设计具有图灵和波动不稳定性的反应-交叉扩散系统。

IF 2.3 4区 数学 Q2 BIOLOGY
Edgardo Villar-Sepúlveda, Alan R Champneys, Andrew L Krause
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引用次数: 0

摘要

建立了反应-交叉扩散系统发生时空模式形成不稳定性的一般条件。最近的工作集中在理论和实验上设计系统,以展示具有特定特征的模式,但非对角扩散矩阵的情况尚未得到分析。本文提出了一个框架,用于设计具有给定波长的图灵和波不稳定性的一般n组分反应-交叉扩散系统。对于一组固定的反应动力学,展示了如何选择产生每种不稳定性的扩散矩阵;相反,对于给定的扩散张量,如何选择线性化动力学。该理论被应用于几个例子,包括双曲反应-扩散系统,两个不同的3组分模型,以及Ross-Macdonald疟疾传播模型的时空版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Designing reaction-cross-diffusion systems with Turing and wave instabilities.

Designing reaction-cross-diffusion systems with Turing and wave instabilities.

Designing reaction-cross-diffusion systems with Turing and wave instabilities.

Designing reaction-cross-diffusion systems with Turing and wave instabilities.

General conditions are established under which reaction-cross-diffusion systems can undergo spatiotemporal pattern-forming instabilities. Recent work has focused on designing systems theoretically and experimentally to exhibit patterns with specific features, but the case of non-diagonal diffusion matrices has yet to be analysed. Here, a framework is presented for the design of general n-component reaction-cross-diffusion systems that exhibit Turing and wave instabilities of a given wavelength. For a fixed set of reaction kinetics, it is shown how to choose diffusion matrices that produce each instability; conversely, for a given diffusion tensor, how to choose linearised kinetics. The theory is applied to several examples including a hyperbolic reaction-diffusion system, two different 3-component models, and a spatio-temporal version of the Ross-Macdonald model for the spread of malaria.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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