Problem detail · source-aware

Erdos Problem #731

partialconfidence 70%

VibeMathed reports this item as partial. VibeMath preserves that report as a source assertion and has not independently authored a plain-language mathematical explanation.

Precise statement

Let $A(n)$ be the least positive integer not dividing $\binom{2n}{n}$. Erdos asked for the behaviour of $A(n)$ for reasonable $n$. Under an explicit dyadic-regularity formalization of reasonable, the distribution is determined on dyadic intervals against the scale $F_X = \sqrt{2}(\log 2)^{1/4} L^{1/4} \exp\sqrt{(\log 2)L}$ with $L = \log(2X)$.

The source statement is reproduced for indexing with attribution. Mathematical correctness requires domain-expert or mechanical review. VibeMath has not independently audited statement fidelity, correctness, priority, or novelty.

What AI did

ChatGPT, Aristotle

The declaration says large language models, primarily ChatGPT, were used extensively throughout the research while the author originated the ideas, and that the accompanying Lean formalization was developed by the author with Aristotle.

Provider: OpenAI / Harmonic · Prompt public: unknown · Independence: unknown

Verification boundary

unreviewed

A Lean formalization accompanies the paper; we have not compiled it. The result is conditional on the paper's own formalization of Erdos's informal word 'reasonable', which the entry's resolution status reflects. arXiv preprint, not peer-reviewed.

Correctness: unknown · statement fidelity: unaudited · peer review: none

Timeline

  1. arXiv:2606.29062 - A Resolution of Erdos Problem 731 under Dyadic Regularity

    resolved under an explicit formalization of 'reasonable', not in full generality

Known method families

argument (source-reported)

Source-reported tools: argument.

Independent: unknown · difference confidence: 0

What remains uncertain

VibeMath has not independently audited the mathematical statement, proof, or novelty claim.

  • VibeMath has not independently verified the mathematical claim.
  • AI-attempt independence and training-data exposure are unknown unless explicitly documented.
  • VibeMath has not independently audited the mathematical statement, proof, or novelty claim.