English

Convergence rates of Gibbs measures with degenerate minimum

Probability 2022-12-12 v2

Abstract

We study convergence rates for Gibbs measures, with density proportional to ef(x)/te^{-f(x)/t}, as t0t \rightarrow 0 where f:RdRf : \mathbb{R}^d \rightarrow \mathbb{R} admits a unique global minimum at xx^\star. We focus on the case where the Hessian is not definite at xx^\star. We assume instead that the minimum is strictly polynomial and give a higher order nested expansion of ff at xx^\star, which depends on every coordinate. We give an algorithm yielding such a decomposition if the polynomial order of xx^\star is no more than 88, in connection with Hilbert's 17th17^{\text{th}} problem. However, we prove that the case where the order is 1010 or higher is fundamentally different and that further assumptions are needed. We then give the rate of convergence of Gibbs measures using this expansion. Finally we adapt our results to the multiple well case.

Keywords

Cite

@article{arxiv.2101.11557,
  title  = {Convergence rates of Gibbs measures with degenerate minimum},
  author = {Pierre Bras},
  journal= {arXiv preprint arXiv:2101.11557},
  year   = {2022}
}

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25 pages