Synchronization of neuromorphic memristive Josephson junction network and its application

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.