Fast Generation of Random Spanning Trees and the Effective Resistance Metric

Abstract

We present a new algorithm for generating a uniformly random spanning tree in an undirected graph. Our algorithm samples such a tree in expected time. This improves over the best previously known bound of , O(nω)) − that follows from the work of Kelner and Madry [FOCS'09] and of Colbourn et al. [J. Algorithms'96] – whenever the input graph is sufficiently sparse. At a high level, our result stems from carefully exploiting the interplay of random spanning trees, random walks, and the notion of effective resistance, as well as from devising a way to algorithmically relate these concepts to the combinatorial structure of the graph. This involves, in particular, establishing a new connection between the effective resistance metric and the cut structure of the underlying graph.