Network bypasses sustain complexity

Estrada, Ernesto ; Gómez-Gardeñes, Jesús (Universidad de Zaragoza) ; Lacasa, Lucas

Resumen: 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.

Idioma: Inglés

DOI: 10.1073/pnas.2305001120

Año: 2023

Publicado en: Proceedings of the National Academy of Sciences of the United States of America 120, 31 (2023), 2305001120 [10 pp.]
ISSN: 0027-8424

Factor impacto JCR: 9.4 (2023)

Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 13 / 134 = 0.097 (2023) - Q1 - T1

Factor impacto CITESCORE: 19.0 - Multidisciplinary (Q1)

Factor impacto SCIMAGO: 3.737 - Multidisciplinary (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL
Financiación: info:eu-repo/grantAgreement/ES/MCIU/PID2019-107603GB-I00
Financiación: info:eu-repo/grantAgreement/ES/MICINN/CEX2021-001164-M
Financiación: info:eu-repo/grantAgreement/ES/MCINN/EUR2021-122067
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-113582GB-I00
Financiación: info:eu-repo/grantAgreement/ES/MCINN/PID2020-114324GB-C22

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Física Materia Condensada (Dpto. Física Materia Condensa.)