聚合方程及其他随机扩散流动的全局解。

IF 1.5 1区 数学 Q2 STATISTICS & PROBABILITY
Probability Theory and Related Fields Pub Date : 2023-01-01 Epub Date: 2022-10-31 DOI:10.1007/s00440-022-01171-8
Matthew Rosenzweig, Gigliola Staffilani
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引用次数: 0

摘要

众所周知,聚合方程(如抛物线-椭圆形 Patlak-Keller-Segel 模型)在全局存在与有限时间爆炸之间有一个最佳临界点。特别是,如果不存在扩散,那么所有具有有限第二矩的平稳解只能在局部时间内存在。然而,我们可以问一下,是否可以通过在方程中加入适当的噪声来恢复全局存在性,从而使动力学变得随机。Buckmaster 等人的研究(Int Math Res Not IMRN 23:9370-9385, 2020)表明,具有随机扩散的不粘性 SQG 方程很有可能具有全局经典解,受此启发,我们研究了适当的随机扩散能否恢复一大类任意维度、可能具有奇异速度场的活动标量方程的全局存在性。这类方程包括哈密顿流(如 SQG 方程及其广义)和梯度流(如聚集模型中出现的梯度流)。对于这类方程,我们展示了在 Gevrey 型傅里叶-勒贝格空间中以可量化的高概率存在的全局解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global solutions of aggregation equations and other flows with random diffusion.

Aggregation equations, such as the parabolic-elliptic Patlak-Keller-Segel model, are known to have an optimal threshold for global existence versus finite-time blow-up. In particular, if the diffusion is absent, then all smooth solutions with finite second moment can exist only locally in time. Nevertheless, one can ask whether global existence can be restored by adding a suitable noise to the equation, so that the dynamics are now stochastic. Inspired by the work of Buckmaster et al. (Int Math Res Not IMRN 23:9370-9385, 2020) showing that, with high probability, the inviscid SQG equation with random diffusion has global classical solutions, we investigate whether suitable random diffusion can restore global existence for a large class of active scalar equations in arbitrary dimension with possibly singular velocity fields. This class includes Hamiltonian flows, such as the SQG equation and its generalizations, and gradient flows, such as those arising in aggregation models. For this class, we show global existence of solutions in Gevrey-type Fourier-Lebesgue spaces with quantifiable high probability.

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来源期刊
Probability Theory and Related Fields
Probability Theory and Related Fields 数学-统计学与概率论
CiteScore
3.70
自引率
5.00%
发文量
71
审稿时长
6-12 weeks
期刊介绍: Probability Theory and Related Fields publishes research papers in modern probability theory and its various fields of application. Thus, subjects of interest include: mathematical statistical physics, mathematical statistics, mathematical biology, theoretical computer science, and applications of probability theory to other areas of mathematics such as combinatorics, analysis, ergodic theory and geometry. Survey papers on emerging areas of importance may be considered for publication. The main languages of publication are English, French and German.
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