New frequency-domain models IMRPhenomXHM_NSBH, SEOBNRv5HM_ROM_NRTidalv3_NSBH, and IMRPhenomXPHM_NSBH bring higher-order modes and tidal effects to fast NSBH waveform templates.
Morisaki, Phys
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Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
Hybrid SPA-plus-FFT frequency-domain version of SEOBNRv5THM for quasi-circular spin-aligned BNS systems matches time-domain baseline accuracy while cutting computational cost for long signals.
Relative binning accelerates TIGER parameterized GR tests by factors of 10-100 while recovering unbiased posteriors on simulated signals and real events like GW150914.
citing papers explorer
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Fast gravitational waveform models for quasi-circular coalescences of neutron star--black hole binaries
New frequency-domain models IMRPhenomXHM_NSBH, SEOBNRv5HM_ROM_NRTidalv3_NSBH, and IMRPhenomXPHM_NSBH bring higher-order modes and tidal effects to fast NSBH waveform templates.
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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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Speed and accuracy for long signals: Frequency-domain effective-one-body waveforms for compact binary coalescences
Hybrid SPA-plus-FFT frequency-domain version of SEOBNRv5THM for quasi-circular spin-aligned BNS systems matches time-domain baseline accuracy while cutting computational cost for long signals.
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Accelerating parameter estimation for parameterized tests of general relativity with gravitational-wave observations
Relative binning accelerates TIGER parameterized GR tests by factors of 10-100 while recovering unbiased posteriors on simulated signals and real events like GW150914.