Waveform Reconstruction

Navigating Unknowns: Deep Learning Robustness for Gravitational Wave Signal Reconstruction
We extend the work in Chatterjee & Jani, 2024 and demonstrate that AWaRe can be used to estimate gravitational wave reconstruction uncertainties. We further show that the uncertainties capture waveform systematics the model has not been trained on, including intermediate mass black holes and eccentricity.
Dr. Chayan Chatterjee, Karan Jani
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Navigating Unknowns: Deep Learning Robustness for Gravitational Wave Signal Reconstruction
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