From Continuous-Time Random Walks to Laplace Tails

Abstract

During Brownian motion, the displacement is normally distributed, a classical fact aligned with the central limit theorem. However, single particle tracking in complex media such as glasses, living cells, and colloidal suspensions often reveals pronounced exponential decay of the displacement distribution, known as Laplace tails. In a short letter, two of us presented the emergence of Laplace tails in the continuous time random walk (CTRW) framework. Here, a detailed complementary study is presented. By exploring the behavior of $Q_t(n)$, the probability that exactly $n$ renewals occur during time $t$, we develop a rate function-like framework for this quantity, valid for finite $t$. We show that $Q_t(n)$ exhibits exponential tails, which in turn give rise to exponential tails of the positional probability density function $P(x,t)$. Favorable comparison to finite-time numerical simulations and asymptotic large deviation rate functions establishes the validity of our results over a wide temporal range.