Autor: |
Tiago A. Schieber, Laura C. Carpi, Panos M. Pardalos, Cristina Masoller, Albert Díaz-Guilera, Martín G. Ravetti |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023) |
Druh dokumentu: |
article |
ISSN: |
2041-1723 |
DOI: |
10.1038/s41467-023-37323-0 |
Popis: |
Abstract Understanding diffusive processes in networks is a significant challenge in complexity science. Networks possess a diffusive potential that depends on their topological configuration, but diffusion also relies on the process and initial conditions. This article presents Diffusion Capacity, a concept that measures a node’s potential to diffuse information based on a distance distribution that considers both geodesic and weighted shortest paths and dynamical features of the diffusion process. Diffusion Capacity thoroughly describes the role of individual nodes during a diffusion process and can identify structural modifications that may improve diffusion mechanisms. The article defines Diffusion Capacity for interconnected networks and introduces Relative Gain, which compares the performance of a node in a single structure versus an interconnected one. The method applies to a global climate network constructed from surface air temperature data, revealing a significant change in diffusion capacity around the year 2000, suggesting a loss of the planet’s diffusion capacity that could contribute to the emergence of more frequent climatic events. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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