Statistical mechanics of topological phase transitions in networks
Gergely Palla, Imre Derenyi, Illes Farkas, Tamas Vicsek

TL;DR
This paper develops a statistical mechanical framework to analyze topological phase transitions in networks, revealing diverse transition types and structural changes driven by temperature and energy functions.
Contribution
It introduces a phenomenological model assigning energy to network topologies and explores phase transitions using simulations and theoretical analysis.
Findings
Identifies various topological phase transitions with changing temperature.
Shows that energy functions influence the nature of the phase transition.
Demonstrates the emergence of scale-free graphs at critical points.
Abstract
We provide a phenomenological theory for topological transitions in restructuring networks. In this statistical mechanical approach energy is assigned to the different network topologies and temperature is used as a quantity referring to the level of noise during the rewiring of the edges. The associated microscopic dynamics satisfies the detailed balance condition and is equivalent to a lattice gas model on the edge-dual graph of a fully connected network. In our studies -- based on an exact enumeration method, Monte-Carlo simulations, and theoretical considerations -- we find a rich variety of topological phase transitions when the temperature is varied. These transitions signal singular changes in the essential features of the global structure of the network. Depending on the energy function chosen, the observed transitions can be best monitored using the order parameters…
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