Vacuum Selection from Cosmology on Networks of String Geometries

We introduce  network science as a framework for studying the string landscape. Two large  networks of string geometries are constructed, where nodes are  extra-dimensional six-manifolds and edges represent topological transitions  between them. We show that a standard bubble cosmology model on the networks  has late-time behavior determined by the largest eigenvector of −(L+D),  where L and D are the Laplacian and degree matrices of the networks, which  provides a dynamical mechanism for vacuum selection in the string landscape.