Nicosia Vincenzo, Skardal Per Sebastian, Arenas Alex, Latora Vito
School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom.
Department of Mathematics, Trinity College, Hartford, Connecticut 06106, USA.
Phys Rev Lett. 2017 Mar 31;118(13):138302. doi: 10.1103/PhysRevLett.118.138302.
We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.
我们引入了一个框架，使用多层网络方法将不同性质的动力学过程交织在一起，每个过程都有其独特的网络拓扑结构。作为多个动力学过程相互作用产生的集体现象的一个例子，我们研究了一个模型，其中神经动力学和营养物质运输双向耦合，使得一层的运输过程分配取决于另一层的同步程度，反之亦然。我们通过数值展示并通过解析证明，多层耦合会引发自发的爆炸性同步和分配的异质性分布，而在分别考虑的两个系统中则不存在这种情况。我们的框架可应用于其他案例，其中两个或更多动力学过程，如同步、观点形成、信息扩散或疾病传播，正在相互作用。
