Koopman Autoencoder Architecture for Current Density Modeling in Kinetic Plasma Simulations

We present a reduced-order model (ROM) based on Koopman autoencoder architecture for prediction of current density in kinetic plasma simulations. We apply the proposed method to forecast the time evolution of the current density derived from high-fidelity electromagnetic particle-in-cell (EMPIC) simulation based on the Maxwell- Vlasov system of equations. We test the Koopman auto encoder architecture for a two-dimensional oscillating electron beam inside a square cavity. Such analysis can be crucial in modeling of complex nonlinear plasma system as well as expediting time-consuming particle-in-cell simulations.