Gravitational waveform modeling with physics informed neural networks and surrogates

I will discuss a recent proof-of-concept waveform model (arxiv.org/abs/2511.10522) that augments post-Newtonian quations using ideas from physics-informed neural networks and universal differential equations. I will then discuss ongoing efforts to develop a precessing surrogate model that evaluates in under 1 millisecond and also covers more of the LVK band.