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      Concepts and status of Chinese space gravitational wave detection projects

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      Nature Astronomy
      Springer Science and Business Media LLC

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          Is Open Access

          Observation of Gravitational Waves from a Binary Black Hole Merger

          On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of 1.0×10(-21). It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203,000 years, equivalent to a significance greater than 5.1σ. The source lies at a luminosity distance of 410(-180)(+160)  Mpc corresponding to a redshift z=0.09(-0.04)(+0.03). In the source frame, the initial black hole masses are 36(-4)(+5)M⊙ and 29(-4)(+4)M⊙, and the final black hole mass is 62(-4)(+4)M⊙, with 3.0(-0.5)(+0.5)M⊙c(2) radiated in gravitational waves. All uncertainties define 90% credible intervals. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.
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            GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral

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              Advanced LIGO: the next generation of gravitational wave detectors

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                Author and article information

                Contributors
                Journal
                Nature Astronomy
                Nat Astron
                Springer Science and Business Media LLC
                2397-3366
                September 2021
                September 15 2021
                : 5
                : 9
                : 881-889
                Article
                10.1038/s41550-021-01480-3
                7a866503-540a-41c1-a5df-241627dadb2a
                © 2021

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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