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We present a data-driven reduced-order modeling of the space-charge dynamicsfor electromagnetic particle-in-cell (EMPIC) plasma simulations based ondynamic mode decomposition (DMD). The dynamics of the charged particles inkinetic plasma simulations such as EMPIC is manifested through the plasmacurrent density defined on the edges of the spatial mesh. We showcase theefficacy of DMD in modeling the time evolution of current density through alow-dimensional feature space. Not only do such DMD-based predictivereduced-order models help accelerate EMPIC simulations, they also have thepotential to facilitate investigative analysis and control applications. Wedemonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of currentdensity, and speed-up in EMPIC simulations involving electron beams under theinfluence of magnetic fields and virtual cathode oscillations.

Accelerating Particle-in-Cell Kinetic Plasma Simulations via Reduced-Order Modeling of Space-Charge Dynamics using Dynamic Mode Decomposition