  We demonstrate the application of the Dynamic Mode Decomposition (DMD) for
the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in
resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal
matrix decomposition that correlates spatial features of computational or
experimental data while simultaneously associating the spatial activity with
periodic temporal behavior. DMD can produce low-rank, reduced order surrogate
models that can be used to reconstruct the state of the system and produce
high-fidelity future state predictions. This allows for a reduction in the
computational cost, and, at the same time, accurate approximations of the
problem, even if the data are sparsely sampled. We demonstrate the use of the
method on both numerical and experimental data, showing that it is a successful
mathematical architecture for characterizing the HIT-IS magnetohydrodynamics.
Importantly, the DMD decomposition produces interpretable, dominant mode
structures, including the spheromak mode and a pair of injector-driven modes.
In combination, the 3-mode DMD model produces excellent dynamic reconstructions
that can be used for future state prediction and/or control strategies.
