Diffusion capacity of single and interconnected networks

Tiago A. Schieber, Laura C. Carpi, Panos M. Pardalos, Cristina Masoller, Albert Díaz-Guilera and Martín G. Ravetti ()
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Tiago A. Schieber: Universidade Federal de Minas Gerais
Laura C. Carpi: CEFET-MG
Panos M. Pardalos: University of Florida
Cristina Masoller: Universitat Politècnica de Catalunya
Albert Díaz-Guilera: Universitat de Barcelona
Martín G. Ravetti: Universidade Federal de Minas Gerais

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: 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.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37323-0

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DOI: 10.1038/s41467-023-37323-0

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