English

Dimension-independent functional inequalities by tensorization and projection arguments

Probability 2025-01-03 v2 Analysis of PDEs Functional Analysis

Abstract

We study stability under tensorization and projection-type operations of gradient-type estimates and other functional inequalities for Markov semigroups on metric spaces. Using transportation-type inequalities obtained by F. Baudoin and N. Eldredge in 2021, we prove that constants in the gradient estimates can be chosen to be independent of the dimension. Our results are applicable to hypoelliptic diffusions on sub-Riemannian manifolds and some hypocoercive diffusions. As a byproduct, we obtain dimension-independent reverse Poincar\'{e}, reverse logarithmic Sobolev, and gradient bounds for Lie groups with a transverse symmetry and for non-isotropic Heisenberg groups.

Keywords

Cite

@article{arxiv.2403.18799,
  title  = {Dimension-independent functional inequalities by tensorization and projection arguments},
  author = {Fabrice Baudoin and Maria Gordina and Rohan Sarkar},
  journal= {arXiv preprint arXiv:2403.18799},
  year   = {2025}
}

Comments

33 pages, minor corrections, new examples added

R2 v1 2026-06-28T15:35:54.187Z