Convergence Rates for Lasserre's Upper-Bound Hierarchy on $\mathbb{R}^d$ with Gaussian Measure

Abstract

We establish quantitative convergence rates for Lasserre's measure-based upper-bound hierarchy on $\mathbb{R}^d$ using the standard Gaussian measure as the reference measure. For any polynomial $f$ attaining its global infimum $f_{\min}$, we prove that the order-$r$ upper bounds satisfy $$ λ_r-f_{\min}=O\Big(\frac{1}{r}\Big), $$ yielding, to the best of our knowledge, the first explicit convergence rate for this hierarchy on a noncompact domain. We further show that the rate is sharp by proving an $Ω(1/r)$ rate for $f=x^2$, while demonstrating that, without attainment of the infimum, convergence can be arbitrarily slow: for every $m\ge0$, we construct a polynomial whose upper bounds converge at rate $Θ(r^{-1/(m+2)})$.