A new gravitational wave event reveals a binary black hole merger with total mass 190-265 solar masses, indicating black holes can form via gravitational-wave driven mergers beyond standard stellar channels.
Searching for Gravitational Waves from Compact Binaries with Precessing Spins
10 Pith papers cite this work. Polarity classification is still indexing.
10
Pith papers citing it
abstract
Current searches for gravitational waves from compact-object binaries with the LIGO and Virgo observatories employ waveform models with spins aligned (or anti-aligned) with the orbital angular momentum. Here, we derive a new statistic to search for compact objects carrying generic (precessing) spins. Applying this statistic, we construct banks of both aligned- and generic-spin templates for binary black holes and neutron-star--black-hole binaries, and compare the effectualness of these banks towards simulated populations of generic-spin systems. We then use these banks in a pipeline analysis of Gaussian noise to measure the increase in background incurred by using generic- instead of aligned-spin banks. Although the generic-spin banks have a factor of ten to twenty more templates than the aligned-spin banks, we find an overall improvement in signal recovery at fixed false-alarm rate for systems with high-mass ratio and highly precessing spins ---up to 60\% for neutron-star--black-hole mergers. This gain in sensitivity comes at a small loss of sensitivity ($\lesssim$4\%) for systems that are already well-covered by aligned-spin templates. Since the observation of even a single binary merger with misalinged spins could provide unique astrophysical insights into the formation of these sources, we recommend that the method described here be developed further to mount a viable search for generic-spin binary mergers in LIGO/Virgo data.
citation-role summary
background 2
method 1
citation-polarity summary
representative citing papers
A new harmonic-decomposition template search for precessing binary black holes in LIGO O3 data improves sensitivity by up to 28% and reduces computational cost by up to 5x with no new detections.
A mixture-model framework for combining gravitational-wave tests of General Relativity yields Bayes factors of 10-20 favoring GR, substantially lower than existing methods that assume uniform deviations across events.
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
Neural network surrogate approximates precessing compact binary gravitational waveforms up to 1000x faster than the base EOB model with validated accuracy.
A time-frequency semi-coherent search pipeline detects stellar-mass BBH inspirals in LISA data down to coherent SNR of approximately 11-14 on the Yorsh data challenge for aligned-spin, low-eccentricity systems.
Reanalysis of flagged LVK events with waveform uncertainty models produces consistent spin and precession inferences across raw/deglitched data and multiple waveform approximants.
citing papers explorer
-
GW231123: a Binary Black Hole Merger with Total Mass 190-265 $M_{\odot}$
A new gravitational wave event reveals a binary black hole merger with total mass 190-265 solar masses, indicating black holes can form via gravitational-wave driven mergers beyond standard stellar channels.
-
Search for Precessing Binary Black Holes in Advanced LIGO's Third Observing Run using Harmonic Decomposition
A new harmonic-decomposition template search for precessing binary black holes in LIGO O3 data improves sensitivity by up to 28% and reduces computational cost by up to 5x with no new detections.
-
Testing General Relativity with GWTC-4.0 through mixture models
A mixture-model framework for combining gravitational-wave tests of General Relativity yields Bayes factors of 10-20 favoring GR, substantially lower than existing methods that assume uniform deviations across events.
-
A Robust and Efficient F-statistic-based Framework for Consistent Bayesian Inference of Compact Binary Coalescences
F-statistic framework analytically maximizes over distance and polarization to enable faster Bayesian inference of compact binary coalescences with a new evidence formulation that matches full frequency-domain results at lower cost.
-
Parameter inference of millilensed gravitational waves using neural spline flows
Neural spline flows perform fast posterior inference on 11-dimensional millilensed GW parameters with accuracy comparable to dynesty for most quantities and a 3-day to 0.8-second speedup.
-
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.
-
Global time-frequency search for stellar-mass binary black holes in LISA
A time-frequency semi-coherent search pipeline detects stellar-mass BBH inspirals in LISA data down to coherent SNR of approximately 11-14 on the Yorsh data challenge for aligned-spin, low-eccentricity systems.
-
Mitigating Systematic Errors in Parameter Estimation of Binary Black Hole Mergers in O1-O3 LIGO-Virgo Data
Reanalysis of flagged LVK events with waveform uncertainty models produces consistent spin and precession inferences across raw/deglitched data and multiple waveform approximants.
- Horizon absorption in eccentric precessing binary black hole inspirals and its importance for gravitational wave data analysis
- Post-Newtonian inspiral waveform model for eccentric precessing binaries with higher-order modes and matter effects