Problem detail · source-aware

Erdős Problem #856

candidateconfidence 50%

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

Precise statement

Let $k\geq 3$ and $f_k(N)$ be the maximum of $\sum_{n\in A}\frac{1}{n}$ over all $A\subseteq\{1,\ldots,N\}$ containing no $k$ subsets with the same pairwise least common multiple. Estimate $f_k(N)$. The claimed answer: $f_k(N)=(\log N)^{\gamma_k+o(1)}$, where $\gamma_k$ is a weighted generalization of the Tang-Zhang sunflower capacity.

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

GPT-5.4 Pro

A weighted version of the Tang-Zhang sunflower-capacity argument giving the exact logarithmic exponent was developed with GPT-5.4 Pro, using a mass-transport idea from the forum's discussion of problem #1196.

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

Verification boundary

unreviewed

An AI screening found no issues and no prior literature with the result; the site's owner unpacked and restated the main claim without checking details, a Lean formalization attempt hit missing mathlib prerequisites, and the problem is still listed open.

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

Timeline

  1. erdosproblems.com/856

    Identifies the exponent as a variational sunflower-capacity constant, sharpening the Tang-Zhang bounds; the value of that constant itself remains open, as does site acceptance

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.

  • The source status is candidate and must not be represented as solved.
  • 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.