# Poly-logarithmic localization for random walks among random obstacles

## TL;DR

This paper proves that in a high-dimensional lattice with randomly placed obstacles, a simple random walk conditioned on survival localizes in a region whose volume grows poly-logarithmically with time, improving understanding of localization phenomena.

## Contribution

It establishes poly-logarithmic volume localization for random walks among random obstacles, extending previous results from Brownian motion to discrete lattice settings.

## Key findings

- Random walk localizes in poly-logarithmic volume regions
- Localization occurs with probability tending to 1 as time increases
- Results hold for environments with percolation probability above critical threshold

## Abstract

Place an obstacle with probability $1-p$ independently at each vertex of $\mathbb Z^d$, and run a simple random walk until hitting one of the obstacles. For $d\geq 2$ and $p$ strictly above the critical threshold for site percolation, we condition on the environment where the origin is contained in an infinite connected component free of obstacles, and we show that the following \emph{path localization} holds for environments with probability tending to 1 as $n\to \infty$: conditioned on survival up to time $n$ we have that ever since $o(n)$ steps the simple random walk is localized in a region of volume poly-logarithmic in $n$ with probability tending to 1. The previous best result of this type went back to Sznitman (1996) on Brownian motion among Poisson obstacles, where a localization (only for the end point) in a region of volume $t^{o(1)}$ was derived conditioned on the survival of Brownian motion up to time $t$.