Synchronization of neuromorphic memristive Josephson junction network and its application

doi:10.1088/1674-1056/ae1456

Abstract Neuromorphic circuits based on superconducting tunnel junctions have attracted much attention due to their high-speed computing capabilities and low energy consumption. Josephson junction circuits can effectively mimic biological neural dynamics. Leveraging these advantages, we construct a Josephson junction neuron-like model with a phase-dependent dissipative current, referred to as a memristive current. The proposed memristive Josephson junction model exhibits complex dynamical behaviors. Furthermore, considering the effect of a fast-modulated synapse, we explore synchronization phenomena in coupled networks under varying coupling conductances and excitatory/inhibitory interactions. Finally, we extend the neuromorphic Josephson junction model—exhibiting complex dynamics—to the field of image encryption. These results not only enrich the understanding of the dynamical characteristics of memristive Josephson junctions but also provide a theoretical basis and technical support for the development of new neural networks and their applications in information security technology.

Keywords: nonlinear dynamics memristive Josephson junction synchronization image encryption

Received: 12 September 2025
Revised: 14 October 2025
Accepted manuscript online: 17 October 2025

PACS:	05.45.Pq	(Numerical simulations of chaotic systems)
	05.45.Gg	(Control of chaos, applications of chaos)
	05.45.Xt	(Synchronization; coupled oscillators)

Fund: The authors sincerely thank the editor, anonymous reviewers, and Huimin Qi for their valuable comments and suggestions that greatly improved this work. This research was supported by the National Natural Science Foundation of China (Grant No. 12302070), the Natural Science Foundation of Ningxia (Grant No. 2024AAC05002), the Youth Science and Technology Talent Cultivation Project of Ningxia, and the Ningxia Science and Technology Leading Talent Training Program (Grant No. 2022GKLRLX04).

Corresponding Authors: Fuqiang Wu
E-mail: alexwutian@nxu.edu.cn

Cite this article:

Dejun Yan(严德军), Fuqiang Wu(吴富强), and Wenshuai Wang(汪文帅) Synchronization of neuromorphic memristive Josephson junction network and its application 2026 Chin. Phys. B 35 010505

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Synchronization of neuromorphic memristive Josephson junction network and its application

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