  We considered diffusion-driven processes on small-world networks with
distance-dependent random links. The study of diffusion on such networks is
motivated by transport on randomly folded polymer chains, synchronization
problems in task-completion networks, and gradient driven transport on
networks. Changing the parameters of the distance-dependence, we found a rich
phase diagram, with different transient and recurrent phases in the context of
random walks on networks. We performed the calculations in two limiting cases:
in the annealed case, where the rearrangement of the random links is fast, and
in the quenched case, where the link rearrangement is slow compared to the
motion of the random walker or the surface. It has been well-established that
in a large class of interacting systems, adding an arbitrarily small density
of, possibly long-range, quenched random links to a regular lattice interaction
topology, will give rise to mean-field (or annealed) like behavior. In some
cases, however, mean-field scaling breaks down, such as in diffusion or in the
Edwards-Wilkinson process in "low-dimensional" small-world networks. This
break-down can be understood by treating the random links perturbatively, where
the mean-field (or annealed) prediction appears as the lowest-order term of a
naive perturbation expansion. The asymptotic analytic results are also
confirmed numerically by employing exact numerical diagonalization of the
network Laplacian. Further, we construct a finite-size scaling framework for
the relevant observables, capturing the cross-over behaviors in finite
networks. This work provides a detailed account of the
self-consistent-perturbative and renormalization approaches briefly introduced
in two earlier short reports.
