We exhibit a strong connection between cover times of graphs, Gaussian processes, and Talagrand's theory of majorizing measures. In particular, we show that the cover time of any graph @math is equivalent, up to universal constants, to the square of the expected maximum of the Gaussian free field on @math , scaled by the number of edges in @math . This allows us to resolve a number of open questions. We give a deterministic polynomial-time algorithm that computes the cover time to within an O(1) factor for any graph, answering a question of Aldous and Fill (1994). We also positively resolve the blanket time conjectures of Winkler and Zuckerman (1996), showing that for any graph, the blanket and cover times are within an O(1) factor. The best previous approximation factor for both these problems was @math for @math -vertex graphs, due to Kahn, Kim, Lovasz, and Vu (2000).
A fundamental bound of Matthews @cite_46 shows that @math where we recall that @math is the expected hitting time from @math to @math . Using the straightforward lower bound @math , this fact provides a deterministic @math -approximation to @math in @math -node graphs.
@cite_46
2136645553
We prove upper and lower bounds and give an approximation algorithm for the cover time of the random walk on a graph. We introduce a parameter M motivated by the well-known Matthews bounds (P. Matthews, 1988) on the cover time, C, and prove that M 2<C= O(M(lnlnn) sup 2 ). We give a deterministic-polynomial time algorithm to approximate M within a factor of 2; this then approximates C within a factor of O((lnlnn) sup 2 ), improving the previous bound O(lnn) due to Matthews. The blanket time B was introduced by P. Winkler and D. Zuckerman (1996): it is the expectation of the first time when all vertices are visited within a constant factor of the number of times suggested by the stationary distribution. Obviously C spl les B. Winkler and Zuckerman conjectured B=O(C) and proved B=O(Clnn). Our bounds above are also valid for the blanket time, and so it follows that B=O(C(lnlnn) sup 2 ).