Abstract

Given a finite graph $G$, a vertex of the lamplighter graph $G^\diamondsuit=\mathbb {Z}_2 \wr G$ consists of a zero-one labeling of the vertices of $G$, and a marked vertex of $G$. For transitive $G$ we show that, up to constants, the relaxation time for simple random walk in $G^\diamondsuit$ is the maximal hitting time for simple random walk in $G$, while the mixing time in total variation on $G^\diamondsuit$ is the expected cover time on $G$. The mixing time in the uniform metric on $G^\diamondsuit$ admits a sharp threshold, and equals $|G|$ multiplied by the relaxation time on $G$, up to a factor of $\log |G|$. For $\mathbb {Z}_2 \wr \mathbb {Z}_n^2$, the lamplighter group over the discrete two dimensional torus, the relaxation time is of order $n^2 \log n$, the total variation mixing time is of order $n^2 \log^2 n$, and the uniform mixing time is of order $n^4$. For $\mathbb {Z}_2 \wr \mathbb {Z}_n^d$ when $d\geq 3$, the relaxation time is of order $n^d$, the total variation mixing time is of order $n^d \log n$, and the uniform mixing time is of order $n^{d+2}$. In particular, these three quantities are of different orders of magnitude.

Highlights

  • Given a finite graph G = (VG, EG), the wreath product G♦ = Z2 G is the graph whose vertices are ordered pairs (f, x), where x ∈ VG and f ∈ {0, 1}VG

  • (We recall the definitions of these mixing time parameters in (1)-(3).) The general correspondence between notions of mixing on G♦ and properties of random walk on G is indicated in the following table: underlying graph G

  • By Theorem 1.2, Trel(Z2 Zn2 ) is on the order of 2n, and Theorem 1.3 shows that the convergence time in total variation on Z2 Zn2 is on the order of n2n

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Summary

Introduction

Let {Gn} be a sequence of vertex transitive graphs with |Gn| → ∞, and Cn denote the cover time for simple random walk on Gn. For any > 0, there exist constants c1, c2 depending on such that the total variation mixing time satisfies (15). The uniform mixing time τ ( , G♦n ) has a sharp threshold in the sense that for all > 0, The intuition behind both Theorems 1.3 and 1.4 can be most explained by considering the case when Gn is the complete graph Kn, with a loop added at each vertex of Kn. The position π(Xt) of the lamplighter performs a simple random walk on Kn with holding probability 1/n, and every lamp that is visited is randomized. The upper and lower bounds of (17) are of the same order of magnitude and are accurate up to constants

More examples
Relaxation time bounds
Total variation mixing
Uniform mixing
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