Characterization of subordinate symmetric Markov processes
Probability
2024-12-17 v2
Abstract
In this paper, we consider subordinate symmetric Markov processes which correspond to non-killing Dirichlet forms enjoying heat kernel estimates on a metric measure space with the volume doubling property. We obtain estimates of the jump kernel of the subordinate process and establish equivalent conditions for the jump kernel following Liu-Murugan. In particular, we clarify the scale of the jump kernel, which is different from the diffusion type. This result is appliable to non-subordinate processes by the transferring method, which uses stability of Dirichlet forms.
Cite
@article{arxiv.2412.05030,
title = {Characterization of subordinate symmetric Markov processes},
author = {Ryuto Kushida},
journal= {arXiv preprint arXiv:2412.05030},
year = {2024}
}