Physics-Informed Neural Networks for Discovering Periodic Orbits in the Gravitational Three-Body Problem
Locating periodic solutions of chaotic dynamical systems normally requires an initial guess close enough to the target orbit for numerical continuation or gradient-based search to converge. We show that Physics-Informed Neural Networks (PINNs) trained on sparse, noisy observations \emph{without} initial conditions reco...