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GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs

B. P. Abbott et al. (LIGO Scientific Collaboration and Virgo Collaboration)
Phys. Rev. X 9, 031040 – Published 4 September 2019
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  • INTRODUCTION
  • INSTRUMENTAL OVERVIEW AND DATA
  • SEARCHES
  • SEARCH RESULTS
  • SOURCE PROPERTIES
  • WAVEFORM RECONSTRUCTIONS
  • MERGER RATES OF COMPACT BINARY SYSTEMS
  • CONCLUSIONS
  • ACKNOWLEDGMENTS
  • APPENDICES
    • References

    Abstract

    We present the results from three gravitational-wave searches for coalescing compact binaries with component masses above 1  M⊙ during the first and second observing runs of the advanced gravitational-wave detector network. During the first observing run (O1), from September 12, 2015 to January 19, 2016, gravitational waves from three binary black hole mergers were detected. The second observing run (O2), which ran from November 30, 2016 to August 25, 2017, saw the first detection of gravitational waves from a binary neutron star inspiral, in addition to the observation of gravitational waves from a total of seven binary black hole mergers, four of which we report here for the first time: GW170729, GW170809, GW170818, and GW170823. For all significant gravitational-wave events, we provide estimates of the source properties. The detected binary black holes have total masses between 18.6−0.7+3.2  M⊙ and 84.4−11.1+15.8  M⊙ and range in distance between 320−110+120 and 2840−1360+1400  Mpc. No neutron star–black hole mergers were detected. In addition to highly significant gravitational-wave events, we also provide a list of marginal event candidates with an estimated false-alarm rate less than 1 per 30 days. From these results over the first two observing runs, which include approximately one gravitational-wave detection per 15 days of data searched, we infer merger rates at the 90% confidence intervals of 110−3840  Gpc−3 y−1 for binary neutron stars and 9.7−101  Gpc−3 y−1 for binary black holes assuming fixed population distributions and determine a neutron star–black hole merger rate 90% upper limit of 610  Gpc−3 y−1.

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    • Received 14 December 2018
    • Revised 27 March 2019

    DOI:https://doi.org/10.1103/PhysRevX.9.031040

    Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

    Published by the American Physical Society

    Physics Subject Headings (PhySH)

    1. Research Areas
    Gravitational wave detectionGravitational wave sourcesGravitational waves
    Gravitation, Cosmology & Astrophysics

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    Popular Summary

    Gravitational waves, ripples in the fabric of spacetime, allow researchers to investigate compact celestial objects such as black holes and to explain the origin of some gamma-ray bursts, which are among the most energetic electromagnetic outbursts in the Universe. Since 2015, the LIGO Scientific and Virgo Collaborations have detected 11 gravitational-wave signals, in addition to a number of marginal event candidates. Here, we present the first gravitational-wave transient catalog, GWTC-1, which describes the properties of every detection to date.

    The 11 significant detections in the catalog are associated with mergers between extraordinarily dense objects: ten are from mergers of two massive black holes and one is from a merger of two neutron stars. Researchers analyzed each of the events in detail to determine the properties of the source. We use state-of-the-art theoretical and numerical general relativistic gravitational-wave models to determine the masses, spins, and tidal deformations for the neutron star event, as well as parameters related to the location and orientation of the binary. The observation of ten binary black hole mergers and one binary neutron star merger allows us to estimate the rate at which these binaries merge in the Universe. We also present 14 marginal event candidates whose astrophysical origin cannot be definitively ruled out.

    The gravitational-wave catalog allows physicists and astronomers to analyze the accompanying publicly available data, investigate the underlying populations, perform tests of general relativity, and pursue entirely new avenues of research.

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    Vol. 9, Iss. 3 — July - September 2019

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    • Figure 1
      Figure 1

      Left: BNS range for each instrument during O2. The break at week 3 is for the 2016 end-of-year holidays. There is an additional break in the run at week 23 to make improvements to instrument sensitivity. The Montana earthquake’s impact on the LHO instrument sensitivity can be seen at week 31. Virgo joins O2 in week 34. Right: Amplitude spectral density of the total strain noise of the Virgo, LHO, and LLO detectors. The curves are representative of the best performance of each detector during O2.

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    • Figure 2
      Figure 2

      Cumulative histograms of search results for the matched-filter searches, plotted versus inverse false-alarm rate. The dashed lines show the expected background, given the analysis time. Shaded regions denote sigma uncertainty bounds for Poisson uncertainty. The blue dots are the named gravitational-wave events found by each respective search. Any events with a measured or bounded inverse false-alarm rate greater than 3000 y are shown with an arrow pointing right. Left: PyCBC results. Right: GstLAL results.

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    • Figure 3
      Figure 3

      Cumulative histograms of search results for the cWB search, plotted versus the inverse false-alarm rate. The dashed lines show the expected background, given the analysis time. Shaded regions denote sigma uncertainty bounds for Poisson uncertainty. The blue dots are the named gravitational-wave events found by each respective search. Any events with a measured or bounded inverse false-alarm rate greater than 3000 y are shown with an arrow pointing right.

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    • Figure 4
      Figure 4

      Parameter estimation summary plots I. Posterior probability densities of the component masses and final masses and spins of the GW events. For the two-dimensional distributions, the contours show 90% credible regions. Left: Source-frame component masses m1 and m2. We use the convention that m1≥m2, which produces the sharp cut in the two-dimensional distribution. Lines of constant mass ratio q=m2/m1 are shown for 1/q=2, 4, 8. For low-mass events, the contours follow lines of constant chirp mass. Right: The mass Mf and dimensionless spin magnitude af of the final black holes. The colored event labels are ordered by source-frame chirp mass. The same color code and ordering (where appropriate) apply to Figs. 5, 6, 7, 8.

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    • Figure 5
      Figure 5

      Parameter estimation summary plots II. Posterior probability densities of the mass ratio and spin parameters of the GW events. The shaded probability distributions have equal maximum widths, and horizontal lines indicate the medians and 90% credible intervals of the distributions. For the two-dimensional distributions, the contours show 90% credible regions. Events are ordered by source-frame chirp mass. The colors correspond to the colors used in summary plots. For GW170817, we show results for the high-spin prior ai<0.89. Top left: The mass ratio q=m2/m1. Top right: The effective aligned spin magnitude χeff. Bottom left: Contours of 90% credible regions for the effective aligned spin and mass ratio of the binary components for low- (high-) mass binaries are shown in the upper (lower) panel. Bottom right: The effective precession spin posterior (colored) and its effective prior distribution (white) for BBH (BNS) events. The priors are conditioned on the χeff posterior distributions.

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    • Figure 6
      Figure 6

      Parameter estimation summary plots III. Posterior probability distributions for the dimensionless component spins cS→1/(Gm12) and cS→2/(Gm22) relative to the normal to the orbital plane L→, marginalized over the azimuthal angles. The bins are constructed linearly in spin magnitude and the cosine of the tilt angles and are assigned equal prior probability. Events are ordered by source-frame chirp mass. The colors correspond to the colors used in summary plots. For GW170817, we show results for the high-spin prior ai<0.89.

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    • Figure 7
      Figure 7

      Parameter estimation summary plots IV. Posterior probability densities of distance dL, inclination angle θJN, and chirp mass M of the GW events. For the two-dimensional distributions, the contours show 90% credible regions. For GW170817, we show results for the high-spin prior ai<0.89. Left: The inclination angle and luminosity distance of the binaries. Right: The luminosity distance (or redshift z) and source-frame chirp mass. The colored event labels are ordered by source-frame chirp mass.

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    • Figure 8
      Figure 8

      Parameter estimation summary plots V. The contours show 90% and 50% credible regions for the sky locations of all GW events in a Mollweide projection. The probable position of the source is shown in equatorial coordinates (right ascension is measured in hours, and declination is measured in degrees). 50% and 90% credible regions of posterior probability sky areas for the GW events. Top: Confidently detected O2 GW events [22] (GW170817, GW170104, GW170823, GW170608, GW170809, and GW170814) for which alerts were sent to EM observers. Bottom: O1 events (GW150914, GW151226, and GW151012), along with O2 events (GW170729 and GW170818) not previously released to EM observers. Where applicable, the initial sky maps shared with EM partners in low latency are available from Ref. [185].

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    • Figure 9
      Figure 9

      Posterior distributions for component masses and tidal deformability for GW170817 for the waveform models: IMRPhenomPv2NRT, SEOBNRv4NRT, TaylorF2, SEOBNRv4T, and TEOBResumS. Top: 90% credible regions for the component masses for the high-spin prior ai<0.89 (left) and low-spin prior ai<0.05 (right). The edge of the 90% credible regions is marked by points; the uncertainty in the contour is smaller than the thickness shown because of the precise chirp mass determination. 1D marginal distributions are renormalized to have equal maxima, and the vertical and horizontal lines give the 90% upper and lower limits on m1 and m2, respectively. Bottom: Posterior distributions of the effective tidal deformability parameter Λ˜ for the high-spin (left) and low-spin (right) priors. These PDFs are reweighted to have a flat prior distribution. The original Λ˜ prior is shown in yellow. 90% upper bounds are represented by vertical lines for the high-spin prior (left). For the low-spin prior (right), 90% highest posterior density (HPD) credible intervals are shown instead. Gray PDFs indicate seven representative equations of state (EOSs) using masses estimated with the IMRPhenomPv2NRT model.

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    • Figure 10
      Figure 10

      Time-frequency maps and reconstructed signal waveforms for the ten BBH events. Each event is represented with three panels showing whitened data from the LIGO detector where the higher SNR is recorded. The first panel shows a normalized time-frequency power map of the GW strain. The remaining pair of panels shows time-domain reconstructions of the whitened signal, in units of the standard deviation of the noise. The upper panels show the 90% credible intervals from the posterior probability density functions of the waveform time series, inferred using CBC waveform templates from Bayesian inference (LALInference) with the PhenomP model (red band) and by the BayesWave wavelet model (blue band) [53]. The lower panels show the point estimates from the cWB search (solid lines), along with a 90% confidence interval (green band) derived from cWB analyses of simulated waveforms from the LALInference CBC parameter estimation injected into data near each event. Visible differences between the different reconstruction methods are verified to be consistent with a noise origin (see the text for details).

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    • Figure 11
      Figure 11

      Astrophysical signal and terrestrial noise event models compared with results for the matched-filter searches, PyCBC (left) and GstLAL (right), versus the respective search’s ranking statistic: ϱ for PyCBC [73] and lnL for GstLAL [9, 82]. These ranking statistics are not the same as the SNRs reported in Table 1; see citations for details. For each panel, the solid colored lines show the median estimated rate (“model”) of signal, noise, or signal plus noise events above a given ranking statistic threshold, while shaded regions show the estimated model uncertainties on the combined and individual models at 68% and 95% confidence. The observed number of events above the ranking statistic threshold is indicated by the black line, with confidently detected events (Sec. 4b) labeled. The PyCBC signal model and observed events are restricted to events with masses compatible with a BBH, with a chirp mass >4.35  M⊙ (so that BNS candidate events including GW170817 are not plotted); the GstLAL signal model includes all events, with the signal counts summed over the three astrophysical categories BNS, NSBH, and BBH. The different ranking statistic used in the PyCBC and GstLAL searches lead to differently shaped signal models. The black dashed line in the GstLAL plot shows a realization of the cumulative counts in time-shifted data, reinforcing its consistency with the noise model.

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    • Figure 12
      Figure 12

      This figure shows the posterior distribution—combined from the results of PyCBC and GstLAL—on the BBH event rate for the flat in log (blue) and power-law (orange) mass distributions. The symmetric 90% confidence intervals are indicated with vertical lines beneath the posterior distribution. The union of intervals is indicated in black.

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    • Figure 13
      Figure 13

      This figure shows the posterior distributions of the BNS event rate for the GstLAL and PyCBC searches. The uniform mass distribution corresponds to the orange curves, and Gaussian mass distributions correspond to the blue curves. The symmetric 90% confidence intervals are indicated with vertical lines beneath the posterior distributions.

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    • Figure 14
      Figure 14

      This figure shows the 90% rate upper limit for the NSBH category, measured at a set of three discrete BH masses (5, 10, and 30  M⊙) with the fiducial NS mass fixed to 1.4  M⊙. The upper limit is evaluated for both matched-filter search pipelines, with GstLAL corresponding to red curves and PyCBC to blue. We also show two choices of spin distributions: isotropic (dashed lines) and aligned spin (solid lines).

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    • Figure 15
      Figure 15

      Normalized spectrograms of the time around common noise artifacts with a time-frequency evolution of a related trigger template overlaid. Top left: Scattered light artifacts at Hanford with the template of trigger 170616 overlaid. Top right: A 60–200 Hz nonstationarity at Livingston with the template of trigger 170412 overlaid. Bottom left: A short-duration transient at Livingston with the template of trigger 170630 overlaid. Bottom right: A blip at Hanford with the template of a subthreshold high-mass trigger overlaid.

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    • Figure 16
      Figure 16

      Jensen-Shannon divergence between the two precessing BBH waveform models for key binary parameters, detector-frame chirp mass, mass ratio, luminosity distance, effective aligned spin, and effective precession spin.

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    • Figure 17
      Figure 17

      Example prior and posterior distributions for GW170809. Left column: The four panels show the three different prior choices P1 (black), P2 (blue), and P3 (red) for four different physical parameters: the chirp mass, the effective aligned spin, the effective precession spin, and the luminosity distance. Right column: The four panels show the corresponding posterior probability distributions for the same four physical parameters obtained under the three different prior assumptions P1 (black), P2 (blue), and P3 (red). In all panels, the dashed vertical lines indicate the 90% credible intervals.

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