Transition dynamics in aging systems: microscopic origin of logarithmic time evolution

TL;DR

This paper introduces a generic transition process model based on non-renewal, aging waiting times that explains the logarithmic slow time evolution observed in aging systems, bridging aging and non-aging behaviors.

Contribution

It presents a universal model for transition dynamics in complex systems with aging, capturing different growth regimes based on waiting time distributions.

Findings

Logarithmic time evolution for power-law waiting times with 0<α<1

Normal linear growth for α>2

Power-law growth for 1<α<2

Abstract

There exists compelling experimental evidence in numerous systems for logarithmically slow time evolution, yet its theoretical understanding remains elusive. We here introduce and study a generic transition process in complex systems, based on non-renewal, aging waiting times. Each state n of the system follows a local clock initiated at t=0. The random time \tau between clock ticks follows the waiting time density \psi(\tau). Transitions between states occur only at local clock ticks and are hence triggered by the local forward waiting time, rather than by \psi(\tau). For power-law forms \psi(\tau) ~ \tau^{-1-\alpha} (0<\alpha<1) we obtain a logarithmic time evolution of the state number <n(t)> ~ log(t/t_0), while for \alpha>2 the process becomes normal in the sense that <n(t)> ~ t. In the intermediate range 1<\alpha<2 we find the power-law growth <n(t)> ~ t^{\alpha-1}. Our model provides a universal description for transition dynamics between aging and non-aging states.