Heat kernel estimates for subordinate Markov processes and their applications

Soobin Cho, Panki Kim, Renming Song, Zoran Vondraček

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we establish sharp two-sided estimates for transition densities of a large class of subordinate Markov processes. As applications, we show that the parabolic Harnack inequality and Hölder regularity hold for parabolic functions of such processes, and derive sharp two-sided Green function estimates.

Original languageEnglish (US)
Pages (from-to)28-93
Number of pages66
JournalJournal of Differential Equations
Volume316
DOIs
StatePublished - Apr 15 2022

Keywords

  • Green function
  • Heat kernel
  • Parabolic Harnack inequality
  • Spectral fractional Laplacian
  • Subordinate Markov process
  • Transition density

ASJC Scopus subject areas

  • Analysis
  • Applied Mathematics

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