Statistics of a Large Number of Renewals in Equilibrium and Non-Equilibrium Renewal Processes (2409.19966v2)

Abstract: The renewal process is a key statistical model for describing a wide range of stochastic systems in Physics. This work investigates the behavior of the probability distribution of the number of renewals in renewal processes in the short-time limit, with a focus on cases where the number of renewals is large. We find that the specific details of the sojourn time distribution $\phi(\tau)$ in this limit can significantly modify the behavior in the large-number-of-renewals regime. We explore both non-equilibrium and equilibrium renewal processes, deriving results for various forms of $\phi(\tau)$. Using saddle point approximations, we analyze cases where $\phi(\tau)$ follows a power-series expansion, includes a cutoff, or exhibits non-analytic behavior near $\tau = 0$. Additionally, we show how the short-time properties of $\phi(\tau)$ shape the decay of the number of renewals in equilibrium compared to non-equilibrium renewal processes. The probability of the number of renewals plays a crucial role in determining rare event behaviors, such as Laplace tails. The results obtained here are expected to help advance the development of a theoretical framework for rare events in transport processes in complex systems.