Logarithmic aging phenomena are prevalent in various systems, including electronic materials and biological structures. This study utilizes a generalized continuous time random walk (CTRW) framework to investigate the mechanisms behind the logarithmic aging phenomena. By incorporating non-Markovian jump processes with significant memory effects, we modify traditional diffusion models to exhibit logarithmic decay in both survival and return probabilities. In addition, we analyze the impact of aging on autocorrelation functions, illustrating how long-term memory behaviors affect the temporal evolution of physical properties. These results connect microscopic models to macroscopic manifestations in real-world systems, advancing the understanding of ultraslow dynamics in disordered systems.

生成讲解博客的中文版本

生成AI智能校验的中文版本