Uncertainty principles as forcing mechanisms

Abstract

In this note we first consider the Heisenberg uncertainty principle. We show that it acts as a {\bf forcing mechanism} in the following sense. Real functions that approach its limit are close to Gaussian distributions, with proximity both in the sense of total variation distance and Wasserstein-1 distance. We next consider the uncertainty principle for functions defined on finite Abelian groups, and show that it acts as a forcing mechanism in the following sense. Functions that approach its limit are close (after translation and modulation by a complex exponential) to indicator functions of some subgroup, with proximity measured in ${\mathbb{L}}^1$-norm.