Abstract
Let G be a finite connected graph. A spanning tree T of G is a connected subgraph of G that contains no cycles and such that every vertex of G is incident to at least one edge of T. The set of spanning trees of a given finite connected graph is obviously finite and hence we may draw one uniformly at random. This random tree is called the uniform spanning tree (UST) of G. This model was first studied by Kirchhoff who gave a formula for the number of spanning trees of a given graph and provided a beautiful connection with the theory of electric networks. In particular, he showed that the probability that a given edge {x, y} of G is contained in the UST equals \(\mathcal {R}_{\mathrm {eff}}(x \leftrightarrow y; G)\); we prove this fundamental formula in Sect. 7.2 (see Theorem 7.2).
Highlights
Let G be a finite connected graph
The set of spanning trees of a given finite connected graph is obviously finite and we may draw one uniformly at random. This random tree is called the uniform spanning tree (UST) of G. This model was first studied by Kirchhoff [49] who gave a formula for the number of spanning trees of a given graph and provided a beautiful connection with the theory of electric networks
We will define there the wired uniform spanning forest which is obtained by taking a limit of the UST probability measures over exhaustions with wired boundary
Summary
Let G be a finite connected graph. A spanning tree T of G is a connected subgraph of G that contains no cycles and such that every vertex of G is incident to at least one edge of T. The set of spanning trees of a given finite connected graph is obviously finite and we may draw one uniformly at random. This random tree is called the uniform spanning tree (UST) of G This model was first studied by Kirchhoff [49] who gave a formula for the number of spanning trees of a given graph and provided a beautiful connection with the theory of electric networks. He showed that the probability that a given edge {x, y} of G is contained in the UST equals Reff(x ↔ y; G); we prove this fundamental formula in Sect.
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