Title: Higher-order correlation inequalities for random spanning trees
| Speaker: | David Wagner |
| Affiliation: | University of Waterloo |
| Location: | MC 6029 |
There will be a pre-seminar presenting relevant background at the beginning graduate level starting at 1:00 pm.
Abstract: The connection between enumerating spanning trees of a graph and the theory of (linear) electrical networks goes all the way back to Kirchhoff's 1847 paper. It is physically sensible that if one increases the conductance of one wire in an electrical network, then the overall conductance of the network can not decrease. This corresponds to the less obvious fact that any two distinct edges are non-positively correlated, when one chooses a random spanning tree. Covariance is the 2-point "Ursell function'', and expectation is the 1-point Ursell function. For any subset of edges there is an associated Ursell function, and these are related to occupation probabilities by Möbius inversion. I will discuss some situations in which the signs of these Ursell functions can be predicted, yielding higher-order correlation inequalities for random spanning trees.