Convergence to the uniform distribution of moderately self-interacting diffusions on compact Riemannian manifolds

TL;DR

This paper proves that a class of self-interacting diffusions on compact Riemannian manifolds converges to the uniform distribution, with a polynomial rate, by linking occupation measures to a specific flow.

Contribution

It establishes almost sure convergence of occupation measures to uniform distribution for self-interacting diffusions on manifolds, with explicit convergence rates.

Findings

Occupation measure converges weakly to uniform distribution.

Polynomial rate of convergence for smooth test functions.

Occupation measure shadows a specific differential flow.

Abstract

We consider a self-interacting diffusion $X$ on a smooth compact Riemannian manifold $\mathbb M$, described by the stochastic differential equation \[ dX_t = \sqrt{2} dW_t(X_t)- \beta(t) \nabla V_t(X_t)dt, \] where $\beta$ is suitably lower-bounded and grows at most logarithmically, and $V_t(x)=\frac{1}{t}\int_0^t V(x,X_s)ds$ for a suitable smooth function $V\colon \mathbb M^2\to\mathbb R$ that makes the term $-\nabla V_t(X_t)$ self-repelling. We prove that almost surely the normalized occupation measure $\mu_t$ of $X$ converges weakly to the uniform distribution $\mathcal U$, and we provide a polynomial rate of convergence for smooth test functions. The key to this result is showing that if $f\colon\mathbb M\to\mathbb R$ is smooth, then $\mu_{e^t}(f)$ shadows the flow generated by the ordinary differential equation \[ \dot x_t=-x_t+\mathcal U(f). \]