The concept of discrete p-modulus provides a general framework for understanding arbitrary families of objects on a graph. The p-modulus provides a sense of "structure'' of the underlying graph, with different families of objects leading to different insight into the graph's structure. This dissertation builds on this idea, with an emphasis on the family of spanning trees and the underlying graph structure that spanning tree modulus exposes.

This dissertation provides a review of the probabilistic interpretation of modulus. In the context of spanning trees, this interpretation rephrases modulus as the problem of choosing a probability mass function on the spanning trees so that two independent, identically distributed random spanning trees have expected overlap as small as possible.

A theoretical lower bound on the expected overlap is shown. Graphs that attain this lower bound are called homogeneous and have the property that there exists a probability mass function that gives every edge equal likelihood to appear in a random tree. Moreover, any nonhomogeneous graph necessarily has a homogeneous subgraph (called a homogeneous core), which is shown to split the modulus problem into two smaller subproblems through a process called deflation.

Spanning tree modulus and the process of deflation establish a type of hierarchical structure in the underlying graph that is similar to the concept of core-periphery structure found in the literature. Using this, one can see an alternative way of decomposing a graph into its hierarchical community components using homogeneous cores and a related concept: minimum feasible partitions.

This dissertation also introduces a simple greedy algorithm for computing the spanning tree modulus that utilizes any efficient algorithm for finding minimum spanning trees. A theoretical proof of the convergence rate is provided, along with computational examples.