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arXiv 2007.03674math.AP
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Gagliardo-Nirenberg-Sobolev 不等式中的稳定性:流、正则性与熵方法

Stability in Gagliardo-Nirenberg-Sobolev inequalities: flows, regularity and the entropy method

Matteo Bonforte, Jean Dolbeault, Bruno Nazaret, Nikita Simonov

AI总结:

本文利用快速扩散方程流建立次临界 Gagliardo-Nirenberg-Sobolev 不等式的定量构造性稳定性结果,首次获得含 Sobolev 临界情形的稳定性常数估计。

摘要:

本工作的目的是为一类次临界 Gagliardo-Nirenberg-Sobolev 不等式建立一个定量且构造性的稳定性结果,这类不等式在对数 Sobolev 不等式与标准 Sobolev 不等式(维数大于三时)或二维 Onofri 不等式之间进行插值。我们发展了一种新策略,其中快速扩散方程的流被用作工具:不等式中的稳定性结果等价于该流向平衡态收敛速率的改进。抛物型流的正则性使我们能够将初始时间层内改进的熵-熵产生不等式与一个适合渐近时间层的线性化问题的谱性质联系起来。总体而言,不等式中的稳定性由一个亏量来度量,该亏量在强范数(一种 Fisher 信息,可解释为广义 Heisenberg 不确定性原理)下控制到最优函数流形的距离。该方法是构造性的,并且首次得到了稳定性常数的定量估计,包括在 Sobolev 不等式的临界情形中。为了建立这些估计,我们证明了一个定量全局 Harnack 原理,并通过熵方法对大时间渐近行为进行了详细分析。

英文摘要:

The purpose of this work is to establish a quantitative and constructive stability result for a class of subcritical Gagliardo-Nirenberg-Sobolev inequalities which interpolates between the logarithmic Sobolev inequality and the standard Sobolev inequality (in dimension larger than three), or Onofri's inequality in dimension two. We develop a new strategy, in which the flow of the fast diffusion equation is used as a tool: a stability result in the inequality is equivalent to an improved rate of convergence to equilibrium for the flow. The regularity properties of the parabolic flow allow us to connect an improved entropy - entropy production inequality during an initial time layer to spectral properties of a suitable linearized problem which is relevant for the asymptotic time layer. Altogether, the stability in the inequalities is measured by a deficit which controls in strong norms (a Fisher information which can be interpreted as a generalized Heisenberg uncertainty principle) the distance to the manifold of optimal functions. The method is constructive and, for the first time, quantitative estimates of the stability constant are obtained, including in the critical case of Sobolev's inequality. To build the estimates, we establish a quantitative global Harnack principle and perform a detailed analysis of large time asymptotics by entropy methods.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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