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GW190521: a Binary Black Hole Merger with a Total Mass of 150M ⊙

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GW190521: a Binary Black Hole Merger with a Total Mass of 150M ⊙ GW190521: A Binary Black Hole Merger with a Total Mass of 150M - Supplemental Material The LIGO Scientific Collaboration and the Virgo Collaboration SUPPLEMENTAL MATERIAL The CWB searches are performed with two pipeline configurations targeting detection of low mass (binary Coherent Wave Burst search BH configuration) and high mass (IMBH configuration) binary systems. They use different selection cuts de- fined a priori to alleviate the large variability of the non- Coherent Wave Burst (CWB) is a search algorithm for stationary noise in the detectors. The GW190521 event detection and reconstruction of gravitational wave (GW) was detected by CWB in its IMBH configuration. To fur- transient signals operating without a specific waveform ther improve the background the CWB analysis employs model. CWB searches for coincident signal power in additional selection cuts based on the generic properties multiple detectors with duration up to a few seconds. of IMBH binary signals: (a) the low central frequency The analysis is performed in the wavelet domain [1] on f of the GW signal and (b) their large chirp mass. In data normalized by the amplitude spectral density of the c CWB, the redshifted chirp mass M of a binary system detector noise. CWB selects wavelets with amplitudes is estimated by using the time-frequency evolution of the above the fluctuations of the detector noise and groups GW signal [4]. To select IMBH systems we require that them into clusters. For clusters correlated in multiple de- jMj > 10M and the signal central frequency f is below tectors, CWB identifies coherent events and reconstructs c 80 Hz. Both parameters M = 22:6M and f = 58 Hz the source sky location and signal waveforms with the c reconstructed for GW190521 are well within the limits constrained maximum likelihood method [2]. defined by the analysis selection cuts. The CWB detection statistic is based on the coherent To estimate the statistical significance of selected can- network energy E obtained by cross-correlating data in c p didates, each event was ranked against a set of back- different detectors; E is the estimator of the coherent c ground triggers obtained by repeating the analysis on network signal-to-noise ration (SNR) [2]. The agreement time-shifted data. The time shifts were selected to be between a GW signal and CWB reconstruction is charac- much longer (≥ 1 s) than the expected signal time delay terized by a reduced chi-squared statistic χ2 = E =N , n df between the detectors, in order to exclude astrophysical where E is the residual energy estimated after the re- n events from the background set. By using multiple time constructed waveforms are subtracted from the whitened shifts, a set of background events equivalent to 9800 yr of data, and N is the number of independent wavelet am- df null observation was obtained. The candidate events that plitudes describing the event. GW190521 is identified survived the selection criteria were then assigned a false- in LIGO data with χ2 = 0:68, showing no evidence for alarm rate given by the rate of background events with residual energy inconsistent with Gaussian noise. the CWB detection statistics greater than the detection To improve the robustness of the algorithm against statistic of the candidate event. non-stationary detector noise (glitches) and reduce the rate of false alarms, CWB uses signal-independent ve- toes. The primary veto cuts are on the network correla- 2 GstLAL and PyCBC searches tion coefficient cc = Ec=(Ec +En) and the χ . For a GW signal the expected values of both statistics are close to 2 unity and candidate events with cc < 0:7 and χ > 2:5 GstLAL [5{10] and PyCBC [11{16] independently are rejected as potential glitches. The blip glitches, de- implement search algorithms targeting compact binary scribed in the Data section of the letter, are decimated mergers with banks of template waveforms and matched by a selection cut based on a distinct shape of the glitch filtering. Both algorithms are used for low-latency as well waveform. It is best described by a cosine wave in a Gaus- as offline analyses. sian envelope with the standard deviation less than half All analyses based on GstLAL and PyCBC in O3 to a cycle. This selection cut starts to affect the detection date rely on SEOBNRv4 waveforms [17] as templates for of intermediate mass black hole (IMBH) binary systems the heavier-mass BH binary systems. These templates with total redshifted mass M > 300M , but the loss of neglect several physical effects. First, the spins of the detection efficiency is marginal (< 20%) as was tested compact objects are assumed to be aligned with the or- with simulated numerical relativity waveforms. In addi- bital angular momentum, such that the orbital plane does tion, the periodic variations of the noise in the frequency not precess. Second, the orbit is assumed to be quasicir- band 16-48 Hz, due to scattered light, are corrected with cular: its eccentricity is assumed to be negligible when the linear prediction error filter [3]. the signal becomes visible in the interferometers. Third, 2 only the quadrupolar radiation multipole moment is in- In order to assign a false-alarm rate to each candidate cluded. Fourth, finite-size effects (such as tidal deforma- coincidence, both the online and offline PyCBC analy- bility) are neglected. Simulation studies, as well as the ses use time shifts to construct background samples and published LIGO and Virgo discoveries, demonstrate that measure the cumulative background rate as a function of the above simplifications reduce the computational cost the ranking statistic. The two pipelines differ in how this of the search by at least an order of magnitude without process is implemented. The online analysis includes the compromising its sensitivity to most detectable signals data from the third interferometer, if available, in the [18, 19]. Nevertheless, there can be extreme systems for calculation of the false-alarm rate of a coincident can- which one or more of the above assumptions are not ap- didate. The offline pipeline calculates the background plicable, implying that the search may detect the system over an amount of data larger by more than an order with a reduced significance, or miss it altogether [19{21]. of magnitude, and can therefore claim correspondingly The template banks also necessarily cover a limited range lower false-alarm rates for events louder than the avail- of redshifted masses. In O3, the range of redshifted total able background. masses is [2; 758] M for GstLAL and [2; 500] M for Contrary to previously discovered compact binary 2 PyCBC [22, 23]; however, the effective high-mass bound- mergers, PyCBC's χr signal-based veto [24] reported a ary depends on mass ratio and spins. In the bank used disagreement between the event and the template wave- by PyCBC, templates with nearly equal mass and small form producing the highest significance in the search 2 effective spin have a maximum redshifted total mass just [17, 25]. Specifically, χr, expected to be ∼ 1 for sig- above 100 M , while this limit is ≈ 600M for the bank nals well described by the search templates, resulted in used by GstLAL. 1:1 (LHO) and 3:2 (LLO) in the offline analysis; the on- GstLAL and PyCBC differ in several important tech- line analysis showed a similar behavior. The large LLO 2 nical choices, notably the signal-based vetoes used to re- χr reflects a deficit of signal power between ∼ 23 Hz > ject instrumental transients, the ranking of GW candi- and ∼ 43 Hz, and similarly for ∼ 68 Hz, with respect dates resulting from matched filtering, and the method to the template waveform. This effect can be due to a used to assign false-alarm rates to the ranked GW can- combination of high redshifted total mass, which places didates. These differences can lead to vastly different GW190521 at the limit of the mass space covered by Py- significances for the same astrophysical signal. CBC's configuration in O3 [23], and possibly waveform GstLAL uses a likelihood-ratio statistic to rank GW effects not modeled by the templates, such as precession, candidates by (i) the matched-filter SNRs, (ii) a sig- higher-order multipole moments, or eccentricity. 2 nal consistency check based on waveform autocorrelation, In order to investigate this point, we recalculated χr at (iii) the sensitivities of the detectors, (iv) the time and LLO using different quasicircular waveform models with phase delays observed across the detector network, and parameters that maximize the network SNR, obtaining (v) a template-dependent factor that describes the prob- values between 0:8 and 1:8, which no longer indicate a ability that a signal from the observed source population disagreement. The LHO{LLO network matched-filter is identified by a specific template in our bank. Informa- SNR correspondingly increases to 14:5{15:0, consistent tion from auxiliary channels that monitor the detectors with the values obtained by CWB and GstLAL. As an and their environment is also included in the ranking. additional check, we then added the maximum-likelihood GstLAL estimates the search background from trig- SEOBNRv4 template to the bank used by PyCBC and gers not found in coincidence at times when both LIGO repeated the offline analysis. The new template was pre- interferometers are operating. The background triggers ferred by the ranking over the previous template, increas- are used to estimate the probability density of noise-like ing the LHO{LLO network SNR to 14:5 and decreasing 2 events, and Monte Carlo methods are used to sample the the LLO χr to 1:7. These values are consistent with the noise probability density and produce a mapping from other pipelines.
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