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A note on the uniform ergodicity of diffusion processes

Nikola Sandrić

TL;DR

This paper derives explicit Lyapunov-type conditions for the uniform ergodicity of Itô diffusions in total variation, via the Foster–Lyapunov framework. By verifying open-set irreducibility and aperiodicity and constructing a Lyapunov function from integral quantities $I_{x_0}$ and $\gamma_{x_0}$, it proves exponential convergence to a unique invariant measure under the condition $\Lambda<\infty$. The results apply to a broad class of diffusions and extend to subordinate processes, with practical examples illustrating the conditions and demonstrating preservation of uniform ergodicity under subordination. The work provides a concrete, verifiable set of criteria that complements existing coupling-based approaches and broadens the applicability to diffusion models with nontrivial drift and diffusion structures.

Abstract

In this note, we discuss the uniform ergodicity of a diffusion process given by an Itô stochastic differential equation. We present an integral condition in terms of the drift and diffusion coefficients that ensures the uniform ergodicity of the corresponding transition kernel with respect to the total variation distance. Applications of the obtained results to a class of subordinate diffusion processes are also presented.

A note on the uniform ergodicity of diffusion processes

TL;DR

This paper derives explicit Lyapunov-type conditions for the uniform ergodicity of Itô diffusions in total variation, via the Foster–Lyapunov framework. By verifying open-set irreducibility and aperiodicity and constructing a Lyapunov function from integral quantities and , it proves exponential convergence to a unique invariant measure under the condition . The results apply to a broad class of diffusions and extend to subordinate processes, with practical examples illustrating the conditions and demonstrating preservation of uniform ergodicity under subordination. The work provides a concrete, verifiable set of criteria that complements existing coupling-based approaches and broadens the applicability to diffusion models with nontrivial drift and diffusion structures.

Abstract

In this note, we discuss the uniform ergodicity of a diffusion process given by an Itô stochastic differential equation. We present an integral condition in terms of the drift and diffusion coefficients that ensures the uniform ergodicity of the corresponding transition kernel with respect to the total variation distance. Applications of the obtained results to a class of subordinate diffusion processes are also presented.

Paper Structure

This paper contains 6 sections, 2 theorems, 51 equations.

Key Result

Theorem 1.1

Assume $\textbf{(A1)-(A5)}$, and (observe that (A5) ensures that $\Lambda$ is well defined). Then, $\{X(t)\}_{t\ge0}$ is uniformly ergodic.

Theorems & Definitions (7)

  • Theorem 1.1
  • Proposition 2.1
  • proof
  • proof : Proof of Theorem \ref{['tm:TV']}
  • Example 3.1
  • Example 3.2
  • Example 3.3