  A dynamic mode decomposition (DMD) based reduced-order model (ROM) is
developed for tracking, detection, and prediction of kinetic plasma behavior.
DMD is applied to the high-fidelity kinetic plasma model based on the
electromagnetic particle-in-cell (EMPIC) algorithm to extract the underlying
dynamics and key features of the model. In particular, the ability of DMD to
reconstruct the spatial pattern of the self electric field from high-fidelity
data and the effect of DMD extrapolated self-fields on charged particle
dynamics are investigated. An in-line sliding-window DMD method is presented
for identifying the transition from transient to equilibrium state based on the
loci of DMD eigenvalues in the complex plane. The in-line detection of
equilibrium state combined with time extrapolation ability of DMD has the
potential to effectively expedite the simulation. Case studies involving
electron beams and plasma ball are presented to assess the strengths and
limitations of the proposed method.
