A reverse Sidorenko inequality
Ashwin Sah, Mehtaab Sawhney, David Stoner, Yufei Zhao

TL;DR
This paper establishes new inequalities for weighted graph homomorphisms, providing tight bounds on partition functions of models like Ising and Potts, and characterizes extremal graphs in various settings.
Contribution
It introduces a reverse Sidorenko inequality for triangle-free graphs, generalizes graphical Brascamp-Lieb inequalities, and characterizes extremal graphs for homomorphism counts and partition functions.
Findings
Proves a reverse Sidorenko inequality for triangle-free graphs.
Establishes tight upper bounds on partition functions of statistical models.
Characterizes extremal graphs for homomorphism counts in various models.
Abstract
Let be a graph allowing loops as well as vertex and edge weights. We prove that, for every triangle-free graph without isolated vertices, the weighted number of graph homomorphisms satisfies the inequality \[ \hom(G, H ) \le \prod_{uv \in E(G)} \hom(K_{d_u,d_v}, H )^{1/(d_ud_v)}, \] where denotes the degree of vertex in . In particular, one has \[ \hom(G, H )^{1/|E(G)|} \le \hom(K_{d,d}, H )^{1/d^2} \] for every -regular triangle-free . The triangle-free hypothesis on is best possible. More generally, we prove a graphical Brascamp-Lieb type inequality, where every edge of is assigned some two-variable function. These inequalities imply tight upper bounds on the partition function of various statistical models such as the Ising and Potts models, which includes independent sets and graph colorings. For graph colorings, corresponding to $H…
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