# Controllability implies mixing I. Convergence in the total variation metric

## TL;DR

This paper establishes that certain controllability conditions in dynamical systems guarantee the uniqueness of stationary measures and exponential mixing in total variation, with applications to stochastic differential equations on manifolds.

## Contribution

It proves that approximate and solid controllability imply exponential mixing and uniqueness of stationary measures, linking controllability to stochastic system asymptotics.

## Key findings

- Approximate controllability and solid controllability imply exponential mixing.
- These controllability conditions ensure the uniqueness of stationary measures.
- Application to random differential equations on compact Riemannian manifolds.

## Abstract

This paper is the first part of a project devoted to studying the interconnection between controllability properties of a dynamical system and the large-time asymptotics of trajectories for the associated stochastic system. It is proved that the approximate controllability to a given point and the solid controllability from the same point imply the uniqueness of a stationary measure and exponential mixing in the total variation metric. This result is then applied to random differential equations on a compact Riemannian manifold. In the second part, we shall replace the solid controllability by a stabilisability condition and prove that it is still sufficient for the uniqueness of a stationary distribution, whereas the convergence to it holds in the weaker dual-Lipschitz metric.