Exploring growing complex systems with higher-order interactions

TL;DR

This paper introduces a model for growing complex systems with higher-order interactions using simplicial complexes, analyzes their percolation properties, and reveals an infinite-order phase transition related to the emergence of giant clusters.

Contribution

It proposes a new growing random simplicial complex model and rigorously derives its percolation properties, advancing understanding of higher-order interactions in complex systems.

Findings

System exhibits an infinite-order phase transition.

Higher-order interactions accelerate system growth.

Emergence of a giant cluster is influenced by interaction complexity.

Abstract

A complex system with many interacting individuals can be represented by a network consisting of nodes and links representing individuals and pairwise interactions, respectively. However, real-world systems grow with time and include many higher-order interactions. Such systems with higher-order interactions can be well described by a simplicial complex (SC), which is a type of hypergraph, consisting of simplexes representing sets of multiple interacting nodes. Here, capturing the properties of growing real-world systems, we propose a growing random SC (GRSC) model where a node is added and a higher dimensional simplex is established among nodes at each time step. We then rigorously derive various percolation properties in the GRSC. Finally, we confirm that the system exhibits an infinite-order phase transition as higher-order interactions accelerate the growth of the system and result in the advanced emergence of a giant cluster. This work can pave the way for interpreting growing complex systems with higher-order interactions such as social, biological, brain, and technological systems.