arXiv · 1804.05237
Asymptotic Linear Programming Lower Bounds for the Energy of Minimizing Riesz and Gauss Configurations
Abstract
Utilizing frameworks developed by Delsarte, Yudin and Levenshtein, we deduce linear programming lower bounds (as $N\to \infty$) for the Riesz energy of $N$-point configurations on the $d$-dimensional unit sphere in the so-called hypersingular case; i.e, for non-integrable Riesz kernels of the form $|x-y|^{-s}$ with $s>d.$ As a consequence, we immediately get (thanks to the Poppy-seed bagel theorem) lower estimates for the large $N$ limits of minimal hypersingular Riesz energy on compact $d$-rectifiable sets. Furthermore, for the Gaussian potential $\exp(-\alpha|x-y|^2)$ on $\mathbb{R}^p,$ we obtain lower bounds for the energy of infinite configurations having a prescribed density.
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Douglas P. Hardin, Timothy J. Michaels, Edward B. Saff. 2018-04-14. Asymptotic Linear Programming Lower Bounds for the Energy of Minimizing Riesz and Gauss Configurations. https://doi.org/10.1112/s0025579318000360
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