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The final twist: A model of gravitational waves from precessing black-hole binaries through merger and ringdown
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We present PhenomPNR, a frequency-domain phenomenological model of the gravitational-wave (GW) signal from binary-black-hole mergers that is tuned to numerical relativity (NR) simulations of precessing binaries. In many current waveform models, e.g., the "Phenom" and "EOBNR" families that have been used extensively to analyse LIGO-Virgo GW observations, analytic approximations are used to add precession effects to models of non-precessing (aligned-spin) binaries, and it is only the aligned-spin models that are fully tuned to NR results. In PhenomPNR we incorporate precessing-binary NR results in two ways: (i) we produce the first NR-tuned model of the signal-based precession dynamics through merger and ringdown, and (ii) we extend a previous aligned-spin model, PhenomD, to include the effects of misaligned spins on the signal in the co-precessing frame. The NR calibration has been performed on 40 simulations of binaries with mass ratios between 1:1 and 1:8, where the larger black hole has a dimensionless spin magnitude of 0.4 or 0.8, and we choose five angles of spin misalignment with the orbital angular momentum. PhenomPNR has a typical mismatch accuracy within 0.1% up to mass-ratio 1:4, and within 1% up to mass-ratio 1:8.
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Cited by 3 Pith papers
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PhenomXPNR: An improved gravitational wave model linking precessing inspirals and NR-calibrated merger-ringdown
PhenomXPNR is a fast frequency-domain gravitational-wave template for spinning black-hole mergers that combines post-Newtonian inspiral precession with numerical-relativity-calibrated merger and ringdown.
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