On gradient flows initialized near maxima

Abstract

Let $(M,g)$ be a closed Riemannian manifold, and let $F:M\to \mathbb{R}$ be a smooth function on $M$. We show the following holds generically for the function $F$: for each maximum $p$ of $F$, there exist two minima, denoted by $m_{+}(p)$ and $m_{-}(p)$, so that the gradient flow initialized at a random point close to $p$ converges to either $m_{-}(p)$ or $m_{+}(p)$ with high probability. The statement also holds for $F\in C^{\infty }(M)$ fixed and a generic metric $g$ on $M$. We conclude by associating to a given a generic pair $(F,g)$ what we call its max-min graph, which captures the relation between minima and maxima derived in the main result.

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