Sharp stability of the logarithmic Sobolev inequality in the critical point setting
Juncheng Wei, Yuanze Wu

TL;DR
This paper establishes the sharp stability of the Euclidean logarithmic Sobolev inequality at critical points, showing that functions close to extremals are quantitatively close in the H^1 norm, with an optimal rate.
Contribution
The paper proves an optimal stability estimate for the logarithmic Sobolev inequality at critical points, quantifying how near functions are to extremal Gaussians in the H^1 norm.
Findings
Proves a sharp stability estimate for the inequality.
Quantifies the distance to extremal functions in H^1 norm.
Demonstrates the optimality of the stability rate.
Abstract
In this paper, we consider the Euclidean logarithmic Sobolev inequality \begin{eqnarray*} \int_{\mathbb{R}^d}|u|^2\log|u|dx\leq\frac{d}{4}\log\bigg(\frac{2}{\pi d e}\|\nabla u\|_{L^2(\mathbb{R}^d)}^2\bigg), \end{eqnarray*} where with and . It is well known that extremal functions of this inequality are precisely the Gaussians \begin{eqnarray*} \mathfrak{g}_{\sigma,z}(x)=(\pi\sigma)^{-\frac{d}{2}}\mathfrak{g}_{*}\bigg(\sqrt{\frac{\sigma}{2}}(x-z)\bigg)\quad\text{with}\quad \mathfrak{g}_{*}(x)=e^{-\frac{|x|^2}{2}}. \end{eqnarray*} We prove that if satisfying and , where , and sufficiently small, then \begin{eqnarray*}…
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Taxonomy
TopicsNonlinear Partial Differential Equations
