  For $\lambda>0$, we define a $\lambda$-damped random walk to be a random walk
that is started from a random vertex of a graph and stopped at each step with
probability $\frac{\lambda}{1+\lambda}$, otherwise continued with probability
$\frac{1}{1+\lambda}$. We use the Aldous-Broder algorithm (\cite{aldous,
broder}) of generating a random spanning tree and the Matrix-tree theorem to
relate the values of the characteristic polynomial of the Laplacian at $\pm
\lambda$ and the stationary measures of the sets of nodes visited by $i$
independent $\lambda$-damped random walks for $i \in \N$. As a corollary, we
obtain a new characterization of the non-zero eigenvalues of the Weighted Graph
Laplacian.
