The Griffiths-Hurst-Sherman inequality for exponential random graphs: a counterexample to a conjecture and the case of chosen graphs with at most two edges

An exponential random graph is a Gibbs measure on the graphs with n labeled vertices. Its Hamiltonian is $n^{2}$ times a linear combination of the homomorphism densities of chosen finite graphs, one of which is the graph $K_{2}$ with one edge. The coefficients of the combination are the parameters of the model. The GHS inequality, which Griffiths, Hurst and Sherman proved for Ising ferromagnets with pair interactions in a nonnegative field, states for an exponential random graph that the third joint cumulant of any three edge indicators is nonpositive. Bianchi, Collet and Magnanini proved the GHS inequality in a region of the parameters of the two-star model, whose chosen graphs are $K_{2}$ and a path with two edges. For a general exponential random graph whose parameters other than that of $K_{2}$ are nonnegative, they showed that the inequality fails when the probability of an edge, which is the same for all edges, is below $1/2$, and conjectured that it holds whenever that probability is at least $1/2$. We show that, whenever a chosen graph H has at least three edges, the conjecture fails even when every chosen graph other than $K_{2}$ and H has parameter 0. When the chosen graphs are $K_{2}$ and H, and n is at least the number of vertices of H, the probability of an edge is at least $1/2$ at every nonnegative parameter of $K_{2}$ and every positive parameter of H, whereas the inequality fails at every nonnegative parameter of $K_{2}$ when the parameter of H is positive and below a bound that depends on n and on the parameter of $K_{2}$. There is also an explicit bound, which does not depend on n, such that, at every positive parameter of H below it, the inequality fails for every large n at some parameter of $K_{2}$ at which the probability of an edge exceeds $1/2$. When every chosen graph has at most two edges and the parameters other than that of $K_{2}$ are nonnegative, the model is an Ising ferromagnet with pair interactions in a uniform field that is nonnegative exactly when the probability of an edge is at least $1/2$, so the conjecture holds by the inequality of Griffiths, Hurst and Sherman. For the two-star model with a nonnegative parameter of the path, that field is a linear function of the two parameters, so the GHS inequality holds exactly on one side of an explicit line.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-27
DOI
https://doi.org/10.5281/zenodo.23693535
Primary Topic
Stochastic processes and statistical mechanics
Type
preprint
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preprint

The Griffiths-Hurst-Sherman inequality for exponential random graphs: a counterexample to a conjecture and the case of chosen graphs with at most two edges

Sungwoo Kang
Zenodo (CERN European Organization for Nuclear Research)
Stochastic processes and statistical mechanics
preprint

The Griffiths-Hurst-Sherman inequality for exponential random graphs: a counterexample to a conjecture and the case of chosen graphs with at most two edges

Sungwoo Kang
preprint en

Abstract

An exponential random graph is a Gibbs measure on the graphs with n labeled vertices. Its Hamiltonian is $n^{2}$ times a linear combination of the homomorphism densities of chosen finite graphs, one of which is the graph $K_{2}$ with one edge. The coefficients of the combination are the parameters of the model. The GHS inequality, which Griffiths, Hurst and Sherman proved for Ising ferromagnets with pair interactions in a nonnegative field, states for an exponential random graph that the third joint cumulant of any three edge indicators is nonpositive. Bianchi, Collet and Magnanini proved the GHS inequality in a region of the parameters of the two-star model, whose chosen graphs are $K_{2}$ and a path with two edges. For a general exponential random graph whose parameters other than that of $K_{2}$ are nonnegative, they showed that the inequality fails when the probability of an edge, which is the same for all edges, is below $1/2$, and conjectured that it holds whenever that probability is at least $1/2$. We show that, whenever a chosen graph H has at least three edges, the conjecture fails even when every chosen graph other than $K_{2}$ and H has parameter 0. When the chosen graphs are $K_{2}$ and H, and n is at least the number of vertices of H, the probability of an edge is at least $1/2$ at every nonnegative parameter of $K_{2}$ and every positive parameter of H, whereas the inequality fails at every nonnegative parameter of $K_{2}$ when the parameter of H is positive and below a bound that depends on n and on the parameter of $K_{2}$. There is also an explicit bound, which does not depend on n, such that, at every positive parameter of H below it, the inequality fails for every large n at some parameter of $K_{2}$ at which the probability of an edge exceeds $1/2$. When every chosen graph has at most two edges and the parameters other than that of $K_{2}$ are nonnegative, the model is an Ising ferromagnet with pair interactions in a uniform field that is nonnegative exactly when the probability of an edge is at least $1/2$, so the conjecture holds by the inequality of Griffiths, Hurst and Sherman. For the two-star model with a nonnegative parameter of the path, that field is a linear function of the two parameters, so the GHS inequality holds exactly on one side of an explicit line.

Zenodo (CERN European Organization for Nuclear Research)
Stochastic processes and statistical mechanics
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