Dynamical dark energy imprints O(1) shifts on black hole quasi-normal modes via cosmological hair, enabling constraints at 10^{-2} (LVK) to 10^{-4} (LISA) precision using the cubic Galileon as example.
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High-accuracy mass, spin, and recoil predictions of generic black-hole merger remnants
Mixed citation behavior. Most common role is background (67%).
13
Pith papers citing it
Background
67% of classified citations
abstract
We present accurate fits for the remnant properties of generically precessing binary black holes, trained on large banks of numerical-relativity simulations. We use Gaussian process regression to interpolate the remnant mass, spin, and recoil velocity in the 7-dimensional parameter space of precessing black-hole binaries with mass ratios $q\leq2$, and spin magnitudes $\chi_1,\chi_2\leq0.8$. For precessing systems, our errors in estimating the remnant mass, spin magnitude, and kick magnitude are lower than those of existing fitting formulae by at least an order of magnitude (improvement is also reported in the extrapolated region at high mass ratios and spins). In addition, we also model the remnant spin and kick directions. Being trained directly on precessing simulations, our fits are free from ambiguities regarding the initial frequency at which precessing quantities are defined. We also construct a model for remnant properties of aligned-spin systems with mass ratios $q\leq8$, and spin magnitudes $\chi_1,\chi_2\leq0.8$. As a byproduct, we also provide error estimates for all fitted quantities, which can be consistently incorporated into current and future gravitational-wave parameter-estimation analyses. Our model(s) are made publicly available through a fast and easy-to-use Python module called surfinBH.
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representative citing papers
Numerical study of cusp formation on horizons in head-on non-spinning black hole mergers, with analysis of mass and multipole behavior at the cusp and a proposed phenomenological model.
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.
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.
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
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.
Ringdown analysis of GW150914 with overtones measures remnant mass and spin consistent with a Kerr black hole, supporting the no-hair theorem at the 10% level.
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
IMRPhenomXPHM is a new computationally efficient phenomenological model for precessing binary black hole gravitational-wave signals that incorporates higher-order modes via twisting-up maps from non-precessing waveforms.
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.
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.
The paper evaluates how triangular versus two-L-shaped geometries, arm lengths, and presence of low-frequency instruments affect the science reach of the Einstein Telescope for compact binaries, multi-messenger events, and stochastic backgrounds.
citing papers explorer
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Testing Dark Energy with Black Hole Ringdown
Dynamical dark energy imprints O(1) shifts on black hole quasi-normal modes via cosmological hair, enabling constraints at 10^{-2} (LVK) to 10^{-4} (LISA) precision using the cubic Galileon as example.
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Cusp Formation in Merging Black Hole Horizons
Numerical study of cusp formation on horizons in head-on non-spinning black hole mergers, with analysis of mass and multipole behavior at the cusp and a proposed phenomenological model.
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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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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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Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least one of 57 events is eccentric under an astrophysically motivated rate prior.
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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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Testing the no-hair theorem with GW150914
Ringdown analysis of GW150914 with overtones measures remnant mass and spin consistent with a Kerr black hole, supporting the no-hair theorem at the 10% 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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Computationally efficient models for the dominant and sub-dominant harmonic modes of precessing binary black holes
IMRPhenomXPHM is a new computationally efficient phenomenological model for precessing binary black hole gravitational-wave signals that incorporates higher-order modes via twisting-up maps from non-precessing waveforms.
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Biased parameter inference of eccentric, spin-precessing binary black holes
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.
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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.
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Science with the Einstein Telescope: a comparison of different designs
The paper evaluates how triangular versus two-L-shaped geometries, arm lengths, and presence of low-frequency instruments affect the science reach of the Einstein Telescope for compact binaries, multi-messenger events, and stochastic backgrounds.
- Recoil kicks from binary black hole mergers in GWTC catalogs: implications for retention and hierarchical mergers