New surrogate models predict remnant properties and eccentricity dynamics for eccentric nonspinning black hole binary mergers using numerical relativity data over a limited parameter space.
A Surrogate Model of Gravitational Waveforms from Numerical Relativity Simulations of Pre- cessing Binary Black Hole Mergers
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
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
-
Merger remnant and eccentricity dynamics surrogates for eccentric nonspinning black hole binaries
New surrogate models predict remnant properties and eccentricity dynamics for eccentric nonspinning black hole binary mergers using numerical relativity data over a limited parameter space.
-
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.
-
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.