
R. W. P. Drever,
1
J. C. Driggers,
39
M. Ducrot,
8
S. E. Dwyer,
39
T. B. Edo,
87
M. C. Edwards,
61
A. Effler,
7
H.-B. Eggenstein,
10
P. Ehrens,
1
J. Eichholz,
6
,
1
S. S. Eikenberry,
6
W. Engels,
78
R. C. Essick,
12
T. Etzel,
1
M. Evans,
12
T. M. Evans,
7
R. Everett,
73
M. Factourovich,
41
V. Fafone,
27
,
15
H. Fair,
37
X. Fan,
71
Q. Fang,
52
S. Farinon,
48
B. Farr,
77
W. M. Farr,
46
M. Favata,
92
M. Fays,
91
H. Fehrmann,
10
M. M. Fejer,
42
E. Fenyvesi,
93
I. Ferrante,
20
,
21
E. C. Ferreira,
13
F. Ferrini,
36
F. Fidecaro,
20
,
21
I. Fiori,
36
D. Fiorucci,
32
R. P. Fisher,
37
R. Flaminio,
66
,
94
M. Fletcher,
38
J.-D. Fournier,
54
S. Frasca,
80
,
30
F. Frasconi,
21
Z. Frei,
93
A. Freise,
46
R. Frey,
59
V. Frey,
25
P. Fritschel,
12
V. V. Frolov,
7
P. Fulda,
6
M. Fyffe,
7
H. A. G. Gabbard,
23
J. R. Gair,
95
L. Gammaitoni,
34
S. G. Gaonkar,
16
F. Garufi,
68
,
5
G. Gaur,
96
,
86
N. Gehrels,
69
G. Gemme,
48
P. Geng,
88
E. Genin,
36
A. Gennai,
21
J. George,
49
L. Gergely,
97
V. Germain,
8
Abhirup Ghosh,
17
Archisman Ghosh,
17
S. Ghosh,
53
,
11
J. A. Giaime,
2
,
7
K. D. Giardina,
7
A. Giazotto,
21
K. Gill,
98
A. Glaefke,
38
E. Goetz,
39
R. Goetz,
6
L. Gondan,
93
G. Gonz ́alez,
2
J. M. Gonzalez Castro,
20
,
21
A. Gopakumar,
99
N. A. Gordon,
38
M. L. Gorodetsky,
50
S. E. Gossan,
1
M. Gosselin,
36
R. Gouaty,
8
A. Grado,
100
,
5
C. Graef,
38
P. B. Graff,
64
M. Granata,
66
A. Grant,
38
S. Gras,
12
C. Gray,
39
G. Greco,
57
,
58
A. C. Green,
46
P. Groot,
53
H. Grote,
10
S. Grunewald,
31
G. M. Guidi,
57
,
58
X. Guo,
71
A. Gupta,
16
M. K. Gupta,
86
K. E. Gushwa,
1
E. K. Gustafson,
1
R. Gustafson,
101
J. J. Hacker,
24
B. R. Hall,
56
E. D. Hall,
1
G. Hammond,
38
M. Haney,
99
M. M. Hanke,
10
J. Hanks,
39
C. Hanna,
73
J. Hanson,
7
T. Hardwick,
2
J. Harms,
57
,
58
G. M. Harry,
3
I. W. Harry,
31
M. J. Hart,
38
M. T. Hartman,
6
C.-J. Haster,
46
K. Haughian,
38
arXiv:1607.02216v1 [gr-qc] 8 Jul 2016
2
A. Heidmann,
60
M. C. Heintze,
7
H. Heitmann,
54
P. Hello,
25
G. Hemming,
36
M. Hendry,
38
I. S. Heng,
38
J. Hennig,
38
J. Henry,
102
A. W. Heptonstall,
1
M. Heurs,
10
,
19
S. Hild,
38
D. Hoak,
36
D. Hofman,
66
K. Holt,
7
D. E. Holz,
77
P. Hopkins,
91
J. Hough,
38
E. A. Houston,
38
E. J. Howell,
52
Y. M. Hu,
10
S. Huang,
74
E. A. Huerta,
103
D. Huet,
25
B. Hughey,
98
S. Husa,
104
S. H. Huttner,
38
T. Huynh-Dinh,
7
N. Indik,
10
D. R. Ingram,
39
R. Inta,
72
H. N. Isa,
38
J.-M. Isac,
60
M. Isi,
1
T. Isogai,
12
B. R. Iyer,
17
K. Izumi,
39
T. Jacqmin,
60
H. Jang,
79
K. Jani,
65
P. Jaranowski,
105
S. Jawahar,
106
L. Jian,
52
F. Jim ́enez-Forteza,
104
W. W. Johnson,
2
D. I. Jones,
28
R. Jones,
38
R. J. G. Jonker,
11
L. Ju,
52
Haris K,
107
C. V. Kalaghatgi,
91
V. Kalogera,
83
S. Kandhasamy,
23
G. Kang,
79
J. B. Kanner,
1
S. J. Kapadia,
10
S. Karki,
59
K. S. Karvinen,
10
M. Kasprzack,
36
,
2
E. Katsavounidis,
12
W. Katzman,
7
S. Kaufer,
19
T. Kaur,
52
K. Kawabe,
39
F. K ́ef ́elian,
54
M. S. Kehl,
108
D. Keitel,
104
D. B. Kelley,
37
W. Kells,
1
R. Kennedy,
87
J. S. Key,
88
F. Y. Khalili,
50
I. Khan,
14
S. Khan,
91
Z. Khan,
86
E. A. Khazanov,
109
N. Kijbunchoo,
39
Chi-Woong Kim,
79
Chunglee Kim,
79
J. Kim,
110
K. Kim,
111
N. Kim,
42
W. Kim,
112
Y.-M. Kim,
110
S. J. Kimbrell,
65
E. J. King,
112
P. J. King,
39
J. S. Kissel,
39
B. Klein,
83
L. Kleybolte,
29
S. Klimenko,
6
S. M. Koehlenbeck,
10
S. Koley,
11
V. Kondrashov,
1
A. Kontos,
12
M. Korobko,
29
W. Z. Korth,
1
I. Kowalska,
62
D. B. Kozak,
1
V. Kringel,
10
B. Krishnan,
10
A. Kr ́olak,
113
,
114
C. Krueger,
19
G. Kuehn,
10
P. Kumar,
108
R. Kumar,
86
L. Kuo,
74
A. Kutynia,
113
B. D. Lackey,
37
M. Landry,
39
J. Lange,
102
B. Lantz,
42
P. D. Lasky,
115
M. Laxen,
7
C. Lazzaro,
44
P. Leaci,
80
,
30
S. Leavey,
38
E. O. Lebigot,
32
,
71
C. H. Lee,
110
H. K. Lee,
111
H. M. Lee,
116
K. Lee,
38
A. Lenon,
37
M. Leonardi,
89
,
90
J. R. Leong,
10
N. Leroy,
25
N. Letendre,
8
Y. Levin,
115
J. B. Lewis,
1
T. G. F. Li,
117
A. Libson,
12
T. B. Littenberg,
118
N. A. Lockerbie,
106
A. L. Lombardi,
119
L. T. London,
91
J. E. Lord,
37
M. Lorenzini,
14
,
15
V. Loriette,
120
M. Lormand,
7
G. Losurdo,
58
J. D. Lough,
10
,
19
H. L ̈uck,
19
,
10
A. P. Lundgren,
10
R. Lynch,
12
Y. Ma,
52
B. Machenschalk,
10
M. MacInnis,
12
D. M. Macleod,
2
F. Maga ̃na-Sandoval,
37
L. Maga ̃na Zertuche,
37
R. M. Magee,
56
E. Majorana,
30
I. Maksimovic,
120
V. Malvezzi,
27
,
15
N. Man,
54
V. Mandic,
84
V. Mangano,
38
G. L. Mansell,
22
M. Manske,
18
M. Mantovani,
36
F. Marchesoni,
121
,
35
F. Marion,
8
S. M ́arka,
41
Z. M ́arka,
41
A. S. Markosyan,
42
E. Maros,
1
F. Martelli,
57
,
58
L. Martellini,
54
I. W. Martin,
38
D. V. Martynov,
12
J. N. Marx,
1
K. Mason,
12
A. Masserot,
8
T. J. Massinger,
37
M. Masso-Reid,
38
S. Mastrogiovanni,
80
,
30
F. Matichard,
12
L. Matone,
41
N. Mavalvala,
12
N. Mazumder,
56
R. McCarthy,
39
D. E. McClelland,
22
S. McCormick,
7
S. C. McGuire,
122
G. McIntyre,
1
J. McIver,
1
D. J. McManus,
22
T. McRae,
22
S. T. McWilliams,
76
D. Meacher,
73
G. D. Meadors,
31
,
10
J. Meidam,
11
A. Melatos,
85
G. Mendell,
39
R. A. Mercer,
18
E. L. Merilh,
39
M. Merzougui,
54
S. Meshkov,
1
C. Messenger,
38
C. Messick,
73
R. Metzdorff,
60
P. M. Meyers,
84
F. Mezzani,
30
,
80
H. Miao,
46
C. Michel,
66
H. Middleton,
46
E. E. Mikhailov,
123
L. Milano,
68
,
5
A. L. Miller,
6
,
80
,
30
A. Miller,
83
B. B. Miller,
83
J. Miller,
12
M. Millhouse,
33
Y. Minenkov,
15
J. Ming,
31
S. Mirshekari,
124
C. Mishra,
17
S. Mitra,
16
V. P. Mitrofanov,
50
G. Mitselmakher,
6
R. Mittleman,
12
A. Moggi,
21
M. Mohan,
36
S. R. P. Mohapatra,
12
M. Montani,
57
,
58
B. C. Moore,
92
C. J. Moore,
125
D. Moraru,
39
G. Moreno,
39
S. R. Morriss,
88
K. Mossavi,
10
B. Mours,
8
C. M. Mow-Lowry,
46
G. Mueller,
6
A. W. Muir,
91
Arunava Mukherjee,
17
D. Mukherjee,
18
S. Mukherjee,
88
N. Mukund,
16
A. Mullavey,
7
J. Munch,
112
D. J. Murphy,
41
P. G. Murray,
38
A. Mytidis,
6
I. Nardecchia,
27
,
15
L. Naticchioni,
80
,
30
R. K. Nayak,
126
K. Nedkova,
119
G. Nelemans,
53
,
11
T. J. N. Nelson,
7
M. Neri,
47
,
48
A. Neunzert,
101
G. Newton,
38
T. T. Nguyen,
22
A. B. Nielsen,
10
S. Nissanke,
53
,
11
A. Nitz,
10
F. Nocera,
36
D. Nolting,
7
M. E. N. Normandin,
88
L. K. Nuttall,
37
J. Oberling,
39
E. Ochsner,
18
J. O’Dell,
127
E. Oelker,
12
G. H. Ogin,
128
J. J. Oh,
129
S. H. Oh,
129
F. Ohme,
91
M. Oliver,
104
P. Oppermann,
10
Richard J. Oram,
7
B. O’Reilly,
7
R. O’Shaughnessy,
102
D. J. Ottaway,
112
H. Overmier,
7
B. J. Owen,
72
A. Pai,
107
S. A. Pai,
49
J. R. Palamos,
59
O. Palashov,
109
C. Palomba,
30
A. Pal-Singh,
29
H. Pan,
74
C. Pankow,
83
F. Pannarale,
91
B. C. Pant,
49
F. Paoletti,
36
,
21
A. Paoli,
36
M. A. Papa,
31
,
18
,
10
H. R. Paris,
42
W. Parker,
7
D. Pascucci,
38
A. Pasqualetti,
36
R. Passaquieti,
20
,
21
D. Passuello,
21
P. Patel,
1
B. Patricelli,
20
,
21
Z. Patrick,
42
B. L. Pearlstone,
38
M. Pedraza,
1
R. Pedurand,
66
,
130
L. Pekowsky,
37
A. Pele,
7
S. Penn,
131
A. Perreca,
1
L. M. Perri,
83
M. Phelps,
38
O. J. Piccinni,
80
,
30
M. Pichot,
54
F. Piergiovanni,
57
,
58
V. Pierro,
9
G. Pillant,
36
L. Pinard,
66
I. M. Pinto,
9
M. Pitkin,
38
M. Poe,
18
R. Poggiani,
20
,
21
P. Popolizio,
36
A. Post,
10
J. Powell,
38
J. Prasad,
16
V. Predoi,
91
T. Prestegard,
84
L. R. Price,
1
M. Prijatelj,
10
,
36
M. Principe,
9
S. Privitera,
31
R. Prix,
10
G. A. Prodi,
89
,
90
L. Prokhorov,
50
O. Puncken,
10
M. Punturo,
35
P. Puppo,
30
M. P ̈urrer,
31
H. Qi,
18
J. Qin,
52
S. Qiu,
115
V. Quetschke,
88
E. A. Quintero,
1
R. Quitzow-James,
59
F. J. Raab,
39
D. S. Rabeling,
22
H. Radkins,
39
P. Raffai,
93
S. Raja,
49
C. Rajan,
49
M. Rakhmanov,
88
P. Rapagnani,
80
,
30
V. Raymond,
31
M. Razzano,
20
,
21
V. Re,
27
J. Read,
24
C. M. Reed,
39
T. Regimbau,
54
L. Rei,
48
S. Reid,
51
D. H. Reitze,
1
,
6
H. Rew,
123
S. D. Reyes,
37
F. Ricci,
80
,
30
K. Riles,
101
M. Rizzo,
102
N. A. Robertson,
1
,
38
R. Robie,
38
F. Robinet,
25
A. Rocchi,
15
L. Rolland,
8
J. G. Rollins,
1
V. J. Roma,
59
R. Romano,
4
,
5
G. Romanov,
123
J. H. Romie,
7
D. Rosi ́nska,
132
,
45
S. Rowan,
38
A. R ̈udiger,
10
P. Ruggi,
36
K. Ryan,
39
S. Sachdev,
1
T. Sadecki,
39
L. Sadeghian,
18
M. Sakellariadou,
133
L. Salconi,
36
M. Saleem,
107
F. Salemi,
10
A. Samajdar,
126
L. Sammut,
115
E. J. Sanchez,
1
V. Sandberg,
39
B. Sandeen,
83
3
J. R. Sanders,
37
B. Sassolas,
66
P. R. Saulson,
37
O. E. S. Sauter,
101
R. L. Savage,
39
A. Sawadsky,
19
P. Schale,
59
R. Schilling
,
10
J. Schmidt,
10
P. Schmidt,
1
,
78
R. Schnabel,
29
R. M. S. Schofield,
59
A. Sch ̈onbeck,
29
E. Schreiber,
10
D. Schuette,
10
,
19
B. F. Schutz,
91
,
31
J. Scott,
38
S. M. Scott,
22
D. Sellers,
7
A. S. Sengupta,
96
D. Sentenac,
36
V. Sequino,
27
,
15
A. Sergeev,
109
Y. Setyawati,
53
,
11
D. A. Shaddock,
22
T. Shaffer,
39
M. S. Shahriar,
83
M. Shaltev,
10
B. Shapiro,
42
P. Shawhan,
64
A. Sheperd,
18
D. H. Shoemaker,
12
D. M. Shoemaker,
65
K. Siellez,
65
X. Siemens,
18
M. Sieniawska,
45
D. Sigg,
39
A. D. Silva,
13
A. Singer,
1
L. P. Singer,
69
A. Singh,
31
,
10
,
19
R. Singh,
2
A. Singhal,
14
A. M. Sintes,
104
B. J. J. Slagmolen,
22
J. R. Smith,
24
N. D. Smith,
1
R. J. E. Smith,
1
E. J. Son,
129
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38
F. Sorrentino,
48
T. Souradeep,
16
A. K. Srivastava,
86
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41
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10
J. Steinlechner,
38
S. Steinlechner,
38
D. Steinmeyer,
10
,
19
B. C. Stephens,
18
R. Stone,
88
K. A. Strain,
38
N. Straniero,
66
G. Stratta,
57
,
58
N. A. Strauss,
61
S. Strigin,
50
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124
A. L. Stuver,
7
T. Z. Summerscales,
134
L. Sun,
85
S. Sunil,
86
P. J. Sutton,
91
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36
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98
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32
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59
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6
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97
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10
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31
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1
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1
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7
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106
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87
M. Tonelli,
20
,
21
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38
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,
88
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1
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46
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34
,
35
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7
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23
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89
,
90
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135
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12
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136
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99
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18
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1
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88
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11
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63
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11
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37
L. van der Schaaf,
11
J. V. van Heijningen,
11
A. A. van Veggel,
38
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43
,
44
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1
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40
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12
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46
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44
J. Veitch,
46
P. J. Veitch,
112
K. Venkateswara,
137
D. Verkindt,
8
F. Vetrano,
57
,
58
A. Vicer ́e,
57
,
58
S. Vinciguerra,
46
D. J. Vine,
51
J.-Y. Vinet,
54
S. Vitale,
12
T. Vo,
37
H. Vocca,
34
,
35
C. Vorvick,
39
D. V. Voss,
6
W. D. Vousden,
46
S. P. Vyatchanin,
50
A. R. Wade,
22
L. E. Wade,
138
M. Wade,
138
M. Walker,
2
L. Wallace,
1
S. Walsh,
31
,
10
G. Wang,
14
,
58
H. Wang,
46
M. Wang,
46
X. Wang,
71
Y. Wang,
52
R. L. Ward,
22
J. Warner,
39
M. Was,
8
B. Weaver,
39
L.-W. Wei,
54
M. Weinert,
10
A. J. Weinstein,
1
R. Weiss,
12
L. Wen,
52
P. Weßels,
10
T. Westphal,
10
K. Wette,
10
J. T. Whelan,
102
B. F. Whiting,
6
R. D. Williams,
1
A. R. Williamson,
91
J. L. Willis,
139
B. Willke,
19
,
10
M. H. Wimmer,
10
,
19
W. Winkler,
10
C. C. Wipf,
1
H. Wittel,
10
,
19
G. Woan,
38
J. Woehler,
10
J. Worden,
39
J. L. Wright,
38
D. S. Wu,
10
G. Wu,
7
J. Yablon,
83
W. Yam,
12
H. Yamamoto,
1
C. C. Yancey,
64
H. Yu,
12
M. Yvert,
8
A. Zadro ̇zny,
113
L. Zangrando,
44
M. Zanolin,
98
J.-P. Zendri,
44
M. Zevin,
83
L. Zhang,
1
M. Zhang,
123
Y. Zhang,
102
C. Zhao,
52
M. Zhou,
83
Z. Zhou,
83
X. J. Zhu,
52
M. E. Zucker,
1
,
12
S. E. Zuraw,
119
J. Zweizig
1
(LIGO Scientific Collaboration and Virgo Collaboration)
and S. Sigurdsson
73
Deceased, March 2016.
Deceased, May 2015.
Deceased, March 2015.
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
International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bangalore 560012, India
18
University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
19
Leibniz Universit ̈at Hannover, D-30167 Hannover, Germany
20
Universit`a di Pisa, I-56127 Pisa, Italy
21
INFN, Sezione di Pisa, I-56127 Pisa, Italy
22
Australian National University, Canberra, Australian Capital Territory 0200, Australia
23
The University of Mississippi, University, MS 38677, USA
4
24
California State University Fullerton, Fullerton, CA 92831, USA
25
LAL, Univ. Paris-Sud, CNRS/IN2P3, Universit ́e Paris-Saclay, Orsay, France
26
Chennai Mathematical Institute, Chennai 603103, India
27
Universit`a di Roma Tor Vergata, I-00133 Roma, Italy
28
University of Southampton, Southampton SO17 1BJ, United Kingdom
29
Universit ̈at Hamburg, D-22761 Hamburg, Germany
30
INFN, Sezione di Roma, I-00185 Roma, Italy
31
Albert-Einstein-Institut, Max-Planck-Institut f ̈ur Gravitationsphysik, D-14476 Potsdam-Golm, Germany
32
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
33
Montana State University, Bozeman, MT 59717, USA
34
Universit`a di Perugia, I-06123 Perugia, Italy
35
INFN, Sezione di Perugia, I-06123 Perugia, Italy
36
European Gravitational Observatory (EGO), I-56021 Cascina, Pisa, Italy
37
Syracuse University, Syracuse, NY 13244, USA
38
SUPA, University of Glasgow, Glasgow G12 8QQ, United Kingdom
39
LIGO Hanford Observatory, Richland, WA 99352, USA
40
Wigner RCP, RMKI, H-1121 Budapest, Konkoly Thege Mikl ́os ́ut 29-33, Hungary
41
Columbia University, New York, NY 10027, USA
42
Stanford University, Stanford, CA 94305, USA
43
Universit`a di Padova, Dipartimento di Fisica e Astronomia, I-35131 Padova, Italy
44
INFN, Sezione di Padova, I-35131 Padova, Italy
45
CAMK-PAN, 00-716 Warsaw, Poland
46
University of Birmingham, Birmingham B15 2TT, United Kingdom
47
Universit`a degli Studi di Genova, I-16146 Genova, Italy
48
INFN, Sezione di Genova, I-16146 Genova, Italy
49
RRCAT, Indore MP 452013, India
50
Faculty of Physics, Lomonosov Moscow State University, Moscow 119991, Russia
51
SUPA, University of the West of Scotland, Paisley PA1 2BE, United Kingdom
52
University of Western Australia, Crawley, Western Australia 6009, Australia
53
Department of Astrophysics/IMAPP, Radboud University Nijmegen,
P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
54
Artemis, Universit ́e Cˆote d’Azur, CNRS, Observatoire Cˆote d’Azur, CS 34229, Nice cedex 4, France
55
Institut de Physique de Rennes, CNRS, Universit ́e de Rennes 1, F-35042 Rennes, France
56
Washington State University, Pullman, WA 99164, USA
57
Universit`a degli Studi di Urbino “Carlo Bo,” I-61029 Urbino, Italy
58
INFN, Sezione di Firenze, I-50019 Sesto Fiorentino, Firenze, Italy
59
University of Oregon, Eugene, OR 97403, USA
60
Laboratoire Kastler Brossel, UPMC-Sorbonne Universit ́es, CNRS,
ENS-PSL Research University, Coll`ege de France, F-75005 Paris, France
61
Carleton College, Northfield, MN 55057, USA
62
Astronomical Observatory Warsaw University, 00-478 Warsaw, Poland
63
VU University Amsterdam, 1081 HV Amsterdam, The Netherlands
64
University of Maryland, College Park, MD 20742, USA
65
Center for Relativistic Astrophysics and School of Physics,
Georgia Institute of Technology, Atlanta, GA 30332, USA
66
Laboratoire des Mat ́eriaux Avanc ́es (LMA), CNRS/IN2P3, F-69622 Villeurbanne, France
67
Universit ́e Claude Bernard Lyon 1, F-69622 Villeurbanne, France
68
Universit`a di Napoli “Federico II,” Complesso Universitario di Monte S.Angelo, I-80126 Napoli, Italy
69
NASA/Goddard Space Flight Center, Greenbelt, MD 20771, USA
70
RESCEU, University of Tokyo, Tokyo, 113-0033, Japan.
71
Tsinghua University, Beijing 100084, China
72
Texas Tech University, Lubbock, TX 79409, 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
West Virginia University, Morgantown, WV 26506, USA
77
University of Chicago, Chicago, IL 60637, USA
78
Caltech CaRT, Pasadena, CA 91125, USA
79
Korea Institute of Science and Technology Information, Daejeon 305-806, Korea
80
Universit`a di Roma “La Sapienza,” I-00185 Roma, Italy
81
University of Brussels, Brussels 1050, Belgium
82
Sonoma State University, Rohnert Park, CA 94928, USA
5
83
Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA),
Northwestern University, Evanston, IL 60208, USA
84
University of Minnesota, Minneapolis, MN 55455, USA
85
The University of Melbourne, Parkville, Victoria 3010, Australia
86
Institute for Plasma Research, Bhat, Gandhinagar 382428, India
87
The University of Sheffield, Sheffield S10 2TN, United Kingdom
88
The University of Texas Rio Grande Valley, Brownsville, TX 78520, USA
89
Universit`a di Trento, Dipartimento di Fisica, I-38123 Povo, Trento, Italy
90
INFN, Trento Institute for Fundamental Physics and Applications, I-38123 Povo, Trento, Italy
91
Cardiff University, Cardiff CF24 3AA, United Kingdom
92
Montclair State University, Montclair, NJ 07043, USA
93
MTA E ̈otv ̈os University, “Lendulet” Astrophysics Research Group, Budapest 1117, Hungary
94
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
95
School of Mathematics, University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
96
Indian Institute of Technology, Gandhinagar Ahmedabad Gujarat 382424, India
97
University of Szeged, D ́om t ́er 9, Szeged 6720, Hungary
98
Embry-Riddle Aeronautical University, Prescott, AZ 86301, USA
99
Tata Institute of Fundamental Research, Mumbai 400005, India
100
INAF, Osservatorio Astronomico di Capodimonte, I-80131, Napoli, Italy
101
University of Michigan, Ann Arbor, MI 48109, USA
102
Rochester Institute of Technology, Rochester, NY 14623, USA
103
NCSA, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
104
Universitat de les Illes Balears, IAC3—IEEC, E-07122 Palma de Mallorca, Spain
105
University of Bia lystok, 15-424 Bia lystok, Poland
106
SUPA, University of Strathclyde, Glasgow G1 1XQ, United Kingdom
107
IISER-TVM, CET Campus, Trivandrum Kerala 695016, India
108
Canadian Institute for Theoretical Astrophysics,
University of Toronto, Toronto, Ontario M5S 3H8, Canada
109
Institute of Applied Physics, Nizhny Novgorod, 603950, Russia
110
Pusan National University, Busan 609-735, Korea
111
Hanyang University, Seoul 133-791, Korea
112
University of Adelaide, Adelaide, South Australia 5005, Australia
113
NCBJ, 05-400
́
Swierk-Otwock, Poland
114
IM-PAN, 00-956 Warsaw, Poland
115
Monash University, Victoria 3800, Australia
116
Seoul National University, Seoul 151-742, Korea
117
The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
118
University of Alabama in Huntsville, Huntsville, AL 35899, USA
119
University of Massachusetts-Amherst, Amherst, MA 01003, USA
120
ESPCI, CNRS, F-75005 Paris, France
121
Universit`a di Camerino, Dipartimento di Fisica, I-62032 Camerino, Italy
122
Southern University and A&M College, Baton Rouge, LA 70813, USA
123
College of William and Mary, Williamsburg, VA 23187, USA
124
Instituto de F ́ısica Te ́orica, University Estadual Paulista/ICTP South
American Institute for Fundamental Research, S ̃ao Paulo SP 01140-070, Brazil
125
University of Cambridge, Cambridge CB2 1TN, United Kingdom
126
IISER-Kolkata, Mohanpur, West Bengal 741252, India
127
Rutherford Appleton Laboratory, HSIC, Chilton, Didcot, Oxon OX11 0QX, United Kingdom
128
Whitman College, 345 Boyer Avenue, Walla Walla, WA 99362 USA
129
National Institute for Mathematical Sciences, Daejeon 305-390, Korea
130
Universit ́e de Lyon, F-69361 Lyon, France
131
Hobart and William Smith Colleges, Geneva, NY 14456, USA
132
Janusz Gil Institute of Astronomy, University of Zielona G ́ora, 65-265 Zielona G ́ora, Poland
133
King’s College London, University of London, London WC2R 2LS, United Kingdom
134
Andrews University, Berrien Springs, MI 49104, USA
135
Universit`a di Siena, I-53100 Siena, Italy
136
Trinity University, San Antonio, TX 78212, USA
137
University of Washington, Seattle, WA 98195, USA
138
Kenyon College, Gambier, OH 43022, USA
139
Abilene Christian University, Abilene, TX 79699, USA
We describe a directed search for continuous gravitational waves in data from the sixth initial
LIGO science run. The target was the nearby globular cluster NGC 6544 at a distance of
2
.
7 kpc.
The search covered a broad band of frequencies along with first and second frequency derivatives
6
for a fixed sky position. The search coherently integrated data from the two LIGO interferometers
over a time span of 9.2 days using the matched-filtering
F
-statistic. We found no gravitational-
wave signals and set 95% confidence upper limits as stringent as 6
.
0
×
10
25
on intrinsic strain and
8
.
5
×
10
6
on fiducial ellipticity. These values beat the indirect limits from energy conservation for
stars with characteristic spindown ages older than 300 years and are within the range of theoretical
predictions for possible neutron-star ellipticities. An important feature of this search was use of a
barycentric resampling algorithm which substantially reduced computational cost; this method will
be used extensively in searches of Advanced LIGO and Virgo detector data.
I. INTRODUCTION
The LIGO Scientific Collaboration (LSC) and Virgo
Collaboration have undertaken numerous searches for
continuous gravitational waves (GW). None has yet de-
tected a signal, but many have placed interesting upper
limits on possible sources. These searches have generally
been drawn from one of three types.
Targeted searches are aimed at a single known pulsar,
with a known precise timing solution. The first search for
continuous waves, using data from the first initial LIGO
science run (S1), was of this type [1], and subsequent
searches have probed the Crab and Vela pulsars, among
others [2–7]. A number of these most recent searches
have been able to set direct upper limits on GW emission
comparable to or stricter than the indirect “spin-down
limits” (derived from energy conservation, as well as the
distance from Earth of the target, its gravitational-wave
frequency, and the frequency’s first derivative, the “spin-
down”) for a few of the pulsars searched.
All-sky searches, as their name suggests, survey the
entire sky for neutron stars not seen as pulsars. These
are very computationally costly, searching over wide fre-
quency bands and covering large ranges of spin-down pa-
rameters [8–17]. The latest of these have incorporated
new techniques to cover possible binary parameters as
well [18]. Recent all-sky searches have set direct upper
limits close to indirect upper limits derived from galactic
neutron-star population simulations [19].
Directed searches sit between these two extremes. As
in the all-sky case, their targets are neutron stars not seen
as pulsars, so that the frequency and other parameters
are unknown. They focus, however, on a known sky loca-
tion (and therefore a known detector-frame Doppler mod-
ulation). This directionality allows for searching over a
wide range of frequencies and frequency derivatives while
remaining much cheaper computationally than an all-sky
search without sacrificing sensitivity. This approach was
first used in a search for the accreting neutron star in the
low-mass X-ray binary Sco X-1 [9, 20, 21].
The search for the central compact object (CCO) in the
supernova remnant (SNR) Cassiopeia A (Cas A)[22] was
the first directed search for a young neutron star without
electromagnetically detected pulsation, motivated by the
idea that young neutron stars might be promising emit-
ters of continuous GW. The Cas A search [22] set upper
limits on GW strain which beat an indirect limit derived
from energy conservation and the age of the remnant [23]
over a wide frequency band. Other directed searches have
since followed in its footsteps, using different data anal-
ysis methods, for supernova 1987A and unseen neutron
stars near the galactic center [21, 24]. Most method-
ologically similar to this search and the S5 Cas A search
was a recent search for nine supernova remnants [25],
which also used fully coherent integration over observa-
tion times on the order of 10 days.
In this article, we describe a search of data from the
sixth initial LIGO science run (S6) for potential young
isolated neutron stars with no observed electromagnetic
pulsations in the nearby (
d
2
.
7 kpc) globular clus-
ter NGC 6544. Globular clusters are unlikely to contain
young neutron stars, but in these dense environments
older neutron stars may be subject to debris accretion
(see Sec. II C) or other events which could render them
detectable as gravitational wave sources. This particular
globular cluster was chosen so that a computationally-
feasible coherent search similar to [22] could beat the
age-based indirect limits on GW emission.
The search did not find a GW signal, and hence the
main result is a set of upper limits on strain amplitude,
fiducial ellipticity, and
r
-mode amplitude
α
, similar to
those presented in [22]. An important new feature of
the search described here was use of a barycentric re-
sampling algorithm which substantially reduced compu-
tational cost, allowing a search over a larger parameter
space using a longer coherence time (see Sec. II D). This
barycentric resampling method will be used extensively
in searches of Advanced LIGO and Virgo detector data.
This article is structured as follows: In Sec. II we
present the method, implementation, and results of the
search. The upper limits set in the absence of a signal
are presented in Sec. III, and the results are discussed in
Sec. IV.
II. SEARCHES
A. Data selection
The sixth initial LIGO science run (S6) extended from
July 7 2009 21:00:00 UTC (GPS 931035615) to October
21 2010 00:00:00 UTC (GPS 971654415) and included
two initial LIGO detectors with 4-km arm lengths, H1 at
LIGO Hanford Observatory (LHO) near Hanford, Wash-
ington and L1 at LIGO Livingston Observatory (LLO)
near Livingston, Louisiana.
After optimization at fixed computing cost determined
an optimum coherence time of 9.2 days (see Sec. II D),
7
S6 sampling times
Label
GPS Start
GPS End
Dates (UTC)
Week 1
931053000
931657800
Jul 8-15, 2009
Week 2
936053000
936657800
Sep 3-10, 2009
Week 3
941053000
941657800
Oct 31-Nov 7, 2009
Week 4
946053000
946657800
Dec 28, 2009-Jan 4, 2010
Week 5
951053000
951657800
Feb 24-Mar 3, 2010
Week 6
956053000
956657800
Apr 23-30, 2010
Week 7
961053000
961657800
Jun 20-27, 2010
Week 8
966053000
966657800
Aug 17-24, 2010
Week 9
971053000
971657800
Oct 14-21, 2010
TABLE I. The weeks sampled to find the most sensitive S6
data. Times are given both in GPS and UTC calendar dates.
two different methods were used to determine which
data would be searched, producing two different 9.2-day
stretches. Both were searched, allowing for the compari-
son of search results between them.
The first method was to look for the most sensitive av-
erage data from S6. This was done by taking nine week-
long data samples from each detector spaced roughly 55
days apart, giving nine evenly spaced weeks throughout
the duration of S6. The data samples used are shown
in Table I. We chose four representative frequencies
(100 Hz, 200 Hz, 400 Hz, 600 Hz) and generated joint-
detector strain noise power spectral densities (PSDs) in
1-Hz bands about these frequencies, using 0
.
01-Hz bin-
ning. The sensitivity
h
sens
was then taken to be
h
j
sens
=
1
(1
/
100)
·
100
i
=0
(
S
i
h
(
f
i
))
1
j
(1)
where
S
i
h
(
f
) represents the PSD value of the
i
th
bin, at
frequency
f
i
, and the index
j
runs from 1 through 4 and
represents the four representative frequencies (note that
this is not an actual estimate of detectable strain). Based
on this figure of merit, the final nine days of S6 yielded
the most sensitive data stretch for all four frequencies:
October 11-20, 2010 (GPS 970840605 – 971621841).
An alternate data selection scheme [22, 25], which
takes detector duty cycle into account is to maximize
the figure of merit
k,f
1
S
h
(
f
)
(2)
where
S
h
(
f
) represents the strain noise power spectral
density at frequency
f
in the
k
th
Short Fourier Trans-
form (SFT), and the sum is taken across all frequencies
f
in the search band and all SFTs in a given 9.2-day
(see Sec. II D below) observation time. The SFT format
is science-mode detector data split into 1800s segments,
band-pass filtered from 40–2035 Hz, Tukey windowed in
the time domain, and Fourier transformed. This method
favored a different data stretch: July 24–August 2, 2010
(GPS 964007133 – 964803598). This second data stretch
had slightly worse average sensitivity than the first, but
a higher detector livetime: our first (October) data set
contained 374 SFTs (202 from Hanford and 172 from Liv-
ingston) with average sensitivity
h
200Hz
sens
= 1
.
92
×
10
23
;
the second (July-August) data set contained 642 SFTs
(368 from Hanford and 274 from Livingston) with aver-
age sensitivity
h
200Hz
sens
= 1
.
95
×
10
23
.
B. Analysis method
The analysis was based on matched filtering, the op-
timal method for detecting signals of known functional
form. To obtain that form we assumed that the poten-
tial target neutron star did not glitch (suffer an abrupt
frequency jump) or have significant timing noise (addi-
tional, possibly stochastic, time dependence of the fre-
quency) [26] during the observation. We also neglected
third and higher derivatives of the GW frequency, based
on the time span and range of
̇
f
and
̈
f
(the first two
derivatives) covered. The precise expression for the in-
terferometer strain response
h
(
t
) to an incoming contin-
uous GW also includes amplitude and phase modulation
by the changing of the beam patterns as the interferom-
eter rotates with the earth. It depends on the source’s
sky location and orientation angles, as well as on the pa-
rameters of the interferometer. The full expression can
be found in [27].
The
detection
statistic
used
was
the
multi-
interferometer
F
-statistic [28], based on the single-
interferometer
F
-statistic [27].
This combines the
results of matched filters for the signal in a way that is
computationally fast and nearly optimal [29]. Assuming
Gaussian noise, 2
F
is drawn from a
χ
2
distribution with
four degrees of freedom.
We used the implementation of the
F
-statistic in
the LALSuite package [30].
In particular most of
the computing power of the search was spent in the
ComputeFStatistic
v2
program.
Unlike the version
used in preceding methodologically similar searches [22,
25], this one implements an option to use a barycentric
resampling algorithm which significantly speeds up the
analysis.
The method of efficiently computing the
F
-statistic
by barycentering and Fast-Fourier-transforming the data
was first proposed in [27]. Various implementations of
this method have been developed and used in previous
searches, such as [31–33]. Here we are using a new LAL-
Suite [30] implementation of this method, which evolved
out of [33], and which will be described in more detail in a
future publication. It converts the input data into a het-
erodyned, downsampled timeseries weighted by antenna-
pattern coefficients, and then resamples this timeseries
at the solar system barycenter using an interpolation
technique. The resampled time series is then Fourier-
transformed to return to the frequency domain, and from
there the
F
-statistic is calculated. For this search, both
8
single-detector and multi-detector
F
-statistics were cal-
culated (see Vetoes section below).
Timing tests run on a modern processor (ca. 2011)
showed that the resampling code was more than 24 times
faster in terms of seconds per template per SFT. This
improvement, by more than an order of magnitude, was
used to perform a deeper search over a wider parame-
ter space than previously possible for the computational
cost incurred (see target selection and search parameters
below).
C. Target selection
Unlike previous directed searches, this one targets a
globular cluster. Since stars in globular clusters are very
old, it is unlikely that a young neutron star will be found
in such an environment. However, some neutron stars
are known to be accompanied by debris disks [34] and
even planets [35–37]. In the densely populated core of
a globular cluster, close encounters may stimulate bom-
bardment episodes as debris orbits are destabilized, akin
to cometary bombardments in our solar system when the
Oort cloud is perturbed [38]. A neutron star which has
recently accreted debris could have it funneled by the
magnetic field into mountains which relax on timescales
of 10
5
–10
8
years [39] and emit gravitational waves for
that duration. Other mechanisms are likely to last a few
years at most [40]. Hence an old neutron star could be
a good gravitational wave source with a low spin-down
age.
The first step in picking a globular cluster is a figure of
merit based on that for directed searches for supernova
remnants [23], an indirect upper limit on gravitational
wave strain based on energy conservation and the age of
the object. Here the inverse of the object age is replaced
by the interaction rate of the globular cluster, which
scales like density
(3
/
2)
times core radius
2
[38, 41], reflect-
ing the mean time since last bombardment. It is hard to
know when the most recent bombardment episode was,
and thus the constant factor out in front, but globular
clusters can be ranked with respect to each other by a
maximum-strain type figure of merit
h
0
ρ
3
/
4
c
r
c
/d,
(3)
where
ρ
c
is the globular cluster core density,
r
c
is the
core radius,
d
is the distance to the cluster, and thus
r
c
/d
is the angular radius of the core. We ranked the Harris
catalog of globular clusters [42, 43] by this figure of merit
and looked at the top few choices, which were mainly
nearby core-collapsed clusters. The closest is NGC 6397
at
2
.
2 kpc, but it is at high declination. This lessens
the Doppler modulation of any gravitational wave signal,
making it harder to distinguish from stationary spectral
line artifacts, which tend to contaminate searches at high
declination near the ecliptic pole. Hence we chose the
next closest, NGC 6544, which is at a declination of less
than 30 degrees and only slightly further away at
2
.
7
kpc.
We restrict the search described below to sources for
which the bombardment history corresponds to a charac-
teristic spindown age older than 300 years. The figure of
300 years is mainly a practical consideration: the cost of
a search rises steeply for lower spin-down ages, and 300
years proved tractable for the Cas A search [22].
D. Search parameter space
An iterative method was used to generate the param-
eter space to be searched. Starting with an (assumed)
spin-down age no younger than 300 years, a braking in-
dex
n
= 5 (see below), and the known distance to the
globular cluster, we calculated the age-based indirect up-
per limit. This is an optimistic limit on the gravitational
wave strain
h
0
which assumes that all energy lost as the
target neutron star spins down is radiated away as grav-
itational waves[23]:
h
0
1
d
5
GI
2
c
3
τ
(
n
1)
.
(4)
Here
d
is the distance to the target,
τ
the assumed age
of the target object, and
I
a fiducial moment of inertia
for a neutron star (10
38
kg
·
m
2
).
G
and
c
are the grav-
itational constant and the speed of light, respectively.
This age-based limit was then superimposed on a curve
of expected upper limits in the absence of signal for the
LIGO detectors, obtained from the noise power spectral
density (PSD) harmonically averaged over all of S6 and
both interferometers. A running median with a 16-Hz
window was further applied to smooth the curve. The
curve is given by:
h
95%
0
= Θ
S
h
T
data
(5)
where
S
h
is the harmonically averaged noise,
T
data
is the
coherence time (the total data livetime searched coher-
ently), initially estimated at two weeks, and Θ is a sen-
sitivity factor that includes a trials factor, or number of
templates searched, and uncertainty in the source orien-
tation [23]. For a directed search like ours, Θ is approx-
imately 35 [23, 44]. The intersection of this coherence-
time adjusted upper limit curve and our indirect limit
(Eq. (4)) gives an initial frequency band over which the
indirect limit can be beaten. The braking index is related
to the frequency parameters by the definition:
n
=
f
̈
f
̇
f
2
.
(6)
Assuming a braking index
n
between 2 and 7 covers most
accepted neutron star models (
n
= 5, the neutron star
9
radiating all energy as gravitational waves via the mass
quadrupole, is used to obtain the indirect limit). We al-
low the braking indices in these expressions to range from
2 to 7 independently, to reflect the fact that in general
multiple processes are operating and
̇
f
is not a simple
power law. This constraint on the braking indices then
produces limits on the frequency derivatives given by [23]
f
τ
≤−
̇
f
f
6
τ
(7)
for the spindown at each frequency and
2
̇
f
2
f
̈
f
7
̇
f
2
f
(8)
for the second spindown at each (
f,
̇
f
). The step sizes for
frequency and its derivatives are given by the equations
[33, 45, 46]
df
=
2
3
m
π
1
T
data
,
(9)
d
̇
f
=
12
5
m
π
1
T
2
data
,
(10)
and
d
̈
f
=
20
7
m
π
1
T
3
data
.
(11)
where
m
is the mismatch parameter, the maximum loss of
2
F
due to discretization of the frequency and derivatives
[47, 48]. This search used a mismatch parameter
m
= 0
.
2.
From these relations the total number of templates
(points in frequency parameter space) to be searched can
be calculated, and with knowledge of the per-template
time taken by the code (obtained from timing tests), the
total computing time can be obtained. Limiting the tar-
get computing time, in our case to 1000 core-months,
then allows us to solve for the coherence time
T
data
, which
we then feed back into Eq. (5) to begin the process anew
until it iteratively converges on a parameter space and
accompanying coherence time. The iterative algorithm
thus balances the computational gains from resampling
between the use of a longer coherence time (giving bet-
ter sensitivity) and the expansion of the parameter space
over which the indirect limit can be beaten (caused by
the improved sensitivity). The result for the globular
cluster NGC 6544 is a search over the frequency range
92.5 Hz to 675 Hz, with a coherence time of 9.2 days.
The peculiar velocities of globular clusters are negli-
gible, as they represent an essentially constant Doppler
shift of order 1
×
10
3
; so is velocity dispersion, which
is an order of magnitude smaller. Since we search down
to 300-year timescales, the acceleration of the cluster is
also not an issue [49].
Band Job min. and max. Note
frequency (Hz)
370.1 370.1
370.2 L1 Output Mode Cleaner (OMC) Jitter Line
393.1 393.1
393.2 H1 Calibration Line
396.7 396.7
396.8 L1 Calibration Line
400.2 400.2
400.3 H1 OMC Quad Photodiode (QPD) Line
403.8 403.8
403.9 L1 OMC QPD Line
417.1 417.1
417.2 H1 OMC QPD Line
580.0 580.0
580.1 L1 2Hz Harmonic
TABLE II. Search sub-bands that, due to the identified dis-
turbances, produced an excessive number of candidates and
were aborted. The 580.0 Hz sub-band had to be stopped only
for the July-August run; the other six bands were vetoed in
both searches.
E. Implementation
All searches were run on the LIGO-Caltech Comput-
ing Cluster at the California Insitute of Technology in
Pasadena, CA, under the control of the Condor queu-
ing system for parallel processing.
The search pro-
cess was split into 5825 individual Condor jobs, each of
which searched over a 0
.
1-Hz subband and corresponding
swathes of (
̇
f,
̈
f
). The number of templates searched by
each job thus varied as a function of frequency.
Each search job produced three distinct outputs. First,
a record was made of all candidates with 2
F
above 45.0,
a choice of recording different from the the fifth initial
LIGO science run (S5) search which recorded the loud-
est 0
.
01% of events. This was needed because of the
contamination of the S6 noise by detector artifacts, as
well as limits on the disk space available and the in-
put/output capability of the cluster filesystem. Second,
a histogram of 2
F
values for all templates searched was
produced to verify that the data matched the expected
chi-square distribution (described in Subsec. II B above).
Last, each job produced a record of the loudest (highest-
2
F
-valued) candidate in its 0.1-Hz band, regardless of
threshold. This data was used in the setting and valida-
tion of upper limits (see Section III below).
F. Vetoes
A high value of 2
F
is not enough to claim a detec-
tion, since instrumental artifacts lead to non-Gaussian
and/or non-stationary noise in many narrow frequency
bands. A variety of veto techniques were used to trim
down the initial list of candidates and arrive at a final
list of outliers.
Six 0.1 Hz sub-bands (see Table (II)) had to be man-
ually aborted in both searches, with a seventh aborted
in the July-August search, as even with the threshold
in place, they produced an excessive number of candi-
dates. Each of these subbands was compared to records
of known noise artifacts and disturbances in the detec-
tor, and in each case a known instrumental line was con-
firmed. These sub-bands were later rerun with the record
10
of candidates disabled in order to produce histograms and
loudest-outlier files for upper limit validation.
To protect against spurious noise lines, a second veto
based on the
F
-statistic consistency veto introduced in
[15] was used. This uses the fact that an astrophysical
signal should have a higher joint value of 2
F
(combining
data from the two interferometers) than in either inter-
ferometer alone. Recorded candidates that violate this
inequality were vetoed. This is a simpler version of the
more recent line veto [50].
Finally, to enforce coincidence between detectors, a
single-detector threshold was employed. Since a true as-
trophysical signal should be present in both detectors at a
significant level, any candidates passing the initial joint-
detector detection criteria (see II G) also had to pass an
additional threshold on the individual-detector values of
2
F
.
The 0.1-Hz band between 200 and 200.1 Hz was ar-
bitrarily chosen as a test band. The joint-detector 2
F
values were taken from the loudest-candidate files and
used to semi-analytically compute [51] an estimate of
the 95% upper limit for that subband using the SFTs
employed by the search. Sets of 1,000 software injections
were performed with strengths of 100%, 80%, 60%, 40%
and 20% of this estimated upper limit. The results were
used to set a threshold of 2
F ≥
20 in each individual
detector, leading to an additional false dismissal rate of
1.5% of injections at the 95% confidence upper limit es-
timate. Candidates failing to meet this criterion were
vetoed.
G. Detection criteria and results
The results of a mock data challenge were used to set
a detection criterion for the joint-detector 2
F
value. The
mock data challenge consisted of a set of 1577 artificial
continuous wave (CW) signals injected into a set of real
detector data from S6, which were then searched for using
the same resampled
F
-Statistic used in the search. A
survey of the loudest joint-detector 2
F
value reported
for background subbands known to be free of injected
signals for the band between 200 Hz and 240 Hz (used in
a pilot run) gave a mean loudest joint-detector 2
F ≈
55.
Given this background level, the detection criterion was
chosen to be joint-detector 2
F ≥
60 to maintain high
efficiency and low false-alarm rate (the false-alarm rate
was 3.17% in these pilot subbands).
With these detection criteria, a search was carried out
in S6 data. The lists of all templates with joint-detector
2
F
greater than 45.0 were filtered for the individual de-
tector threshold and the consistency veto, both singly
and in tandem. If the loudest template failed either
check, the list was used to move to the next-loudest tem-
plate until the loudest template passing all thresholds
and vetoes was identified. This created three sets of
results (threshold-only, veto-only, and threshold+veto)
which could all be queried independently.
The joint 2
F
values for the loudest single template
(passing all thresholds and vetoes) in each 0.1 Hz sub-
band were collated into lists spanning 10Hz (100 joint
2
F
values per list). These lists were then parsed, and
any joint 2
F
values greater than the joint 2
F
thresh-
old of 60 were identified. Each such entry’s correspond-
ing template was then added to a list of outliers. This
method produced a list of 168 outliers for the entirety of
the search band in the October data, and a list of 155
outliers for the entirety of the search band in the July-
August data.
These outliers were then tested using
time shifts
and
extended looks
. In a time shift, the frequency param-
eters of the outliers from each data stretch (October
and July-August) were evolved forwards or backwards
in time, as appropriate, and sought in the opposite data
stretch, under the assumption that a true astrophysical
signal should be present in both data sets for the im-
plicitly long-lived CW signals searched for here. A set
of 1000 software injections (simulated signals with ran-
domly generated parameters) underwent the same treat-
ment to provide a baseline 2
F
threshold for signal detec-
tion, and outliers surpassing the threshold were consid-
ered present.
In an extended look, each outlier was sought in an ex-
panded 20-day coherence time encompassing the original
nine-day coherence time; the same assumption of signal
continuity would predict, roughly, a doubling of the 2
F
value for a doubling of coherence time. These cases as
well were tested with software injections to determine a
threshold.
In both time shifts and extended looks, the searches
were conducted over a parameter space envelope obtained
by starting at the outlier frequency parameters (
f,
̇
f,
̈
f
)
±
2 bins, and evolving those ranges backwards or forwards
in time using the extremum values of the next derivative
(e.g.,
f
evolved at maximum
̇
f
,
̇
f
evolved at maximum
̈
f
) to achieve a conservatively wide envelope.
Outliers detected with joint 2
F
greater than the
threshold established by the software injections were la-
beled candidates and received manual followup. These
tests were not cumulative; an outlier needed only to sur-
vive any one test, not all of them, to persist as a candi-
date. The software injection threshold for both types of
test was placed at a value for joint 2
F
yielding 80% injec-
tion recovery; because each outlier would receive further
consideration if it passed either test, the false dismissal
probability for the first follow-up stage was
4%. The
combined 323 outliers produced only seven candidates,
listed in Table III.
These candidates were subject to manual followup.
They were compared to strain histograms of run-averaged
(i.e., over all of S6) spectra from each detector, to iden-
tify instrumental noise lines which could be responsible.
In five of the seven cases, the strain histograms gave clear
evidence of an instrumental noise line responsible for the
candidate, and in these cases records of prior detector
characterization studies were consulted to provide expla-