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 have an excellent capacity to mimic biological neural dynamics. Based on the capacity and advantage, 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 can present complex dynamic behaviors. Furthermore, considering the effect of a fast-modulated synapse, we explore synchronization phenomena in the coupled network under the influence of different coupling conductance and excitatory/inhibitory effects. Finally, the neuromorphic Josephson junction model, which exhibits complex dynamic behavior, is extended to the field of image encryption. The obtained results can not only enrich the understanding of the dynamic 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.