### Abstract

In this paper, we study the maximum clique problem on hyperbolic random graphs. A hyperbolic random graph is a mathematical model for analyzing scale-free networks since it effectively explains the power-law degree distribution of scale-free networks. We propose a simple algorithm for finding a maximum clique in hyperbolic random graph. We first analyze the running time of our algorithm theoretically. We can compute a maximum clique on a hyperbolic random graph G in O(m + n^{4.5(1-α)}) expected time if a geometric representation is given or in O(m + n^{6(1-α)}) expected time if a geometric representation is not given, where n and m denote the numbers of vertices and edges of G, respectively, and α denotes a parameter controlling the power-law exponent of the degree distribution of G. Also, we implemented and evaluated our algorithm empirically. Our algorithm outperforms the previous algorithm [BFK18] practically and theoretically. Beyond the hyperbolic random graphs, we have experiment on real-world networks. For most of instances, we get large cliques close to the optimum solutions efficiently.

### BibTeX - Entry

`@InProceedings{oh_et_al:LIPIcs.ESA.2023.85,
author = {Oh, Eunjin and Oh, Seunghyeok},
title = {{Algorithms for Computing Maximum Cliques in Hyperbolic Random Graphs}},
booktitle = {31st Annual European Symposium on Algorithms (ESA 2023)},
pages = {85:1--85:15},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-295-2},
ISSN = {1868-8969},
year = {2023},
volume = {274},
editor = {G{\o}rtz, Inge Li and Farach-Colton, Martin and Puglisi, Simon J. and Herman, Grzegorz},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18738},
URN = {urn:nbn:de:0030-drops-187384},
doi = {10.4230/LIPIcs.ESA.2023.85},
annote = {Keywords: Maximum cliques, hyperbolic random graphs}
}`