论文标题

基因流模型的控制限制

Constrained control of gene-flow models

论文作者

Mazari, Idriss, Ruiz-Balet, Domenec, Zuazua, Enrique

论文摘要

在生态学和人群动态中,基因流是指一个特征从一个人群转移到另一个人群。这种现象出现在研究社会特征(例如语言)的演变中。从数学的角度来看,基因流是使用双向反应扩散方程进行建模的。未知的是人口$ n $内拥有一定特征的人口的比例$ p $。假设人口密度$ n $取决于$ p $或位置$ x $,则考虑到基因流。蚊子传播疾病控制问题或双语研究的最新应用呼吁研究这些模型的可控性能。在数学层面上,这对应于边界控制问题,并且由于我们正在处理比例,因此控制$ u $必须满足约束$ 0 \ leq uq u \ leq 1 $。在本文中,我们对基因流动效应对边界可控性能的影响进行了详尽的分析。我们证明,当人口密度$ n $仅取决于特征比例$ p $时,域的几何形状是必须考虑的唯一标准。然后,我们解决人口密度$ n $的情况,$ x $。我们首先证明,当$ n $以$ x $变化而变化时,当域足够狭窄时,可控性总是可以保持的。然后,我们考虑$ n $中急剧波动的情况:我们举例说明可控性可能会失败。相反,我们举例说明$ n $,以便可以保证可控性。所有负面的可控性结果都是通过显示出非平凡固定状态的存在来证明的,这些状态起到了障碍。这种解决方案的存在和证明方法具有独立的利益。我们的文章是通过几个数字实验来完成的,这些实验证实了我们的分析。

In ecology and population dynamics, gene-flow refers to the transfer of a trait from one population to another. This phenomenon appears in studying the evolution of social features, such as languages. From the mathematical point of view, gene-flow is modelled using bistable reaction-diffusion equations. The unknown is the proportion $p$ of the population possessing a certain trait, within a population $N$. Gene-flow is taken into account by assuming that the population density $N$ depends either on $p$ or on the location $x$. Recent applications stemming from mosquito-borne disease control problems or from the study of bilingualism have called for the investigation of the controllability properties of these models. At the mathematical level, this corresponds to boundary control problems and, since we are working with proportions, the control $u$ has to satisfy the constraints $0\leq u \leq 1$. In this article, we provide a thorough analysis of the influence of the gene-flow effect on boundary controllability properties. We prove that, when the population density $N$ only depends on the trait proportion $p$, the geometry of the domain is the only criterion that has to be considered. We then tackle the case of population densities $N$ varying in $x$. We first prove that, when $N$ varies slowly in $x$ and when the domain is narrow enough, controllability always holds. We then consider the case of sharp fluctuations in $N$: we give examples that prove that controllability may fail. Conversely, we give examples of $N$ such that controllability will always be guaranteed. All negative controllability results are proved by showing the existence of non-trivial stationary states, which act as barriers. The existence of such solutions and the methods of proof are of independent interest. Our article is completed by several numerical experiments that confirm our analysis.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源