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arXiv · 2109.14660

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

F. Terragni·L. L. Bonilla·J. M. Vega
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Abstract

Time periodic patterns in a semiconductor superlattice, relevant to microwave generation, are obtained upon numerical integration of a known set of drift-diffusion equations. The associated spatio-temporal transport mechanisms are uncovered by applying (to the computed data) two recent data processing tools, known as the higher order dynamic mode decomposition and the spatio-temporal Koopman decomposition. Outcomes include a clear identification of the asymptotic self-sustained oscillations of the current density (isolated from the transient dynamics) and an accurate description of the electric field traveling pulse in terms of its dispersion diagram. In addition, a preliminary version of a novel data-driven reduced order model is constructed, which allows for extremely fast online simulations of the system response over a range of different configurations.

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F. Terragni, L. L. Bonilla, J. M. Vega. 2021-09-24. Uncovering spatio-temporal patterns in semiconductor superlattices by efficient data processing tools. https://doi.org/10.1103/physreve.104.035303

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