Statistical Thermodynamics of Clustered Populations

Abstract

We present a thermodynamic theory for a generic population of $M$ individuals distributed into $N$ groups (clusters). We construct the ensemble of all distributions with fixed $M$ and $N$, introduce a selection functional that embodies the physics that governs the population, and obtain the distribution that emerges in the scaling limit as the most probable among all distributions consistent with the given physics. We develop the thermodynamics of the ensemble and establish a rigorous mapping to thermodynamics. We treat the emergence of a so-called "giant component" as a formal phase transition and show that the criteria for its emergence are entirely analogous to the equilibrium conditions in molecular systems. We demonstrate the theory by an analytic model and confirm the predictions by Monte Carlo simulation.

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References in corpus (4)

• Epidemic spreading in scale-free networks
• The spread of epidemic disease on networks
• Random graphs with clustering
• Percolation in living neural networks

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• Coalescense with arbitrary-parameter kernels and monodisperse initial conditions: A study within combinatorial framework