LIGO

Modeling precessing binary black hole waveforms with machine learning

I discuss a novel machine learning model for gravitational waves from precessing binary black holes.

Incorporating waveform uncertainty into modeling and inference of GWs

I discuss how systematic errors in waveform models can affect parameter inference and how these errors can be incorporated into the waveform model construction.

Regression methods in waveform modeling: a comparative study

I give a comparison of classical and machine learning methods for regression of gravitational wave data.

Properties and Astrophysical Implications of the 150 Msun Binary Black Hole Merger GW190521

Aligned-spin neutron-star-black-hole waveform model based on the effective-one-body approach and numerical-relativity simulations

Multipolar effective-one-body waveforms for precessing binary black holes: Construction and validation

Frequency-domain reduced-order model of aligned-spin effective-one-body waveforms with higher-order modes

Gravitational waveform accuracy requirements for future ground-based detectors

We assess how accurate models of gravitations waves should be to avoid systematic errors in the measurement of the binaries' parameters.