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Synchronization of chaos in semiconductor gas discharge model with local mean energy approximation

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  • Akhmet, Marat
  • Yeşil, Cihan
  • Başkan, Kağan

Abstract

The delta synchronization is a useful method to analyze appearance of chaotic synchronization in gas discharge systems. In recent studies, the generalized synchronization method has been implemented in various gas discharge systems. However, synchronization is not detected with this conventional method. In our previous study, we introduced the delta synchronization method and applied it to the gas discharge-semiconductor system (GDSS) via the one-dimensional ‘simple’ fluid model approach. In the present study, we implement this method in the more detailed (in terms of plasma chemical reactions and treatment of the electron transport) fluid model, namely the ‘extended’ fluid model or ‘local mean energy approximation’ model. The description of the GDSS model is given, and a bifurcation diagram demonstrates the system’s transition to the chaotic regime. The unpredictable motion, which proves the existence of Poincaré chaos, and the delta synchronized motion are confirmed by the numerical simulations, and corresponding algorithms are given. The time sequences corresponding to the unpredictability and delta synchronization are presented in tables. For consistency, the absence of generalized synchronization is also shown via the auxiliary system approach. The numerical characteristics indicating the degrees of chaos and synchronization are described and implemented in the analysis. These features are also used to compare our results to the simpler model.

Suggested Citation

  • Akhmet, Marat & Yeşil, Cihan & Başkan, Kağan, 2023. "Synchronization of chaos in semiconductor gas discharge model with local mean energy approximation," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077922012140
    DOI: 10.1016/j.chaos.2022.113035
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    Cited by:

    1. Akhmet, Marat & Tleubergenova, Madina & Zhamanshin, Akylbek, 2024. "Cohen-Grossberg neural networks with unpredictable and Poisson stable dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    2. Marat Akhmet & Madina Tleubergenova & Akylbek Zhamanshin, 2023. "Shunting Inhibitory Cellular Neural Networks with Compartmental Unpredictable Coefficients and Inputs," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    3. Marat Akhmet & Kağan Başkan & Cihan Yeşil, 2023. "Revealing Chaos Synchronization Below the Threshold in Coupled Mackey–Glass Systems," Mathematics, MDPI, vol. 11(14), pages 1-15, July.

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