Precession

Reconstruction of Binary Black Hole Harmonics in LIGO Using Deep Learning
We have developed a deep learning model, AWaRe, that is capable of producing accurate reconstructions of gravitational wave signals from real LIGO data. We demonstrate that the model is robust against complex waveform systematics like precession and the presence of higher multipoles.
Dr. Chayan Chatterjee, Karan Jani
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Reconstruction of Binary Black Hole Harmonics in LIGO Using Deep Learning