English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We introduce network $L$-cloning, a technique for creating ensembles ofrandom networks from any given real-world or artificial network. Each member ofthe ensemble is an $L$-cloned network constructed from $L$ copies of theoriginal network. The degree distribution of an $L$-cloned network and, moreimportantly, the degree-degree correlation between and beyond nearest neighborsare identical to those of the original network. The density of triangles in an\LC network, and hence its clustering coefficient, is reduced by a factor of$L$ compared to those of the original network. Furthermore, the density ofloops of any fixed length approaches zero for sufficiently large values of $L$.Other variants of $L$-cloning allow us to keep intact the short loops ofcertain lengths. As an application, we employ these network cloning methods toinvestigate the effect of short loops on dynamical processes running onnetworks and to inspect the accuracy of corresponding tree-based theories. Wedemonstrate that dynamics on $L$-cloned networks (with sufficiently large $L$)are accurately described by the so-called adjacency tree-based theories,examples of which include the message passing technique, some pairapproximation methods, and the belief propagation algorithm used respectivelyto study bond percolation, SI epidemics, and the Ising model.

Network cloning unfolds the effect of clustering on dynamical processes