Self-interacting random walks : aging, exploration and first-passage times
Alex Barbier--Chebbah, Olivier Benichou, Raphael Voituriez

TL;DR
This paper investigates how long-range memory effects in self-interacting random walks influence their aging, exploration, and first-passage times, revealing universal scaling laws and the impact of attractive or repulsive interactions on search efficiency.
Contribution
It provides a quantitative analysis of aging, persistence, and transience exponents in non Markovian self-interacting random walks, and characterizes the universal scaling of first-passage times.
Findings
Memory effects induce aging and non-trivial exponents.
First-passage time distributions follow universal scaling laws.
Attractive interactions enhance local exploration, repulsive interactions accelerate global exploration.
Abstract
Self-interacting random walks are endowed with long range memory effects that emerge from the interaction of the random walker at time with the territory that it has visited at earlier times . This class of non Markovian random walks has applications in a broad range of examples, ranging from insects to living cells, where a random walker modifies locally its environment -- leaving behind footprints along its path, and in turn responds to its own footprints. Because of their inherent non Markovian nature, the exploration properties of self-interacting random walks have remained elusive. Here we show that long range memory effects can have deep consequences on the dynamics of generic self-interacting random walks ; they can induce aging and non trivial persistence and transience exponents, which we determine quantitatively, in both infinite and confined geometries. Based on…
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Taxonomy
TopicsDiffusion and Search Dynamics · Insect and Arachnid Ecology and Behavior
