Complex Networks in and beyond Physics

TL;DR

This paper explores the application of complex network theory across various disciplines, highlighting its role in understanding diverse systems from physics to social sciences and biology, and emphasizing interdisciplinary insights.

Contribution

It reviews how physics-inspired complexity theories are applied to analyze complex systems in multiple fields, fostering cross-disciplinary research and new conceptual developments.

Findings

Complex networks provide a unifying framework for diverse scientific phenomena.

Interdisciplinary applications of complexity theory lead to novel insights in social and biological systems.

Mathematical structures in complexity help model vague human goals in socio-cognitive systems.

Abstract

Physicists study a wide variety of phenomena creating new interdisciplinary research fields by applying theories and methods originally developed in physics in order to solve problems in economics, social science, biology, medicine, technology, etc. In their turn, these different branches of science inspire the invention of new concepts in physics. A basic tool of analysis, in such a context, is the mathematical theory of complexity concerned with the study of complex systems including human economies, climate, nervous systems, cells and living things, including human beings, as well as modern energy or communication infrastructures which are all networks of some kind. Recently, complexity has become a natural domain of interest of the real world socio-cognitive systems, linguistics, and emerging systemics research. The phenomena to be studied and understood arise from neither the physical laws nor the abstraction of mathematics. The challenge is to discern and formulate plausible mathematical structures to describe problems that represent vague human goals.