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Revealing new dynamical patterns in a reaction–diffusion model with cyclic competition via a novel computational framework

机译:通过新颖的计算框架揭示具有循环竞争的反应扩散模型中的新动力学模式

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摘要

Understanding how patterns and travelling waves form in chemical and biological reaction–diffusion models is an area which has been widely researched, yet is still experiencing fast development. Surprisingly enough, we still do not have a clear understanding about all possible types of dynamical regimes in classical reaction–diffusion models, such as Lotka–Volterra competition models with spatial dependence. In this study, we demonstrate some new types of wave propagation and pattern formation in a classical three species cyclic competition model with spatial diffusion, which have been so far missed in the literature. These new patterns are characterized by a high regularity in space, but are different from patterns previously known to exist in reaction–diffusion models, and may have important applications in improving our understanding of biological pattern formation and invasion theory. Finding these new patterns is made technically possible by using an automatic adaptive finite element method driven by a novel a posteriori error estimate which is proved to provide a reliable bound for the error of the numerical method. We demonstrate how this numerical framework allows us to easily explore the dynamical patterns in both two and three spatial dimensions.
机译:了解化学和生物反应扩散模型中的模式和行波是如何形成的,这一领域已被广泛研究,但仍在快速发展。令人惊讶的是,对于经典的反应扩散模型,例如具有空间依赖性的Lotka-Volterra竞争模型,我们仍然对所有可能的动力类型没有清晰的了解。在这项研究中,我们证明了在具有空间扩散的经典三物种循环竞争模型中一些新型的波传播和模式形成,这在文献中是迄今为止所遗漏的。这些新的模式以空间的高度规律性为特征,但不同于以前已知存在于反应扩散模型中的模式,并且在增进我们对生物学模式形成和入侵理论的理解中可能具有重要的应用。通过使用由新颖的后验误差估计驱动的自动自适应有限元方法,在技术上找到这些新模式成为可能,事实证明该方法为数值方法的误差提供了可靠的界限。我们演示了此数值框架如何使我们轻松地探索两个和三个空间维度上的动力学模式。

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