High-level convexity for products of squared Euclidean distance functions

Abstract

We study smooth functions on Euclidean space whose Hessian is positive definite outside a bounded set, with emphasis on products of squared distance functions. More precisely, we first prove a simple convexity principle: if the superlevel region $f^{-1}([c,\infty ))$ is contained in the Hessian-positive region of $f$, then the sublevel set $\{f\le c\}$ is convex. We apply this to finite products $F_P(x)={\prod }_{p\in P}\Vert x-p{\Vert }^2$, proving that their Hessian-positive complements are bounded. For the two-centre product $F_{p,q}(x)=\Vert x-p{\Vert }^2\Vert x-q{\Vert }^2$ in dimension $n\ge 2$, we compute the Hessian-positive region and the exact value \[ h_{max}(F_{p,q})=\frac{\|p-q\|^4}{4}. \] This value is sharp for convexity of sublevel sets in the following sense: we prove convexity above it and nonconvexity below it. This also gives the exact convexity and quasiconvexity truncation levels for the two-centre model.

10 pages; comments are welcome