SIAM Review, Volume 62, Issue 3, Page 615-615, January 2020.
In this issue, Research Spotlights features two exciting and topically diverse articles. The authors of the first article introduce the notion of a metaplex and use it to describe and study dynamics of complex systems having both exo- and endostructure. Unlike previous works where both the exo- and endostructures of the complex systems are assumed representable by networks, in “Metaplex Networks: Influence of the Exo-Endo Structure of Complex Systems on Diffusion," by Ernesto Estrada, Gissell Estrada-Rodriguez, and Heiko Gimperlein, the assumption is that the endostructure can be described by a continuous space. The authors give several important examples of complex networks that exhibit such features: one example is a climate system where the processes inside the regions (a.k.a. nodes) “are well described by aerodynamics and fluid dynamics, while the causal influence between regions is well described by a network of interactions." The study of the dynamics on the metaplex offers the opportunity to better understand the individual contributions of the endo- and exo- components to the global behavior of the system. The significance of this claim is highlighted through the application to a landscape metaplex in Madagascar and to the visual cortex metaplex of the macaque: the metaplex dynamics shows that different factors are responsible for global behavior in each case. Because the study of metaplexes utilizes tools from a broad range of areas, “suggests the relevance of network theory for old problems in these fields," and has the potential to become more widely applicable with the aid of computationally efficient methods like model order reduction, the article should appeal to many SIREV readers. The second article, “Why Are U.S. Parties So Polarized? A `Satisficing' Dynamical Model," is a timely one. In this work, authors Vicky Chuqiao Yang, Daniel M. Abrams, Georgia Kernell, and Adilson E. Motter develop a mathematical model for the ideological polarity in U.S. political parties. Like the well-known Downsian model, the new model considers voter population distributed in a one-dimensional so-called ideology space. However, unlike the Downsian model that assumes “citizens cast their vote for the ideologically closest party, and parties adjust their positions to maximize votes," the new, differential equations--based model is based on the concept of voters who make so-called satisficing decisions, i.e., decisions made randomly among positions the voters deem are satisfactory. Thus, while the former method predicts, incorrectly, that both parties should converge to the median voter's position, the authors' new model is shown to be better able to fit the empirical data. Indeed, the results for the proposed model suggest that “appealing to an extreme segment of the electorate can be a winning political strategy," even, perhaps ironically, in the absence of changes to voters' ideological positions. Readers are invited to explore the supplementary material for some extensions to the model presented in the article and are encouraged to consider future work in expanding their model.

中文翻译：

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研究热点

SIAM评论，第62卷，第3期，第615-615页，2020年1月。
在本期中，《研究热点》刊登了两篇激动人心且主题多样的文章。第一篇文章的作者介绍了元复合体的概念，并用它来描述和研究具有外结构和内结构的复杂系统的动力学。与以前的工作假设复杂系统的外部结构和内部结构都可以用网络表示的情况不同，Ernesto Estrada，Gissell Estrada-Rodriguez和Heiko在“复合网络：复杂系统的外部-内在结构对扩散的影响”中金普林认为，内部结构可以用连续的空间来描述。作者给出了几个具有这种特征的复杂网络的重要例子：一个例子是一个气候系统，其中区域（又称节点）内部的过程得到了很好的描述。通过空气动力学和流体动力学，该文章应吸引许多SIREV读者。第二篇文章“为什么美国政党如此两极化？一种“令人满意的”动力学模型是及时的。在这项工作中，作者Vicky Chuqiao Yang，Daniel M. Abrams，Georgia Kernell和Adilson E. Motter开发了一种数学模型，用于研究美国政党的意识形态极性。新模型考虑到了众所周知的唐斯模型，该模型考虑的是在一个一维所谓的意识形态空间中分布的选民群体。但是，与唐斯模型不同的是，唐斯模型假定“公民投票给意识形态上最接近的政党，而政党会调整自己的立场以最大化选票”这一新的基于微分方程的模型基于选民的概念，这些选民做出了令人满意的决定，即在选民认为满意的位置之间随机做出的决定。因此，虽然前一种方法错误地预测了双方都应收敛到中位选民的立场，但事实证明，作者的新模型能够更好地拟合经验数据。实际上，所提议模型的结果表明，“即使在选民的意识形态立场没有变化的情况下，甚至具有讽刺意味的是，“对选民的极端阶层进行呼吁也可能是一个获胜的政治策略”。本文中介绍的模型的一些扩展的参考资料，并鼓励在扩展模型时考虑将来的工作。