Two new surrogate models, trained on NR simulations, predict remnant properties and eccentricity dynamics for nonspinning eccentric black hole binaries with q ≤ 4 and e < 0.23.
A Surrogate Model of Gravitational Waveforms from Numerical Relativity Simulations of Pre- cessing Binary Black Hole Mergers
7 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present the first surrogate model for gravitational waveforms from the coalescence of precessing binary black holes. We call this surrogate model NRSur4d2s. Our methodology significantly extends recently introduced reduced-order and surrogate modeling techniques, and is capable of directly modeling numerical relativity waveforms without introducing phenomenological assumptions or approximations to general relativity. Motivated by GW150914, LIGO's first detection of gravitational waves from merging black holes, the model is built from a set of $276$ numerical relativity (NR) simulations with mass ratios $q \leq 2$, dimensionless spin magnitudes up to $0.8$, and the restriction that the initial spin of the smaller black hole lies along the axis of orbital angular momentum. It produces waveforms which begin $\sim 30$ gravitational wave cycles before merger and continue through ringdown, and which contain the effects of precession as well as all $\ell \in \{2, 3\}$ spin-weighted spherical-harmonic modes. We perform cross-validation studies to compare the model to NR waveforms \emph{not} used to build the model, and find a better agreement within the parameter range of the model than other, state-of-the-art precessing waveform models, with typical mismatches of $10^{-3}$. We also construct a frequency domain surrogate model (called NRSur4d2s_FDROM) which can be evaluated in $50\, \mathrm{ms}$ and is suitable for performing parameter estimation studies on gravitational wave detections similar to GW150914.
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representative citing papers
A PINN learns higher-order corrections to the TaylorT4 PN model from eight NR surrogate waveforms, reducing phase and amplitude errors in the inspiral while enforcing physical symmetries.
BHPTNRSur2dq1e3 is a new surrogate model for spinning intermediate-mass-ratio black hole binary gravitational waves, constructed from ppBHPT training data with domain decomposition for retrograde modes and calibrated to NR simulations.
New surrogate models NRSur7dq4 and RemnantModel accurately predict waveforms and remnant properties for precessing unequal-mass binary black holes up to q=4, outperforming existing models by an order of magnitude.
Binary black hole signals in GWTC-1 are consistent with general relativity predictions, with an improved graviton mass bound of mg ≤ 4.7 × 10^{-23} eV/c² at 90% credible level.
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
Two asymmetric BBH mergers are characterized with mass ratios 0.35 and ≤0.20; one shows high spins, negative χ_eff, and strong precession, suggesting an emerging population of massive rapidly spinning systems.
citing papers explorer
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Merger remnant and eccentricity dynamics surrogates for eccentric nonspinning black hole binaries
Two new surrogate models, trained on NR simulations, predict remnant properties and eccentricity dynamics for nonspinning eccentric black hole binaries with q ≤ 4 and e < 0.23.
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Learning Post-Newtonian Corrections from Numerical Relativity
A PINN learns higher-order corrections to the TaylorT4 PN model from eight NR surrogate waveforms, reducing phase and amplitude errors in the inspiral while enforcing physical symmetries.
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Gravitational wave surrogate model for spinning, intermediate mass ratio binaries based on perturbation theory and numerical relativity
BHPTNRSur2dq1e3 is a new surrogate model for spinning intermediate-mass-ratio black hole binary gravitational waves, constructed from ppBHPT training data with domain decomposition for retrograde modes and calibrated to NR simulations.
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Surrogate models for precessing binary black hole simulations with unequal masses
New surrogate models NRSur7dq4 and RemnantModel accurately predict waveforms and remnant properties for precessing unequal-mass binary black holes up to q=4, outperforming existing models by an order of magnitude.
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Tests of General Relativity with the Binary Black Hole Signals from the LIGO-Virgo Catalog GWTC-1
Binary black hole signals in GWTC-1 are consistent with general relativity predictions, with an improved graviton mass bound of mg ≤ 4.7 × 10^{-23} eV/c² at 90% credible level.
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Fast neural network surrogate for multimodal effective-one-body gravitational waveforms from generically precessing compact binaries
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
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GW190711_030756 and GW200114_020818: astrophysical interpretation of two asymmetric binary black hole mergers in the IAS catalog
Two asymmetric BBH mergers are characterized with mass ratios 0.35 and ≤0.20; one shows high spins, negative χ_eff, and strong precession, suggesting an emerging population of massive rapidly spinning systems.