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Veitch et al

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23 Pith papers citing it
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abstract

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star, a neutron star black hole binary and a binary black hole, where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence parameter space.

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representative citing papers

Testing the no-hair theorem with GW150914

gr-qc · 2019-05-02 · unverdicted · novelty 6.0

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.

GW231123: Overlapping Gravitational Wave Signals?

gr-qc · 2025-12-19 · conditional · novelty 5.0

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.

The Impact of Spin Priors on Parameterized Tests of General Relativity

gr-qc · 2026-05-06 · unverdicted · novelty 5.0

Spin prior choices propagate into tests of GR via the 1.5PN deviation parameter δφ̂3 in a non-trivial, event-dependent way, with stronger effects for short-inspiral events and partial degeneracy with χ_eff when the deviation is included.

Tests of General Relativity with GWTC-3

gr-qc · 2021-12-13 · accept · novelty 3.0

No evidence for physics beyond general relativity is found in the analysis of 15 GW events from GWTC-3, with consistency in residuals, PN parameters, and remnant properties.

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