English

Intrinsic Geometry and Analysis of Diffusion Processes and $L^\infty$-Variational Problems

Classical Analysis and ODEs 2013-05-28 v1 Analysis of PDEs Functional Analysis Probability

Abstract

The aim of this paper is two-fold: First, we obtain a better understanding of the intrinsic distance of diffusion processes. Precisely, (i) for all n1n\ge1, the diffusion matrix AA is weak upper semicontinuous on Ω\Omega if and only if the intrinsic differential and the local intrinsic distance structures coincide; (ii) if n=1n=1, or if n2n\ge2 and AA is weak upper semicontinuous on Ω\Omega, the intrinsic distance and differential structures always coincide; (iii) if n2n\ge2 and AA fails to be weak upper semicontinuous on Ω\Omega, the (non-) coincidence of the intrinsic distance and differential structures depend on the geometry of the non-weak-upper-semicontinuity set of AA. Second, for an arbitrary diffusion matrix AA, we show that the intrinsic distance completely determines the absolute minimizer of the corresponding LL^\infty-variational problem, and then obtain the existence and uniqueness for given boundary data. We also give an example of a diffusion matrix AA for which there is an absolute minimizer that is not of class C1C^1. When AA is continuous, we also obtain the linear approximation property of the absolute minimizer.

Keywords

Cite

@article{arxiv.1305.6130,
  title  = {Intrinsic Geometry and Analysis of Diffusion Processes and $L^\infty$-Variational Problems},
  author = {Pekka Koskela and Nageswari Shanmugalingam and Yuan Zhou},
  journal= {arXiv preprint arXiv:1305.6130},
  year   = {2013}
}

Comments

submitted

R2 v1 2026-06-22T00:22:58.064Z