Scale-free graphs with many edges

Clara Stegehuis; Bert Zwart

doi:10.1214/23-ECP567

Scale-free graphs with many edges

Clara Stegehuis
, Bert Zwart

Mathematics of Operations Research

Research output: Contribution to journal › Article › Academic › peer-review

3 Citations (Scopus)

62 Downloads (Pure)

Abstract

We develop tail estimates for the number of edges in a Chung-Lu random graph with regularly varying weight distribution. Our results show that the most likely way to have an unusually large number of edges is through the presence of one or more hubs, i.e. vertices with degree of order n.

Original language	English
Article number	62
Journal	Electronic Communications in Probability
Volume	28
DOIs	https://doi.org/10.1214/23-ECP567
Publication status	Published - 2023

Keywords

large deviations
power law
random graphs

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10.1214/23-ECP567Licence: CC BY

23-ECP567Final published version, 335 KBLicence: CC BY

Cite this

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AB - We develop tail estimates for the number of edges in a Chung-Lu random graph with regularly varying weight distribution. Our results show that the most likely way to have an unusually large number of edges is through the presence of one or more hubs, i.e. vertices with degree of order n.

KW - large deviations

KW - power law

KW - random graphs

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DO - 10.1214/23-ECP567

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VL - 28

JO - Electronic Communications in Probability

JF - Electronic Communications in Probability

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Scale-free graphs with many edges

Abstract

Keywords

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