The probability that a transient Markov chain, or a Brownian path, will ever visit a given set $\Lambda$ is classically estimated using the capacity of $\Lambda$ with respect to the Green kernel $G(x, y)$. We show that replacing the Green kernel by the Martin kernel $G(x, y)/G(0, y)$ yields improved estimates, which are exact up to a factor of 2. These estimates are applied to random walks on lattices and also to explain a connection found by Lyons between capacity and percolation on trees.
@article{1176988187,
author = {Benjamini, Itai and Pemantle, Robin and Peres, Yuval},
title = {Martin Capacity for Markov Chains},
journal = {Ann. Probab.},
volume = {23},
number = {3},
year = {1995},
pages = { 1332-1346},
language = {en},
url = {http://dml.mathdoc.fr/item/1176988187}
}
Benjamini, Itai; Pemantle, Robin; Peres, Yuval. Martin Capacity for Markov Chains. Ann. Probab., Tome 23 (1995) no. 3, pp. 1332-1346. http://gdmltest.u-ga.fr/item/1176988187/