For full details see LIGO DCC, arXiv, or Phys. Rev. Letters
This paper and all the companion papers can also be found at papers.ligo.org.

Estimated source parameters

Quantity	Value	Upper/Lower error estimate	Unit
Primary black hole mass	36	+5 -4	M sun
Secondary black hole mass	29	+4 -4	M sun
Final black hole mass	62	+4 -4	M sun
Final black hole spin	0.67	+0.05 -0.07
Luminosity distance	410	+160 -180	Mpc
Source redshift, z	0.09	+0.03 -0.04
Energy radiated	3	+0.5 -0.5	M sun

TABLE I. Estimated source parameters for GW150914. We report the median value as well as the range of the 90% credible interval. Masses are measured in the source frame; to convert masses to detector frame, multiply by (1 + z). The source redshift assumes standard cosmology.

click for DATA	click for DATA (L1 only)
click for DATA (Numerical relativity)	click for DATA (Numerical relativity)
click for DATA	click for DATA

FIG. 1. The gravitational-wave event GW150914 observed by the LIGO Hanford (H1, left column panels) and Livingston (L1, right column panels) detectors. Times are shown relative to September 14, 2015 at 09:50:45 UTC. For visualization, all time series are filtered with a 35–350 Hz band-pass filter to suppress large fluctuations outside the detectors’ most sensitive frequency band, and band-reject filters to remove the strong instrumental spectral lines seen in the Fig. 3 spectra.

• Top row, left: H1 strain. Top row, right: L1 strain. GW150914 arrived first at L1 and 6.9 (+0.5 −0.4) ms later at H1; for a visual comparison the H1 data are also shown, shifted in time by this amount and inverted (to account for the detectors’ relative orientations).
• Second row: Gravitational-wave strain projected onto each detector in the 35–350 Hz band. Solid lines show a numerical relativity waveform for a system with parameters consistent with those recovered from GW150914 confirmed by an independent calculation. Shaded areas show 90% credible regions for two waveform reconstructions: one that models the signal as a set of sine-Gaussian wavelets and one that models the signal using binary-black-hole template waveforms. These reconstructions have a 95% overlap.
• Third row: Residuals after subtracting the filtered numerical relativity waveform from the filtered detector time series.
• Bottom row: A time-frequency decomposition of the signal power associated with GW150914. Both plots show a signal with frequency increasing with time.

Numerical relativity DATA Reconstructed DATA

separation DATA velocity DATA

FIG. 2. Left: Estimated gravitational-wave strain amplitude from GW150914 projected onto H1. This shows the full bandwidth of the waveforms, without the filtering used for Fig. 1. Right: The Keplerian effective black hole separation in units of Schwarzschild radii and the effective relative velocity.

Hanford DATA Livingston DATA

FIG.3. The average measured strain-equivalent noise, or sensitivity, of the Advanced LIGO detectors during the time analyzed to determine the significance of GW150914 (Sept 12 - Oct 20, 2015). Hanford (H1) is shown in red, Livingston (L1) in blue. The solid traces represent the median sensitivity and the shaded regions indicate the 5th and 95th percentile over the analysis period. The narrowband features in the spectra are due to known mechanical resonances, mains power harmonics, and injected signals used for calibration.

Search Result C3 DATA Search Background C3 DATA Search Result C2 C3 DATA Search Background C2 C3 DATA

Search Results DATA

FIG. 4. Search results from the generic transient search (left) and the binary coalescence search (right). These histograms show the number of candidate events (orange markers) and the mean number of background events in the search class where GW150914 was found (black lines) as a function of the search detection statistic and with a bin width of 0.2. The scales on the top give the significance of an event in Gaussian standard deviations based on the corresponding noise background . The significance of GW150914 is greater than 5.1 σ and 4.6 σ for the binary coalescence and the generic transient searches, respectively. (Left): Along with the primary search (C3) we also show the results (yellow markers) and background (green curve) for an alternative search that treats events independently of their frequency evolution (C2+C3). The classes C2 and C3 are defined in the text. (Right): The tail in the black-line background of the binary coalescence search is due to random coincidences of GW150914 in one detector with noise in the other detector. (This type of event is practically absent in the generic transient search background because they do not pass the time-frequency consistency requirements used in that search.) The blue curve is the background excluding those coincidences, which is used to assess the significance of the second strongest event candidate.

• Data usage notes   Please Read This First!
• The data are provided in three formats. HDF5 , Frame (.gwf), and gzipped ascii text. Many data analysis environments can read in data from HDF5 files, including Python (see the h5py package), MATLAB, C/C++, and IDL.
• The md5 checksums provide a check for downloaders that they have received the right file: run the Unix command "md5" (or "md5sum", depending on your OS) on your file and compare to LOSC published values. If different, try downloading again, and if the problem persists, contact us.
• Technical details especially about data quality and injections
• Tutorials to work with the strain data.

Strain Data at 4096 Hz

Strain h(t) time series centered at GPS 1126259462:

Duration	Hanford	Livingston
32 seconds approx 1 Mbyte	DATA hdf5 DATA gwf DATA txt.gz	DATA hdf5 DATA gwf DATA txt.gz
4096 seconds approx 134 Mbyte	DATA hdf5 DATA gwf DATA txt.gz	DATA hdf5 DATA gwf DATA txt.gz

Strain Data at 16384 Hz

Strain h(t) time series centered at GPS 1126259462:

Duration	Hanford	Livingston
32 seconds approx 4 Mbyte	DATA hdf5 DATA gwf DATA txt.gz	DATA hdf5 DATA gwf DATA txt.gz
4096 seconds approx 536 Mbyte	DATA hdf5 DATA gwf DATA txt.gz	DATA hdf5 DATA gwf DATA txt.gz

• View the tutorial as a web page.
• The tutorial is available as a python script, or as an iPython Notebook.
• To run it, you will need Python 2.6 or 2.7, numpy, scipy, matlibplot, and h5py. See the software setup tutorial.
• For all files needed to run the tutorial, download this zip file.
• Explore more LOSC tutorials.

The numerical relativity waveform used in this tutorial can be obtained as a plain-text file, here, where the first column is the time in seconds relative to the peak of the waveform, and the second column is the (unitless) strain. This waveform was obtained from the SXS Gravitational Waveform Database, courtesy of the SXS Collaboration (please see Acknowledgements in that link). It corresponds to waveform ID SXS:BBH:0305, with mass ratio m1/m2 = 1.221 and aligned spins. Its time axis has been rescaled for a system with detector frame total mass of 74.6 solar masses, and the overall amplitude and phase are adjusted, all to get good agreement with the data at both detectors.

The LIGO Observatory

The Laser Interferometer Gravitational-Wave Observatory (LIGO) consists of two widely separated installations within the United States — one in Hanford, Washington and the other in Livingston, Louisiana — operated in unison as a single observatory. LIGO is operated by the LIGO Laboratory, a consortium of the California Institute of Technology (Caltech) and the Massachusetts Institute of Technology (MIT). Funded by the National Science Foundation, LIGO is an international resource for both physics and astrophysics.

The GEO600 Detector

The GEO600 project aims at the direct detection of gravitational waves by means of a laser interferometer of 600 m armlength located near Hannover, Germany. Besides collecting data for gravitational wave searches, the GEO600 detector has been used to develop and test advanced instrumentation for gravitational wave detection.

The LIGO Scientific Collaboration

The LIGO Scientific Collaboration (LSC) is a group of scientists seeking to make the first direct detection of gravitational waves, use them to explore the fundamental physics of gravity, and develop the emerging field of gravitational wave science as a tool of astronomical discovery. The LSC works toward this goal through research on, and development of techniques for, gravitational wave detection, and the development, commissioning and exploitation of gravitational wave detectors. The LSC carries out the science of the LIGO and GEO600 Observatories. Participation in the LSC is open to all interested scientists and engineers from educational and research institutions.

For full details see LIGO DCC or arXiv.

Hanford DATA Livingston DATA

Figure 10: The cWB point estimate for the waveform and the 90% credible interval from the BW analysis. The reconstructed waveforms and shown data are whitened using estimated noise curves for each detector at the time of the event.

For full details see LIGO DCC or arXiv.

For full details see LIGO DCC or arXiv.

For full details see LIGO DCC or arXiv

DATA

FIG 3. The rate at which sensitive time-volume accumulates with redshift.

R1 DATA, gstlal | pycbc R2 DATA, gstlal | pycbc R DATA, gstlal | pycbc

FIG 4. The posterior density on the rate of GW150914-like BBH inspirals, R1 (green), G197392-like BBH inspirals, R2 (red), and the inferred total rate, R = R1 + R2 (blue).

Flat DATA, gstlal | pycbc Powerlaw DATA, gstlal | pycbc

FIG 5. Sensitivity of the inferred BBH coalescence rate to the assumed astrophysical distribution BBH masses. The curves represent the posterior assuming that BBH masses are flat in log (m1)- log (m2) (blue; “Flat”), are exactly GW150914-like or G197392- like as described in Section 2 (green; “Reference”), or are distributed as in Eq. (20) (red; “Power Law”).

For full details see LIGO DCC or arXiv

For full details see LIGO DCC or arXiv.

For full details see LIGO DCC or arXiv or Phys. Rev. Letters.

DATA

FIG. 1: Expected sensitivity of the network of advanced LIGO and Virgo detectors to the Fiducial field model. Energy density spectra are shown in blue (solid for the total background; dashed for the residual background assuming final advanced LIGO and Virgo sensitivity). The pink shaded region shows the 90% CL statistical uncertainty propagated from the local rate measurement. The black curves are power-law integrated sensitivities for the network expected for the two first observing runs O1 and O2, and for 2 years at the design sensitivity in O5 (O3 and O4 are not significantly different than O5); see Table I. If the astrophysical background spectrum intersects a black line, it has expected SNR ≥ 1.

For full details see the paper: LIGO DCC or arXiv.

For full details see LIGO DCC or arXiv.

Hanford DATA Livingston DATA

FIG.1 The average measured strain-equivalent noise, or sensitivity, of the Advanced LIGO detectors during the time analyzed to determine the significance of GW150914 (Sept 12 - Oct 20, 2015). Hanford (H1) is shown in red, Livingston (L1) in blue. The solid traces represent the median sensitivity and the shaded regions indicate the 5th and 95th percentile over the analysis period. The narrowband features in the spectra are due to known mechanical resonances, mains power harmonics, and injected signals used for calibration

For full details see LIGO DCC

For full details see LIGO DCC or arXiv. or Phys. Rev. Letters.

Anthology of papers describing the technology of LIGO can be found at:
    Quest for Detection: Articles from Review of Scientific Instruments .

For full details see LIGO DCC.

Four pipelines produced sky localization information, known as CWB, LIB, BAYESTAR, and LALInference. Their sky coverage comparison is shown below, in equatorial coordinates:

Comparison of different GW sky maps, showing the 90% credible level contours for each algorithm. This orthographic projection centered on the centroid of the LIB localization. The inset shows the distribution of the polar angle θHL (equivalently, the arrival time difference ∆tHL).	Sky at the time of the event, with the LALInference skymap, contoured in deciles of probability. View is from the South Atlantic Ocean, North at the top, with the Sun rising and the Milky Way diagonally from NW to SE.

The skymaps can be visualized in astronomical context with the Skymap Viewer, as in the right-hand image: CWB, LIB, BAYESTAR, LALInference.

The skymaps are represented as HEALPIX-FITS files in equatorial frame, available gzipped:

• CWB DATA,
• LIB DATA,
• BAYESTAR DATA.
• LALInference DATA,

A python library for reading such files is healpy. A very simple healpy code to work with LIGO-Virgo skymaps is here. A large number of simulated skymaps is available here.

Files are in wav format, with data whitened and band-passed to 20 - 300 Hz. These files can be generated from the data using the GW150914 tutorial that is linked above.

• Observed waveform, whitened and band-passed 20 Hz to 300 Hz, for H1 and L1.
• Observed waveform, whitened and band-passed 20 Hz to 300 Hz, and shifted up by 400 Hz, for H1 and L1.
• Observed waveform, whitened and band-passed 40 Hz to 400 Hz, and shifted up by 200 Hz, for H1 and L1.
• Best fit theoretical waveform, whitened and band-passed, and whitened and shifted up by 400 Hz
• Median reconstructions of the event, and whitened. H in left channel, L in right channel: BayesWave.
• Best-fit (MAP) waveforms from paper P1500218, H in left channel, L in right channel: Unwhitened and whitened.

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The following audio files have been produced from a newer tutorial (June 2016) entitled "Tutorial on Signal Processing with Open Data from any O1 BBH event". See the tutorials section for more details.

• Hanford data
  • whitened and bandpassed
  • whitened, bandpassed, and frequency shifted
• Livingston data
  • whitened and bandpassed
  • whitened, bandpassed, and frequency shifted
• Best-fit template
  • whitened
  • whitened and frequency shifted