Uncovering spatiotemporal patterns in semiconductor superlattices by efficient data processing tools

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 spatiotemporal 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 spatiotemporal 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 data-driven reduced order model is constructed, which allows for extremely fast online simulations of the system response over a range of different configurations.

Adaptive Signal Modulation Evolved by the Inherent Nonlinearity of Phase-Change Quantum-Dot String

“…It has been widely proven experimentally and theoretically, including charge carrier dynamics of microstructure devices, , particle tunneling through double barriers assisted by white noise or a periodic square pulses, , machine fault detection, and dynamic behavior of neurons. , Scientists make their great efforts to use the SR via semiconductor superlattices (SSLs) to simulate neural spike firing, ,, because the particle tunneling through SSLs is also event-driven suitable for signal encoding. ,,, The SSL normally comprises multiple epitaxy layers. The key parameters of energy band configuration is the alternative potential barriers and wells, which determine sequential tunneling electron transport (STET) mechanism, and control excitation behaviors in response to signals. ,− However, the SSL device encounters a significant challenge owing to its limited application in generating random numbers, which is that the excited spike series is usually aperiodic at room temperature. This cannot satisfy the requirement of manipulating signals precisely and maximizing the signal-to-noise ratio ( SNR ).…”