First-passage times to quantify and compare structural correlations and heterogeneity in complex systems
Quantifying heterogeneity and correlations in complex systems consisting of a large number of interacting elements is key to understand their emergent properties. Here, the authors propose a method based on the statistics of interclass mean first passage times or random walks, and use it to quantify...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/fcefc73cb2c94819a23837de6fe3c25a |
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| Sumario: | Quantifying heterogeneity and correlations in complex systems consisting of a large number of interacting elements is key to understand their emergent properties. Here, the authors propose a method based on the statistics of interclass mean first passage times or random walks, and use it to quantify in a non-parametric way the level of heterogeneity and the presence of correlations in multiscale complex systems, where nodes are associated to a discrete number of classes. |
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