Dynamics of memristive circuit driven by Josephson junction

Abstract The nonlinear circuit with charge-controlled memristor (CCM) can capture the external electric field effect. The nonlinear circuit with Josephson junction (JJ) can estimate the external magnetic field effect. Therefore, we propose an enhanced functional circuit by connecting a CCM and a JJ into a simple RLC nonlinear circuit. This enchanced circuit can estimate the external electromagnetic fields concurrently. The dynamical equations of the new memristive circuit and its Hamilton energy function are obtained by using the Kirchhoff’s law and the Helmholtz’s theorem. Furthermore, the complex dynamics of memristive circuit are investigated by applying bifurcation diagrams, Lyapunov exponents and time sampled series. The simulation experiment results indicate that the electromagnetic field has a great influence on complex dynamics of memristive circuit. In fact, this new nonlinear circuit is also a functional neural circuit, and it can be used to study the collective dynamic of functional neural network under the condition of an external electromagnetic fields.

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Publication Details

Journal
Physica Scripta
Published
2024-09-02
DOI
https://doi.org/10.1088/1402-4896/ad7650
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.83

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article

Dynamics of memristive circuit driven by Josephson junction

Peng Fei Liu, Fangfang Zhang, Cuimei Jiang, Xuejing Gu et al.
4 citations
Physica Scripta
Advanced Memory and Neural Computing
0.83
article

Dynamics of memristive circuit driven by Josephson junction

Peng Fei Liu, Fangfang Zhang, Cuimei Jiang, Xuejing Gu, Jian Liu
article en
4 citations

Abstract

Abstract The nonlinear circuit with charge-controlled memristor (CCM) can capture the external electric field effect. The nonlinear circuit with Josephson junction (JJ) can estimate the external magnetic field effect. Therefore, we propose an enhanced functional circuit by connecting a CCM and a JJ into a simple RLC nonlinear circuit. This enchanced circuit can estimate the external electromagnetic fields concurrently. The dynamical equations of the new memristive circuit and its Hamilton energy function are obtained by using the Kirchhoff’s law and the Helmholtz’s theorem. Furthermore, the complex dynamics of memristive circuit are investigated by applying bifurcation diagrams, Lyapunov exponents and time sampled series. The simulation experiment results indicate that the electromagnetic field has a great influence on complex dynamics of memristive circuit. In fact, this new nonlinear circuit is also a functional neural circuit, and it can be used to study the collective dynamic of functional neural network under the condition of an external electromagnetic fields.

Physica ScriptaVol. 99(10)
Qilu University of Technology (CN), University of Jinan (CN), Shandong Academy of Sciences (CN)
Natural Science Foundation of Shandong Province
Affordable and clean energy
Openalex Percentile: Top 27%
Advanced Memory and Neural Computing
0.83
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