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Model of gravitational waves from precessing black-hole binaries through merger and ringdown

Eleanor Hamilton, L. T. London, Jonathan E. Thompson, Edward Fauchon-Jones, Mark Hannam, C. V. Kalaghatgi, S. Khan, F. Pannarale, Alex Vañó-Viñuales

2021Physical review. D/Physical review. D.81 citationsDOIOpen Access PDF

Abstract

We present phenompnr, a frequency-domain phenomenological model of the gravitational-wave 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 nonprecessing (aligned-spin) binaries, and it is only the aligned-spin models that are fully tuned to NR results. In phenompnr we incorporate precessing-binary numerical relativity results in two ways: (i) we produce the first numerical relativity-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 coprecessing frame. The numerical relativity calibration has been performed on 40 simulations of binaries with mass ratios between $1\ensuremath{\mathbin:}1$ and $1\ensuremath{\mathbin:}8$, 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 $1\ensuremath{\mathbin:}4$ and within 1% up to mass ratio $1\ensuremath{\mathbin:}8$.

Topics & Concepts

PhysicsPrecessionLIGOGravitational waveMass ratioBlack hole (networking)Angular momentumDimensionless quantitySpin (aerodynamics)Numerical relativityBinary black holeSpinsBinary numberComputational physicsAstrophysicsClassical mechanicsQuantum mechanicsCondensed matter physicsRouting protocolArithmeticMathematicsComputer networkComputer scienceRouting (electronic design automation)ThermodynamicsLink-state routing protocolPulsars and Gravitational Waves ResearchAstrophysical Phenomena and ObservationsGeophysics and Sensor Technology
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