Far Tails of the Positional Distribution in random walk: A Saddle-Point Approach

Abstract

Rare events and large-deviation theory have attracted considerable interest in the study of random walks. Here, we investigate the rare events of the positional distribution of continuous-time random walks under ordinary and equilibrium initial conditions using the saddle point method. We show that the far-tail behavior is sensitive to the expansion of the waiting-time distribution near its minimum value. For a general power-series expansion near the minimum waiting time, the positional distribution exhibits an approximately exponential decay in its far tails. In contrast, when the waiting-time distribution has a cutoff at its minimum value, the positional distribution exhibits an unexpected Gaussian decay, in contrast to the far-tail behavior of the renewal-count distribution. We further find that the most likely number of renewals required to reach a given position, as well as the associated rate functions, is insensitive to the initial conditions, whereas the far tails of the positional distribution retain a dependence on the initial conditions. Our results provide new insights into the rare-event statistics and large deviations of random walks.