Learning orbital dynamics of binary black hole systems from gravitational wave measurements

Understand

We introduce a gravitational waveform inversion strategy that discovers mechanical models of binary black hole (BBH) systems.

• We show that only a single time series of (possibly noisy) waveform data is necessary to construct the equations of motion for a BBH system.
• Starting with a class of universal differential equations parameterized by feed-forward neural networks, our strategy involves the construction of a space of plausible mechanical models and a physics-informed constrained optimization within that space to minimize the waveform error.
• We apply our method to various BBH systems including extreme and comparable mass ratio systems in eccentric and non-eccentric orbits.