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引导复杂网络朝着期望的动态发展。

Steering complex networks toward desired dynamics.

机构信息

Complex Systems Interdisciplinary Group (GISC), Department of Mathematics, Universidad Carlos III de Madrid, 28911, Leganés, Madrid, Spain.

CNR, Institute of Complex Systems, Via Madonna del Piano 10, 50019, Florence, Italy.

出版信息

Sci Rep. 2020 Nov 27;10(1):20744. doi: 10.1038/s41598-020-77663-1.

Abstract

We consider networks of dynamical units that evolve in time according to different laws, and are coupled to each other in highly irregular ways. Studying how to steer the dynamics of such systems towards a desired evolution is of great practical interest in many areas of science, as well as providing insight into the interplay between network structure and dynamical behavior. We propose a pinning protocol for imposing specific dynamic evolutions compatible with the equations of motion on a networked system. The method does not impose any restrictions on the local dynamics, which may vary from node to node, nor on the interactions between nodes, which may adopt in principle any nonlinear mathematical form and be represented by weighted, directed or undirected links. We first explore our method on small synthetic networks of chaotic oscillators, which allows us to unveil a correlation between the ordered sequence of pinned nodes and their topological influence in the network. We then consider a 12-species trophic web network, which is a model of a mammalian food web. By pinning a relatively small number of species, one can make the system abandon its spontaneous evolution from its (typically uncontrolled) initial state towards a target dynamics, or periodically control it so as to make the populations evolve within stipulated bounds. The relevance of these findings for environment management and conservation is discussed.

摘要

我们考虑的是根据不同规律随时间演化的动力学单元网络,它们以高度不规则的方式相互耦合。研究如何将这些系统的动力学引导到期望的演化方向,在科学的许多领域都具有重要的实际意义,同时也为了解网络结构和动力学行为之间的相互作用提供了线索。我们提出了一种钉扎协议,用于对网络系统施加与运动方程兼容的特定动态演化。该方法不对局部动力学施加任何限制,局部动力学可以随节点而变化,也不对节点之间的相互作用施加任何限制,节点之间的相互作用原则上可以采用任何非线性数学形式,并通过加权、有向或无向链接来表示。我们首先在小的混沌振荡器合成网络上探索我们的方法,这使我们能够揭示出被钉扎节点的有序序列与其在网络中的拓扑影响之间的相关性。然后,我们考虑一个 12 种物质的营养网络,它是哺乳动物食物网的模型。通过钉扎相对较少的物种,可以使系统放弃从其(通常是不受控制的)初始状态自发演化到目标动力学,或者周期性地控制它,以使种群在规定的范围内演化。讨论了这些发现对环境管理和保护的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d174/7695727/d84eee2769a1/41598_2020_77663_Fig1_HTML.jpg

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