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Integral and fractional expectation thresholds are equivalent

OpenAI · September 23, 2026

Lean

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Abstract

We prove Talagrand's conjecture that integral and fractional expectation thresholds are within a universal constant factor, with the same covering budget.

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Collected automatically by AI tools (Claude Opus 5.5 and GPT-6 Astra, 2026-10-21) and not checked by a person. May be wrong or incomplete. Report an error.

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Formalization

  • OpenAI, Family 175 Lean scope note (lean/docs/175.md) (OpenAI Math Release, Oct 2026). States that the formalization proves $q_f(\mathcal F)\le25\cdot512^4 q(\mathcal F)$ for nonempty proper increasing families on finite nonempty ground sets, with budget $1/2$ for both covers and fractional weights allowed on the empty set, and links the comparator statement TalagrandExpectationThreshold.lean. [family-level]

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Cite

@misc{OAI:Integral-and-fractional-expectation-thresholds-are-equivalent-September-23-2026,
  author = {{OpenAI}},
  title = {{Integral and fractional expectation thresholds are equivalent}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Integral-and-fractional-expectation-thresholds-are-equivalent-September-23-2026/paper.pdf}{OAI:Integral-and-fractional-expectation-thresholds-are-equivalent-September-23-2026}},
  year = {2026}
}

Lean formalization

OpenAI provides Lean files for this family: lean/docs/175.md. The Lean statements have not been checked by people against the paper's claims.

Family 175: Talagrand’s expectation thresholds, discrete convexity, and graph decompositions

Proves that integral and fractional expectation thresholds differ by at most a universal factor, and resolves Talagrand's discrete-convexity conjecture. An application proves the Ascoli–He–Park–Talagrand graph-decomposition conjecture: every graph's edges split into a universally bounded number of fixed pieces, each with containment threshold at most a universal constant times the original graph's integral expectation threshold. The pieces' embeddings need not agree on shared vertices.

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