Comparing Physics-Informed and Physics-Enforced Neural Networks for the Chaotic Three-Body Problem
The three-body gravitational problem is a canonical benchmark for chaotic dynamical systems, admitting no general closed-form solution and exhibiting sensitive dependence on initial conditions. We present a controlled comparative benchmark of four neural network architectures - a Deep Neural Network (DNN), a Physics-In...