Hyperbolic Random Graphs: Clique Number and Degeneracy with Implications for Colouring

TL;DR

This paper analyzes hyperbolic random graphs, providing bounds on their clique number and degeneracy, and introduces an approximation algorithm for coloring these graphs, bridging the gap between theory and practice.

Contribution

It characterizes degeneracy parameters for approximation algorithms, offers new bounds on clique numbers, and compares properties with related geometric random graph models.

Findings

Degeneracy-based greedy algorithms have bounded approximation ratios.

An improved upper bound on the clique number of hyperbolic random graphs.

The core of HRGs does not contain the largest clique.

Abstract

Hyperbolic random graphs inherit many properties that are present in real-world networks. The hyperbolic geometry imposes a scale-free network with a strong clustering coefficient. Other properties like a giant component, the small world phenomena and others follow. This motivates the design of simple algorithms for hyperbolic random graphs. In this paper we consider threshold hyperbolic random graphs (HRGs). Greedy heuristics are commonly used in practice as they deliver a good approximations to the optimal solution even though their theoretical analysis would suggest otherwise. A typical example for HRGs are degeneracy-based greedy algorithms [Bl\"asius, Fischbeck; Transactions of Algorithms '24]. In an attempt to bridge this theory-practice gap we characterise the parameter of degeneracy yielding a simple approximation algorithm for colouring HRGs. The approximation ratio of our algorithm ranges from $(2/\sqrt{3})$ to $4/3$ depending on the power-law exponent of the model. We complement our findings for the degeneracy with new insights on the clique number of hyperbolic random graphs. We show that degeneracy and clique number are substantially different and derive an improved upper bound on the clique number. Additionally, we show that the core of HRGs does not constitute the largest clique. Lastly we demonstrate that the degeneracy of the closely related standard model of geometric inhomogeneous random graphs behaves inherently different compared to the one of hyperbolic random graphs.