Turing patterns in simplicial complexes

图灵 简单复形 图案形成 图灵机 单纯形 计算机科学 成对比较 统计物理学 组合数学 数学 物理 人工智能 生物 算法 计算 遗传学 程序设计语言
作者
Shupeng Gao,Lili Chang,Matjaž Perc,Zhen Wang
出处
期刊:Physical review [American Physical Society]
卷期号:107 (1) 被引量:45
标识
DOI:10.1103/physreve.107.014216
摘要

The spontaneous emergence of patterns in nature, such as stripes and spots, can be mathematically explained by reaction-diffusion systems. These patterns are often referred as Turing patterns to honor the seminal work of Alan Turing in the early 1950s. With the coming of age of network science, and with its related departure from diffusive nearest-neighbor interactions to long-range links between nodes, additional layers of complexity behind pattern formation have been discovered, including irregular spatiotemporal patterns. Here we investigate the formation of Turing patterns in simplicial complexes, where links no longer connect just pairs of nodes but can connect three or more nodes. Such higher-order interactions are emerging as a new frontier in network science, in particular describing group interaction in various sociological and biological systems, so understanding pattern formation under these conditions is of the utmost importance. We show that a canonical reaction-diffusion system defined over a simplicial complex yields Turing patterns that fundamentally differ from patterns observed in traditional networks. For example, we observe a stable distribution of Turing patterns where the fraction of nodes with reactant concentrations above the equilibrium point is exponentially related to the average degree of 2-simplexes, and we uncover parameter regions where Turing patterns will emerge only under higher-order interactions, but not under pairwise interactions.
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