随机旋转波

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY
Christian Kuehn, James MacLaurin, Giulio Zucal
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引用次数: 0

摘要

随机动力学已成为从应用模型到数学理论基础的关键主题之一。一类最近受到相当关注的随机动力学问题是出现在随机偏微分方程(SPDEs)中的行波模式。这里,我们感兴趣的是确定性行波在随机扰动下的表现。在本文中,我们开始了一类相关问题的数学研究:由SPDEs产生的随机旋转波。我们将确定性偏微分方程(PDE)动力学技术与随机分析方法相结合。我们建立了两种不同的方法,变分相位和近似变分相位,用于定义沿旋转波的随机相位变量,跟踪噪声对与旋转波的特殊欧几里得对称群相关的中性谱模式的影响。此外,我们证明了旋转波的横向稳定性结果,表明在一定的时间尺度和小噪声下,随机旋转波保持接近其确定性对应物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic rotating waves

Stochastic dynamics has emerged as one of the key themes ranging from models in applications to theoretical foundations in mathematics. One class of stochastic dynamics problems that has recently received considerable attention are traveling wave patterns occurring in stochastic partial differential equations (SPDEs). Here, one is interested in how deterministic traveling waves behave under stochastic perturbations. In this paper, we start the mathematical study of a related class of problems: stochastic rotating waves generated by SPDEs. We combine deterministic partial differential equation (PDE) dynamics techniques with methods from stochastic analysis. We establish two different approaches, the variational phase and the approximated variational phase, for defining stochastic phase variables along the rotating wave, which track the effect of noise on neutral spectral modes associated to the special Euclidean symmetry group of rotating waves. Furthermore, we prove transverse stability results for rotating waves showing that over certain time scales and for small noise, the stochastic rotating wave stays close to its deterministic counterpart.

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来源期刊
Stochastics and Dynamics
Stochastics and Dynamics 数学-统计学与概率论
CiteScore
1.70
自引率
0.00%
发文量
49
审稿时长
>12 weeks
期刊介绍: This interdisciplinary journal is devoted to publishing high quality papers in modeling, analyzing, quantifying and predicting stochastic phenomena in science and engineering from a dynamical system''s point of view. Papers can be about theory, experiments, algorithms, numerical simulation and applications. Papers studying the dynamics of stochastic phenomena by means of random or stochastic ordinary, partial or functional differential equations or random mappings are particularly welcome, and so are studies of stochasticity in deterministic systems.
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