A Dimension-Free Hermite-Hadamard Inequality via Gradient Estimates for the Torsion Function

TL;DR

This paper establishes a dimension-free Hermite-Hadamard inequality for convex domains using a novel gradient estimate for the torsion function, providing a new tool in convex analysis and PDEs.

Contribution

It introduces a new gradient estimate for the torsion function, enabling a dimension-free Hermite-Hadamard inequality for convex domains.

Findings

Proves a dimension-free Hermite-Hadamard inequality for convex domains.

Develops a new gradient estimate for the torsion function.

Provides insights applicable to convex analysis and PDEs.

Abstract

Let $\Omega \subset \mathbb{R}^n$ be a convex domain and let $f:\Omega \rightarrow \mathbb{R}$ be a subharmonic function, $\Delta f \geq 0$, which satisfies $f \geq 0$ on the boundary $\partial \Omega$. Then $$ \int_{\Omega}{f ~dx} \leq |\Omega|^{\frac{1}{n}} \int_{\partial \Omega}{f ~d\sigma}.$$ Our proof is based on a new gradient estimate for the torsion function, $\Delta u = -1$ with Dirichlet boundary conditions, which is of independent interest.