A Set of Master Variables for the Two-Star Random Graph

TL;DR

This paper introduces a new method to analyze complex network structures using master variables in the two-star random graph model.

Contribution

The paper introduces master variables to control the thermodynamic limit in the two-star random graph model.

Findings

The master variables recover the mean-field solution of Park and Newman with explicit control over corrections.

The method provides a compact derivation of the Annibale–Courtney solution for sparse regimes.

The approach computes the first subleading correction to the Park–Newman result.

Abstract

The two-star random graph is the simplest exponential random graph model with nontrivial interactions between the graph edges. We propose a set of auxiliary variables that control the thermodynamic limit where the number of vertices N tends to infinity. Such ’master variables’ are usually highly desirable in treatments of ‘large N’ statistical field theory problems. For the dense regime when a finite fraction of all possible edges are filled, this construction recovers the mean-field solution of Park and Newman, but with explicit control over the 1/N corrections. We use this advantage to compute the first subleading correction to the Park–Newman result, which encodes the finite, nonextensive contribution to the free energy. For the sparse regime with a finite mean degree, we obtain a very compact derivation of the Annibale–Courtney solution, originally developed with the use of functional integrals, which is comfortably bypassed in our treatment.

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