Fast rare events in exit times distributions of jump processes

TL;DR

This paper develops a general method to estimate the impact of fast rare events on exit probabilities in jump processes with broad-tailed distributions, revealing their significant contribution to system behavior.

Contribution

The authors introduce a novel approach for quantifying fast rare events in exit times of jump processes with fat-tailed distributions, applicable across various fields.

Findings

Derived exact scaling functions for fast rare event probabilities.

Showed fast events significantly influence exit probabilities.

Validated results with extensive numerical simulations.

Abstract

Rare events in the first-passage distributions of jump processes are capable of triggering anomalous reactions or series of events. Estimating their probability is particularly important when the jump probabilities have broad-tailed distributions, and rare events are therefore not so rare. We formulate a general approach for estimating the contribution of fast rare events to the exit probabilities in the presence of fat tailed distributions. Using this approach, we study three jump processes that are used to model a wide class of phenomena ranging from biology to transport in disordered systems, ecology and finance: discrete time random-walks, L\'evy walks and the L\'evy-Lorentz gas. We determine the exact form of the scaling function for the probability distribution of fast rare events, in which the jump process exits from an interval in a very short time at a large distance opposite to the starting point. In particular, we show that events occurring on time scales orders of magnitude smaller than the typical time scale of the process can make a significant contribution to the exit probability. Our results are confirmed by extensive numerical simulations.