The first informative astrophysical calibration of gravitational-wave detectors is reported using GW240925 and GW250207.
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11 Pith papers cite this work. Polarity classification is still indexing.
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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.
GW250114 data constrains GR deviations in merger amplitude to 10% and frequency to 4% at 90% CL, with first bounds on the (4,4) mode frequency at 6%.
GW250114 data confirm the remnant is consistent with a Kerr black hole and bound the dominant quadrupolar mode frequency to within a few percent of the GR prediction, with constraints tighter than prior multi-event catalogs.
Hierarchical Bayesian inference on GWTC-5.0 constrains the memory enhancement factor to 0.26 with large uncertainties consistent with the GR value of 1 and forecasts that 2000 detections are needed for a 1σ constraint away from zero.
GW231123 data favors an overlapping two-signal model over a single merger with Bayes factors of 100-10000, mitigating waveform-dependent discrepancies and suggesting possible gravitational lensing.
GW250114 data confirm the remnant black hole ringdown frequencies lie within 30% of Kerr predictions and that the final horizon area is larger than the sum of the progenitors' areas to high credibility.
Compactness inference on GWTC-3 events confirms consistency with binary black hole sources after frequency-cut diagnostics show low-compactness modes are noise artifacts.
The high mass and high spin magnitudes inferred for GW231123 using NRSur7dq4 are robust to waveform systematics and Gaussian noise.
Extended-data Bayesian reanalysis of GW190814 finds no evidence for tertiary-induced line-of-sight acceleration or residual eccentricity due to strong degeneracy between the two effects.
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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.