  Given discrete degrees of freedom (spins) on a graph interacting via an
energy function, what can be said about the energy local minima and associated
inherent structures? Using the lid algorithm in the context of a spin glass
energy function, we investigate the properties of the energy landscape for a
variety of graph topologies. First, we find that the multiplicity Ns of the
inherent structures generically has a lognormal distribution. In addition, the
large volume limit of ln<Ns>/<lnNs> differs from unity, except for the
Sherrington-Kirkpatrick model. Second, we find simple scaling laws for the
growth of the height of the energy barrier between the two degenerate ground
states and the size of the associated valleys. For finite connectivity models,
changing the topology of the underlying graph does not modify qualitatively the
energy landscape, but at the quantitative level the models can differ
substantially.

Disordered Systems and Neural Networks