  Let $G=(V,E)$ be a simple, connected graph. One is often interested in a
short path between two vertices $u,v$. We propose a spectral algorithm:
construct the function $\phi:V \rightarrow \mathbb{R}_{\geq 0}$ $$ \phi =
\arg\min_{f:V \rightarrow \mathbb{R} \atop f(u) = 0, f \not\equiv 0}
\frac{\sum_{(w_1, w_2) \in E}{(f(w_1)-f(w_2))^2}}{\sum_{w \in V}{f(w)^2}}.$$
$\phi$ can also be understood as the smallest eigenvector of the Laplacian
Matrix $L=D-A$ after the $u-$th row and column have been removed. We start in
the point $v$ and construct a path from $v$ to $u$: at each step, we move to
the neighbor for which $\phi$ is the smallest. This algorithm provably
terminates and results in a short path from $v$ to $u$, often the shortest. The
efficiency of this method is due to a discrete analogue of a phenomenon in
Partial Differential Equations that is not well understood. We prove optimality
for trees and discuss a number of open questions.
