fkpp型自组织增长模型临界波的对流稳定性。

IF 2.3 4区 数学 Q2 BIOLOGY
Florian Kreten
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引用次数: 0

摘要

构造了两种密度粒子的FKPP生长过程的行波解,并证明了临界行波在波后扰动呈指数增长的空间中是局部稳定的。Hannezo等人(Cell 171(1):242-255, 2017)在分支形态发生的背景下引入了所考虑的反应-扩散系统:活跃的、分支的颗粒聚集不活跃的颗粒,这些颗粒不发生反应。因此,该系统具有连续的稳态解,使分析变得复杂。我们采用Faye和Holzer (J Differ Equ 269(9): 65559 -6601, 2020)的结果来证明临界行波的稳定性,并将半群估计修改为权无界空间。我们使用费曼-卡茨公式来获得PDE尾部的指数先验估计,这是一种新颖而简单的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Convective stability of the critical waves of an FKPP-type model for self-organized growth.

Convective stability of the critical waves of an FKPP-type model for self-organized growth.

Convective stability of the critical waves of an FKPP-type model for self-organized growth.

Convective stability of the critical waves of an FKPP-type model for self-organized growth.

We construct the traveling wave solutions of an FKPP growth process of two densities of particles, and prove that the critical traveling waves are locally stable in a space where the perturbations can grow exponentially at the back of the wave. The considered reaction-diffusion system was introduced by Hannezo et al. (Cell 171(1):242-255, 2017) in the context of branching morphogenesis: active, branching particles accumulate inactive particles, which do not react. Thus, the system features a continuum of steady state solutions, complicating the analysis. We adopt a result by Faye and Holzer (J Differ Equ 269(9):6559-6601, 2020) for proving the stability of the critical traveling waves, and modify the semi-group estimates to spaces with unbounded weights. We use a Feynman-Kac formula to get an exponential a priori estimate for the tail of the PDE, a novel and simple approach.

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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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