Antialigned spin of GW191109: Glitch mitigation and its implications
Rhiannon Udall ,
1,2
,*
Sophie Hourihane ,
1,2
,
†
Simona Miller ,
1,2
,
‡
Derek Davis ,
1,2
,§
Katerina Chatziioannou ,
1,2
,
∥
Max Isi ,
3
,¶
and Howard Deshong
4,2
,**
1
Department of Physics,
California Institute of Technology
, Pasadena, California 91125, USA
2
LIGO Laboratory,
California Institute of Technology
, Pasadena, California 91125, USA
3
Center for Computational Astrophysics,
Flatiron Institute
, New York, New York 10010, USA
4
Schmidt Academy for Software Engineering, Pasadena, California 91125, USA
(Received 3 October 2024; accepted 11 December 2024; published 16 January 2025)
With a high total mass and an inferred effective spin antialigned with the orbital axis at the 99.9% level,
GW191109 is one of the most promising candidates for a dynamical formation origin among gravitational
wave events observed so far. However, the data containing GW191109 are afflicted with terrestrial noise
transients, i.e., detector glitches, generated by the scattering of laser light in both LIGO detectors. We
study the implications of the glitch(es) on the inferred properties and astrophysical interpretation of
GW191109. Using time- and frequency-domain analysis methods, we isolate the critical data for spin
inference to 35
–
40 Hz and 0.1
–
0.04 s before the merger in LIGO Livingston, directly coincident with the
glitch. Using two models of glitch behavior, one tailored to slow scattered light and one more generic, we
perform joint inference of the glitch and binary parameters. When the glitch is modeled as slow scattered
light, the binary parameters favor antialigned spins, in agreement with existing interpretations. When
more flexible glitch modeling based on sine-Gaussian wavelets is used instead, a bimodal aligned/
antialigned solution emerges. The antialigned spin mode is correlated with a weaker inferred glitch and
preferred by
∼
70
∶
30
compared to the aligned spin mode and a stronger inferred glitch. We conclude that if
we assume that the data are only impacted by slow scattering noise, then the antialigned spin inference is
robust. However, the data alone cannot validate this assumption and resolve the antialigned spin and
potentially dynamical formation history of GW191109.
DOI:
10.1103/PhysRevD.111.024046
I. INTRODUCTION
Reported in the third gravitational wave (GW) transient
catalog (GWTC-3)
[1]
, GW191109_010717 (more con-
cisely GW191109) stands out among existing binary black
hole signals. With source-frame primary and secondary
masses of
m
1
¼
65
þ
11
−
11
M
⊙
and
m
2
¼
47
þ
15
−
13
M
⊙
(90% sym-
metric credible intervals), it is among the most massive
events. Furthermore, there is significant support for black
hole (BH) spins antialigned with the orbital angular
momentum: the mass-weighted effective spin
[2
–
4]
is
χ
eff
¼
−
0
.
29
þ
0
.
42
−
0
.
31
. For these reasons, as well as support
for unequal masses,
q
¼
m
2
=m
1
¼
0
.
73
þ
0
.
21
−
0
.
24
, spin preces-
sion, and hints of eccentricity
[5,6]
, the binary is potentially
of dynamical and/or hierarchical origin
[7,8]
and impacts
population inference
[9,10]
.
Multiple GW191109 properties hint toward a dynamical
origin. High masses, above the pair-instability supernova
limit of
45
−
70
M
⊙
(depending on modeling assumptions)
[11,12]
, may require a hierarchical mechanism in order to
form and merge. Asymmetric masses, in particular, might
imply the merger of a second- and a first-generation BH
[7]
.
Furthermore, population synthesis simulations of isolated
formation scenarios typically find little support for spins
antialigned with the orbital angular momentum, unless
supernova kicks are exceptionally high
[8,13,14]
. Finally,
eccentricity would also be challenging to explain except by
dynamical processes
[5,15,16]
, due to the rapid orbit
circularization by GW emission
[17]
.
Given their astrophysical implications, the inferred prop-
erties of GW191109 are worth scrutinizing. The first
potential source of systematics is the waveform used to
model the signal. GWTC-3 employed the
IMRP
henom
XPHM
[18]
and
SEOBNR
v4
PHM
approximants
[19]
, with inference
performed by
B
ilby
[20,21]
and
RIFT
[22]
, respectively. Both
models include the physical effects of higher-order modes
and spin precession, and headline results (as quoted above)
*
Contact author: rudall@caltech.edu
†
Contact author: sohour@caltech.edu
‡
Contact author: smiller@caltech.edu
§
Contact author: dedavis@caltech.edu
∥
Contact author: kchatziioannou@caltech.edu
¶
Contact author: misi@flatironinstitute.org
**
Contact author: hdeshong@caltech.edu
PHYSICAL REVIEW D
111,
024046 (2025)
2470-0010
=
2025
=
111(2)
=
024046(19)
024046-1
© 2025 American Physical Society
are their average. Howe
ver, GW191109 is flagged
for systematic differences between approximants
[1]
,
especially for the binary inclination (edge-on versus
face-on/off, respectively) and the longer
χ
eff
>
0
tail
with
IMRP
henom
XPHM
. A third waveform,
NRS
ur7dq4
[23]
,
wasemployedinRef.
[24]
. A direct surrogate of numeri-
cal relativity simulations,
NRS
ur7dq4
is expected to be the
most accurate available model for systems with high
masses and spins
[23
–
25]
. These results bolster the
evidence for dynamical origin, with a more negative spin,
χ
eff
¼
−
0
.
38
þ
0
.
21
−
0
.
20
, asymmetric masses,
q
¼
0
.
65
þ
0
.
20
−
0
.
19
,and
a precessing spin parameter
[26]
of
χ
p
¼
0
.
59
þ
0
.
26
−
0
.
27
.While
waveform systematics remain relevant, the broad agree-
ment between three waveforms (including a direct surro-
gate to numerical relativity) that
χ
eff
≲
0
to varying
credibility, suggests that subsequent interpretations of
its formation history remain valid.
A second potential source of systematics concerns
modeling the detector noise. Around GW191109
’
s arrival,
both LIGO
[27]
detectors experienced a terrestrial noise
transient known as a scattered light glitch
[1,28,29]
. The
Virgo detector
[30]
was offline at this time, and so only the
LIGO detectors contributed to the observation. In LIGO
Hanford (LHO), the glitch power was at a nadir while the
event was in the detection band, making its impact on the
inferred parameters negligible, see Appendix
A
. As such,
we ignore the LHO glitch going forward. By contrast,
glitch power in the Livingston detector (LLO) was directly
coincident in time and frequency with the signal, a circum-
stance which could bias astrophysical inference
[31
–
35]
.
Specifically, glitch power extends up to
∼
40
Hz, coincident
with the signal, see Fig.
1
. Spin parameters might be
particularly susceptible to such data quality issues due to
the relatively smaller imprint they leave on signals com-
pared to, e.g., the BH masses. For example, GW200129
shows evidence of spin precession
[1,25]
, but its signifi-
cance depends on how the glitch that overlapped that signal
is modeled
[33,36]
.
The headline GWTC-3 results were obtained after an
estimate for the glitch had been subtracted from the data.
The two-step process involved first modeling the signal and
the glitch with a flexible sum of coherent and incoherent
wavelets, respectively, with
B
ayes
W
ave
[37
–
39]
. Second, a
fair draw from the glitch posterior was subtracted and the
system parameters were inferred as quoted above. This
procedure has been shown to generally lead to unbiased
mass and (aligned) spin inference
[31,34]
. However, uncer-
tainties remain related to
B
ayes
W
ave
’
s glitch model and in the
fair draw chosen to be subtracted. These effects were
investigated in Ref.
[28]
, albeit with a simpler waveform
model with single-spin precession and no higher-order
modes,
IMRP
henom
P
v2
[40]
. Glitch mitigation was found to
affect the
χ
eff
inference by a similar amount as waveform
systematics. Completely removing the glitch-affected data,
i.e., all LLO data below 40 Hz, instead resulted in a dramatic
shift of
χ
eff
to positive values
χ
eff
¼
0
.
27
þ
0
.
24
−
0
.
48
.
The stark impact of glitch-affected data on astrophysically
impactful spin inference motivates our study. In Sec.
III
we
extend Ref.
[28]
to explore the manner in which the data
inform the system parameters. Using
NRS
ur7dq4
and a fre-
quency-domain analysis, we find that the LLO data between
30 and 40 Hz are crucial for spin inference: excluding
30
–
40 Hz data shifts the probability of
χ
eff
<
0
from
99.4% to 32.2%, effectively wiping out any preference for
antialigned spins. A similar time-domain analysis
[41]
high-
lights the role of the data 0.1
–
0.04 s prior to merger. These
data, which inform the
χ
eff
<
0
measurement, coincide in
time and frequency with excess power in LLO, see Fig.
2
and
in particular the excess power at
∼
36
Hz. To check whether
such dramatic shifts in support for
χ
eff
<
0
are possible from
Gaussian noise alone, we analyze 100 simulated signals
consistent with GW191109. We find that shifts of this
magnitude are unlikely but not impossible as 6% of the
simulations experience a larger shift than GW191109.
In Sec.
IV
, we focus on the 36 Hz excess power and
address the key question: is the excess power part of the
signal (and hence
χ
eff
<
0
) or is it part of the glitch (and
hence inference has been affected by systematics)? Rather
than the two-step process of glitch fitting and subtraction,
we perform a full analysis where we simultaneously model
both the signal and the glitch. Using a physically motivated
model for scattered light glitches
[29]
we find
χ
eff
<
0
at the
99.9% level using
NRS
ur7dq4
. We attribute this to the fact that
the 36 Hz power is more contained in time than expected for
scattered light glitches that are characterized by arches with
long duration and extensive frequency range. This analysis,
therefore, attributes the 36 Hz power to the signal and thus
prefers
χ
eff
<
0
. It is, however, possible that not all
terrestrial power is due to scattered light or that the physical
model of Ref.
[29]
does not capture all scattered light power.
Instead, using a more flexible model for the glitch based on
wavelets and
B
ayes
W
ave
and
IMRP
henom
XPHM
we obtain a
bimodal solution for the spin. One mode, preferred at the
70
∶
30
level, attributes most of the 36 Hz power to the signal
and results in
χ
eff
<
0
. The second mode attributes this
power to the glitch and results in
χ
eff
>
0
. Given the low
signal-to-noise ratio (SNR) of the 36 Hz power, these results
are impacted by the priors of the glitch model parameters at
the few percent level.
In Sec.
V
we summarize our conclusions. Physically
grounded assumptions about the behavior of scattered light
glitches lend support to
χ
eff
<
0
for GW191109, and thus a
dynamical origin. However, both systematic limitations on
scattered light models and statistical uncertainty due to low
SNR of the excess power and the impact of glitch priors
prevent us from making that determination confidently.
While the crucial 36 Hz power is not part of the scattered
light glitch as modeled in Ref.
[29]
, we cannot rule out
glitch mismodeling or other types of terrestrial noise.
RHIANNON UDALL
et al.
PHYS. REV. D
111,
024046 (2025)
024046-2