Nearest-neighbor directed random hyperbolic graphs

I.A. Kasyanov, P. van der Hoorn, D. Krioukov, M.V. Tamm (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

153 Downloads (Pure)

Abstract

Undirected hyperbolic graph models have been extensively used as models of scale-free small-world networks with high clustering coefficient. Here we presented a simple directed hyperbolic model where nodes randomly distributed on a hyperbolic disk are connected to a fixed number m of their nearest spatial neighbors. We introduce also a canonical version of this network (which we call "network with varied connection radius"), where maximal length of outgoing bond is space dependent and is determined by fixing the average out-degree to m. We study local bond length, in-degree, and reciprocity in these networks as a function of spacial coordinates of the nodes and show that the network has a distinct core-periphery structure. We show that for small densities of nodes the overall in-degree has a truncated power-law distribution. We demonstrate that reciprocity of the network can be regulated by adjusting an additional temperature-like parameter without changing other global properties of the network.

Original languageEnglish
Article number054310
Number of pages19
JournalPhysical Review E
Volume108
Issue number5
DOIs
Publication statusPublished - Nov 2023

Funding

The authors are grateful to M.Á. Serrano, P. Krapivsky, S. Nechaev, K. Polovnikov, and M. Schich for stimulating discussions. This work was partially supported by CUDAN ERA Chair project (Grant No. 810961 of the EU Horizon 2020 program) and NSF Grant No. IIS-1741355.

FundersFunder number
European Union's Horizon 2020 - Research and Innovation Framework Programme
National Science FoundationIIS-1741355

    Fingerprint

    Dive into the research topics of 'Nearest-neighbor directed random hyperbolic graphs'. Together they form a unique fingerprint.

    Cite this