Erdős Problem #684 — For 0≤k≤n0\leq k\leq n write (nk)=uv\binom{n}{k} = uv where the only primes dividing uu are in [2,k][2,k] and the only primes dividing vv are in (k,n](k,n].

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For 0≤k≤n0\leq k\leq n write (nk)=uv\binom{n}{k} = uv where the only primes dividing uu are in [2,k][2,k] and the only primes dividing vv are in (k,n](k,n]. Let f(n)f(n) be the smallest kk such that u>n2u>n^2. Give bounds for f(n)f(n).

References

Progress summary

Refreshed
Claimed solved

A recent manuscript claims the conjectured logarithmic ceiling is false, but the new construction has not yet been independently verified.

The problem asks for the largest possible size of the first index kk where the small-prime part of a binomial coefficient exceeds n2n^2. The long-standing expectation was f(n)reaklesssimlog⁡nf(n)reaklesssim\log n; a recent manuscript instead claims arbitrarily large multiples of log⁡n\log n occur.

Known results

  • Mahler proved f(n)→∞f(n)\to\infty, ineffectively.
  • Tang and ChatGPT obtained f(n)≤n30/43+o(1)f(n)\le n^{30/43+o(1)}, improved conditionally to n2/3+o(1)n^{2/3+o(1)}.
  • Alexeev, Putterman, Sawhney, Sellke, and Valiant proved f(n)≤(24/(π2−6)+o(1))(log⁡n)2f(n)\le(24/(\pi^2-6)+o(1))(\log n)^2.
  • The same authors constructed njn_j with f(nj)≥(1/2+o(1))log⁡njf(n_j)\ge(1/2+o(1))\log n_j.

Unbounded logarithmic limsup: recent claim

The manuscript claims that for every fixed C>1C>1, infinitely many nMn_M satisfy f(nM)>(C−o(1))log⁡nMf(n_M)>(C-o(1))\log n_M, hence lim sup⁡n→∞f(n)/log⁡n=∞\limsup_{n\to\infty}f(n)/\log n=\infty. Its construction uses nM=tlcm⁡(1,…,M)−1n_M=t\operatorname{lcm}(1,\ldots,M)-1 and a Fourier sieve. This is a claimed resolution at the order level, not yet independently verified.

Current status (as of June 2026): The claimed manuscript would settle the worst-case order by making the logarithmic limsup infinite, while the proof and construction remain unverified; the polylogarithmic upper bound and density-one result are established only as reported results.

  • An internal OpenAI model [APSSV26]OpenAIsolvedevidence
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