# Monotonicity of average return probabilities for random walks in random environments

## TL;DR

This paper generalizes a result on the monotonicity of average return probabilities for random walks from finite graphs to infinite random graphs under certain conditions, extending Lyons' 2016 work.

## Contribution

It introduces a new framework for analyzing return probabilities in infinite random graphs with percolation subgraphs, broadening the scope of previous finite graph results.

## Key findings

- Establishes a monotonicity inequality for average return probabilities in infinite random graphs.
- Extends Lyons' 2016 finite graph result to a more general infinite graph setting.
- Provides conditions under which the expected return probability of the original graph bounds that of the percolation subgraph.

## Abstract

We extend a result of Lyons (2016) from fractional tiling of finite graphs to a version for infinite random graphs. The most general result is as follows. Let $\bf P$ be a unimodular probability measure on rooted networks $(G, o)$ with positive weights $w_G$ on its edges and with a percolation subgraph $H$ of $G$ with positive weights $w_H$ on its edges. Let ${\bf P}_{(G, o)}$ denote the conditional law of $H$ given $(G, o)$. Assume that $\alpha := {\bf P}_{(G, o)}\bigl[{o \in V(H)}\bigr] > 0$ is a constant $\bf P$-a.s. We show that if $\bf P$-a.s. whenever $e \in E(G)$ is adjacent to $o$, \[ {\bf E}_{(G, o)}\bigl[{w_H(e) \bigm| e \in E(H)}\bigr] {\bf P}_{(G, o)}\bigl[{e \in E(H) \bigm| o\in V(H)}\bigr] \le w_G(e) \,, \] then \[ \forall t > 0 \quad {\bf E}\bigl[{p_t(o; G)}\bigr] \le {\bf E}\bigl[{p_t(o; H) \bigm| o \in V(H)}\bigr] \,. \]