The asymptotic behavior of fraudulent algorithms

Abstract

Let $U$ be a Morse function on a compact connected $m$-dimensional Riemannian manifold, $m \geq 2,$ satisfying $\min U=0$ and let $\mathcal{U} = \{x \in M \: : U(x) = 0\}$ be the set of global minimizers. Consider the stochastic algorithm $X^{(β)}:=(X^{(β)}(t))_{t\geq 0}$ defined on $N = M \setminus \mathcal{U},$ whose generator is$U Δ\cdot-β\langle \nabla U,\nabla \cdot\rangle$, where $β\in\RR$ is a real parameter.We show that for $β>\frac{m}{2}-1,$ $X^{(β)}(t)$ converges a.s.\ as $t \rightarrow \infty$, toward a point $p \in \mathcal{U}$ and that each $p \in \mathcal{U}$ has a positive probability to be selected. On the other hand, for $β< \frac{m}{2}-1,$ the law of $(X^{(β)}(t))$ converges in total variation (at an exponential rate) toward the probability measure $π_β$ having density proportional to $U(x)^{-1-β}$ with respect to the Riemannian measure.

Theorems & Definitions (10)

• Proposition 1
• Theorem 3
• Theorem 7
• Lemma 9
• Lemma 10
• Lemma 11
• Lemma 12
• Lemma 13
• Lemma 14
• Lemma 15