Null models for multi-optimized large-scale network structures

TL;DR

This paper investigates how multiple selective pressures influence large-scale network structures by constructing null models, revealing diverse optimized configurations and interactions between modularity and robustness.

Contribution

It introduces maximum-entropy null models to isolate effects of joint optimization on network structure, uncovering a rich phase diagram of patterns and their interactions.

Findings

Diverse optimized structures including modular, core-periphery, and bipartite patterns.

Parameter regions where optimization criteria act synergistically or antagonistically.

Interactions between selective pressures significantly shape network architecture.

Abstract

We study the emerging large-scale structures in networks subject to selective pressures that simultaneously drive towards higher modularity and robustness against random failures. We construct maximum-entropy null models that isolate the effects of the joint optimization on the network structure from any kind of evolutionary dynamics. Our analysis reveals a rich phase diagram of optimized structures, composed of many combinations of modular, core-periphery and bipartite patterns. Furthermore, we observe parameter regions where the simultaneous optimization can be either synergistic or antagonistic, with the improvement of one criterion directly aiding or hindering the other, respectively. Our results show how interactions between different selective pressures can be pivotal in determining the emerging network structure, and that these interactions can be captured by simple network models.