Exploration and aging of non-Markovian processes
Julien Br\'emont

TL;DR
This thesis investigates how memory influences space exploration in non-Markovian random walks, revealing universal patterns, phase transitions, and exact results across various models, advancing understanding of memory effects in stochastic processes.
Contribution
It introduces a unified framework for memory effects in non-Markovian walks and provides the first exact results for aged observables in several models.
Findings
Identification of confinement criteria and phase transition in LARWs
Exact expressions for observables in SIRWs, including aging effects
Derivation of the first exact aged observable in TSAW
Abstract
This thesis explores a central question: how does memory affect the way random walkers explore space? By analyzing various non-Markovian models, where past behavior directly influences future dynamics, we uncover new mechanisms and universal patterns in space exploration. In the first part, we study Locally Activated Random Walks (LARWs), where motion depends on the time spent at visited sites. These walks, though simply defined, display rich behaviors such as dynamical trapping, aging, and non-Gaussian diffusion. We identify confinement criteria, reveal a dynamical phase transition, and derive exact analytical results in several regimes. The second part focuses on Self-Interacting Random Walks (SIRWs), where the walker's own history governs future steps. Using advanced probabilistic tools, especially Ray-Knight theory, we compute exact results for observables such as splitting…
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Taxonomy
TopicsDiffusion and Search Dynamics · stochastic dynamics and bifurcation · Space Science and Extraterrestrial Life
