适航性
计算机科学
网络拓扑
复杂网络
测地线
理论计算机科学
排名(信息检索)
复杂系统
网络理论
人工智能
航程(航空)
数学
计算机网络
万维网
数学分析
统计
材料科学
地图学
复合材料
地理
作者
Ernesto Estrada,Jesús Gómez‐Gardeñes,Lucas Lacasa
标识
DOI:10.1073/pnas.2305001120
摘要
Real-world networks are neither regular nor random, a fact elegantly explained by mechanisms such as the Watts–Strogatz or the Barabási-Albert models, among others. Both mechanisms naturally create shortcuts and hubs, which while enhancing the network’s connectivity, also might yield several undesired navigational effects: They tend to be overused during geodesic navigational processes—making the networks fragile—and provide suboptimal routes for diffusive-like navigation. Why, then, networks with complex topologies are ubiquitous? Here, we unveil that these models also entropically generate network bypasses: alternative routes to shortest paths which are topologically longer but easier to navigate. We develop a mathematical theory that elucidates the emergence and consolidation of network bypasses and measure their navigability gain. We apply our theory to a wide range of real-world networks and find that they sustain complexity by different amounts of network bypasses. At the top of this complexity ranking we found the human brain, which points out the importance of these results to understand the plasticity of complex systems.
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