Research notes on every problem, and a library of the papers behind them. Built from the open erdos repository.
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Claim. Theorem 2.1 of Jia-Qi Yang, Erdős's Robust Polynomial Interpolation Problem: the Optimal Exponential Scale (manuscript of 2026-09-13, at the linked pinned commit): there is an absolute constant such that for every and one can choose
such that for every and every , repeated nodes allowed, there are signs for which every complex polynomial with and has at more than indices. At this is the assertion of Problem 1133 with sign data, with a non-strict degree bound in place of the strict one, so the claim is full. The manuscript adds that the exponential order is optimal: with , interpolation at Chebyshev–Lobatto nodes rules out when ; and for the obstruction restricted to the full Chebyshev–Lobatto grids the optimal parameter satisfies , the sharp coefficient for arbitrary nodes being left open. The quantitative input is a finite interpolation estimate in Bernstein spaces of Olevskii and Ulanovskii (Proc. Steklov Inst. Math. 303 (2018), 178–192); the angular reduction and the grouping of nodes into blocks follow the note posted by Chojecki, recorded on its own claim page, which the manuscript cites as an unsigned draft giving a qualitative proof without a rate. The grid result uses periodic sign data and averaging over periods, with a cardinal-interpolation construction for the matching upper bound; a further section treats random signs and angular perturbations of the nodes.
Submission note. Posted to erdosproblems.com as a proof claim by Jia-Qi Yang (account Yjq1368708545) on 13 September 2026, giving "GPT-6" as the AI used:
We prove the assertion in Erdős Problem 1133 and obtain stronger quantitative results. The obstruction holds for sign data with any prescribed pointwise tolerance . We determine the optimal exponential order of the obstruction parameter in , where is the uniform norm bound. For the full Chebyshev–Lobatto grids, we further identify the sharp leading exponential coefficient . The proof combines finite interpolation estimates in Bernstein spaces with angular rescaling and grouping. The sharp grid result uses periodic sign data and averaging to control exceptional samples, together with a cardinal interpolation construction giving the matching upper bound. Notes: GPT-6 was used for mathematical exploration and proof development. This submission concerns a quantitative refinement of the earlier draft and a sharp exponential coefficient for the full Chebyshev–Lobatto grids. Quantitative interpolation estimate used for the arbitrary-node result: A. Olevskii and A. Ulanovskii, “On irregular sampling and interpolation in Bernstein spaces,” Proceedings of the Steklov Institute of Mathematics 303 (2018), 178–192. https://doi.org/10.1134/S0081543818080151
Depends on. No page of this wiki: the inputs are cited from the literature (Olevskii–Ulanovskii; Beurling in Appendix B); the earlier note is credited for the method, not used as a premise.
Standing. A manuscript claim, claimed. The claimant submitted the
claim to the site's proof-claims tab on 2026-09-13 as a full proof,
disclosing that GPT-6 was used for exploration and proof development and
that the submission is a quantitative refinement of the earlier note; the
manuscript carries no author byline, and the repository's README calls it a
preprint that has not been peer reviewed. Not reviewed: the site's label is
OPEN (page last edited 31 December 2025; the tab, accessed 2026-10-06,
carries no comments on the claim), and no outside review is known. Not
refereed: no journal or arXiv version. Its proofs have not been reviewed.