Heat kernel estimates for random walks with degenerate weights
Probability
2019-05-31 v3 Analysis of PDEs
Abstract
We establish Gaussian-type upper bounds on the heat kernel for a continuous-time random walk on a graph with unbounded weights under an ergodicity assumption. For the proof we use Davies' perturbation method, where we show a maximal inequality for the perturbed heat kernel via Moser iteration.
Cite
@article{arxiv.1412.4338,
title = {Heat kernel estimates for random walks with degenerate weights},
author = {Sebastian Andres and Jean-Dominique Deuschel and Martin Slowik},
journal= {arXiv preprint arXiv:1412.4338},
year = {2019}
}
Comments
24 pages; in this version we corrected statement and proof of Theorem 1.10 and removed a minor technical gap in the iteration argument