Efficient Computation of Multidimensional Phase-Space Flows using Time-Discrete Implicit Runge-Kutta Physics-Informed Neural Networks

The authors present a computational framework for efficiently obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations using high-order implicit Runge-Kutta Physics-Informed Neural Networks (IRK-PINNs).