Communicability and multipartite structures in complex networks at negative absolute temperatures

TL;DR

This paper introduces a novel method using communicability at negative temperatures to identify multi-partite structures in complex networks, enhancing understanding of their underlying subgraph organization.

Contribution

It presents a new approach leveraging negative-temperature communicability to detect multi-partite subgraphs, extending previous community detection methods.

Findings

Method successfully identifies multi-partite structures in real networks.

Communicability at negative temperature distinguishes inter- and intra-community links.

Application to food webs and protein networks demonstrates practical relevance.

Abstract

We here present a method of clearly identifying multi-partite subgraphs in a network. The method is based on a recently introduced concept of the communicability, which very clearly identifies communities in a complex network. We here show that, while the communicability at a positive temperature is useful in identifying communities, the communicability at a negative temperature is useful in idenfitying multi-partitite subgraphs; the latter quantity between two nodes is positive when the two nodes belong to the same subgraph and is negative when not. The method is able to discover `almost' multi-partite structures, where inter-community connections vastly outweigh intracommunity connections. We illustrate the relevance of this work to real-life food web and protein-protein interaction networks.