Amb motiu del tancament d'estiu, la validació de documents es reprendrà a partir del 28 d'agost de 2026. Disculpeu les molèsties.
Con motivo del cierre de verano, la validación de documentos se reanudará a partir del 28 de agosto de 2026. Disculpad las molestias
Due to the summer closure, document validation will resume starting August 28, 2026. We apologize for any inconvenience.

Document type

Article

Version

Published version

Publication date

Publication license

cc-by-nc-nd (c) Kouvaris, Nikos E. et al., 2015
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/67783

Pattern formation in multiplex networks

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

The advances in understanding complex networks have generated increasing interest in dynamical processes occurring on them. Pattern formation in activator-inhibitor systems has been studied in networks, revealing differences from the classical continuous media. Here we study pattern formation in a new framework, namely multiplex networks. These are systems where activator and inhibitor species occupy separate nodes in different layers. Species react across layers but diffuse only within their own layer of distinct network topology. This multiplicity generates heterogeneous patterns with significant differences from those observed in single-layer networks. Remarkably, diffusion-induced instability can occur even if the two species have the same mobility rates; condition which can never destabilize single-layer networks. The instability condition is revealed using perturbation theory and expressed by a combination of degrees in the different layers. Our theory demonstrates that the existence of such topology-driven instabilities is generic in multiplex networks, providing a new mechanism of pattern formation.

Citation

Citation

KOUVARIS, Nikos E., HATA, S. and DÍAZ GUILERA, Albert. Pattern formation in multiplex networks. Scientific Reports. 2015. Vol. 5, num. 10840, pags. 1-9. ISSN 2045-2322. [consulted: 15 of August of 2026]. Available at: https://hdl.handle.net/2445/67783

Export metadata

JSON - METS

Share record