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Time periodic patterns in a semiconductor superlattice, relevant to microwavegeneration, are obtained upon numerical integration of a known set ofdrift-diffusion equations. The associated spatio-temporal transport mechanismsare uncovered by applying (to the computed data) two recent data processingtools, known as the higher order dynamic mode decomposition and thespatio-temporal Koopman decomposition. Outcomes include a clear identificationof the asymptotic self-sustained oscillations of the current density (isolatedfrom the transient dynamics) and an accurate description of the electric fieldtraveling pulse in terms of its dispersion diagram. In addition, a preliminaryversion of a novel data-driven reduced order model is constructed, which allowsfor extremely fast online simulations of the system response over a range ofdifferent configurations.

Uncovering spatio-temporal patterns in semiconductor superlattices by efficient data processing tools