Mixing Time of Random Walk on Poisson Geometry Small World

This paper focuses on the problem of modeling for small world effect on complex networks. Let’s consider the supercritical Poisson continuous percolation on \(d\)-dimensional torus \(T^d_n\) with volume \(n^d\). By adding “long edges (short cuts)” randomly to the largest percolation cluster, we obtain a random graph \(\mathscr G_n\). In the present paper, we first prove that the diameter of \(\mathscr G_n\) grows at most polynomially fast in \(\ln n\) and we call it the Poisson Geometry Small World. Secondly, we prove that the random walk on \(\mathscr G_n\) possesses the rapid mixing property, namely, the random walk mixes in time at most polynomially large in \(\ln n\).