The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Controlling edge dynamics in complex networks
Open accessAbstract
The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the past decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges of a network, and demonstrate that the controllability properties of this process significantly differ from simple nodal dynamics. Evaluation of real-world networks indicates that most of them are more controllable than their randomized counterparts. We also find that transcriptional regulatory networks are particularly easy to control. Analytic calculations show that networks with scale-free degree distributions have better controllability properties than uncorrelated networks, and positively correlated in- and out-degrees enhance the controllability of the proposed dynamics. Surprisingly little is known about how network dynamics might be controlled, despite extensive research into how they behave. A study of the controllability of network edge dynamics reveals that it differs from that of nodal dynamics, and that real-world networks are easier to control than their random counterparts.
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Metadata
- Authors
- Nepusz, T., & Vicsek, T.
- Venue
- Nature Physics
- Published
- 2012-05-27
- Volume
- 8
- Issue
- 7
- Pages
- 568-573
- ISSN
- 1745-2473 (ISSN-L)
- 1745-2481
- OpenAlex
- W2092994772
- Cited by
- 430
- References
- 10
- FWCI
- 30.65
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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