Sidorenko's Inequality for Bipartite Graphs
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Definitions and mathematical statement
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For every bipartite graph $H$ and graph $G$, does Sidorenko's inequality $$t_H(G)\geq t_{K_2}(G)^{|E(H)|}$$ hold?Formulation references: [S1], [S2].
Short English statement
For every bipartite graph $H$ and graph $G$, does Sidorenko's inequality $$t_H(G)\geq t_{K_2}(G)^{|E(H)|}$$ hold?Sources
- S1 ULAM.AI and the UnsolvedMath Contributors, UnsolvedMath: A Curated Collection of Open Mathematics Problems, record 30002459 (OWR-12861-004). Catalogue attribution under CC BY 4.0. https://huggingface.co/datasets/ulamai/UnsolvedMath.
- S2 Original problem formulation and mathematical context. https://doi.org/10.4171/owr/2014/01.
Statement licence: CC-BY-SA-4.0 · Source file
Contributions 1
OpenAI claim summary for Math-2394
Sidorenko and forcing counterexamples: The explicit finite bipartite graph H and host G satisfy t(H,G)<t(K_2,G)^e(H). Passing to the associated step graphon also refutes the graphon formulation.
The claimed counterexample lies within the question’s hypotheses and contradicts its universal conclusion.
Sidorenko's Inequality for Bipartite Graphs
OpenAI's claim
Sidorenko and forcing counterexamples: A connected bipartite graph with 35 vertices and 66 edges is claimed to violate Sidorenko’s homomorphism-density lower bound in a finite host. The same pattern is also claimed not to force quasirandomness when the edge and pattern densities match their random values.Mathematical statement of the claimed result
Mathematical claim 1.
Let $H$ be the incidence graph of the explicitly tabulated $22$ triples on $13$ points: it is connected and bipartite with $35$ vertices and $66$ edges. For $t(H,G)=\operatorname{hom}(H,G)/|V(G)|^{35}$ and $p(G)=2|E(G)|/|V(G)|^2$, a finite simple graph $G$ with $p(G)>0$ is claimed to satisfy $t(H,G)<p(G)^{66}$. Moreover, for every $c>0$ another graph $F$ has $0<t(K_2,F)$ and $t(H,F)<c\,p(F)^{66}$. The forcing corollary claims some $p\in(0,1)$ and a nonconstant symmetric measurable graphon $W:[0,1]^2\to[0,1]$ with \[t(K_2,W)=p,\qquad t(H,W)=p^{66},\qquad t(H,W)=\int_{[0,1]^{35}}\prod_{ij\in E(H)}W(x_i,x_j)\,dx.\] Thus equality at that density does not force this cyclic bipartite graph to be quasirandom.Outline of the argument
Sidorenko and forcing counterexamples: The construction combines rank and discriminant relations for symmetric matrices with counts of symplectic intersections. Quadratic Gauss-sum estimates control joint signs, while type scores distinguish the desired vertex roles. Singular configurations are estimated separately so that the signed rank-layer correlations survive normalization and transfer to a finite host graph.Formal verification
Family 161 describes Lean coverage for the fixed-pattern Sidorenko deficit; the forcing consequence is not selected.Sidorenko and forcing counterexamples: The manuscript links SidorenkoCounterexample.lean.
The documented selection includes this manuscript’s main assertion; that assertion retains the restrictions stated above.
This site has not run the Lean development. These links describe OpenAI’s selected formal statements and should be read with their stated scope.
Status caveat
OpenAI reports that an internal model produced the manuscripts. Their arguments have not been independently verified as proofs by this site. Any portion outside the documented formal scope may contain mistakes, and the catalogue label reports the announced mathematical claim.Sources
- OpenAI, A counterexample to Sidorenko's conjecture, 2026-09-23; citation key
OAI:A-counterexample-to-Sidorenkos-conjecture-September-23-2026. PDF (GitHub); PDF (direct); Manuscript page and citation; Latest version; Statement source: thm:main; Statement source: cor:amplification; Statement source: cor:forcing. - Family 161: Lean scope.
- Comparator SidorenkoCounterexample.json.
- Comparator SidorenkoCounterexample.lean.
- OpenAI catalogue entry.