VibeMathedMath problems solved with AI

Fujita's freeness conjecture

Let XX be a smooth complex projective variety of dimension nn, KXK_X its canonical bundle and LL an ample line bundle. Fujita conjectured that KX+mLK_X+mL is globally generated for every m≥n+1m\ge n+1 (and very ample for m≥n+2m\ge n+2); the bound is sharp for (Pn,O(1))(\mathbb P^n,\mathcal O(1)). Known: curves by Riemann-Roch, surfaces by Reider, dimensions 3, 4, 5 by Ein-Lazarsfeld, Kawamata and Ye-Zhu; in general Angehrn-Siu's quadratic bound m≥(n2+n+2)/2m\ge(n^2+n+2)/2, later improved to n(log⁡log⁡n+2.34)n(\log\log n+2.34) by Ghidelli-Lacini and to about 1.776n1.776n by Han. Is KX+(n+1)LK_X+(n+1)L globally generated for every smooth projective XX of every dimension nn and every ample LL?

Result
Proved(see note)
Status
Candidate (review pending)
AI contribution
AI-discovered
Method
Argument
Field
Algebraic geometry; adjoint linear systems
Posed by
Takao Fujita, On polarized manifolds whose adjoint bundles are not semipositive, Algebraic Geometry, Sendai 1985, Adv. Stud. Pure Math. 10 (1987)
Year posed
1987
Years open
39y
Solved
2026-09-23
Model
Unreleased internal OpenAI model
Vendor
OpenAI
Collaborators
—
Verification
Unreviewed
Publication
Announced
Collection
OpenAI math release (October 2026), version adc7f12
Significance
60 / 100
Disclosed cost
—
Wikipedia
No dedicated article

What was actually shown

Theorem 1.1: for every smooth connected complex projective variety XX of dimension n≥1n\ge1 and every ample line bundle LL, KX+(n+1)LK_X+(n+1)L is generated by global sections; hence KX+mLK_X+mL is globally generated for all m≥n+1m\ge n+1, even when LL itself is not. The bound is sharp. The method minimises an exponential average of normalised section orders over bases and weighted monomial valuations, then lifts sections with Fujita's discrepancy-and-vanishing mechanism. It does not prove the very-ampleness conjecture (m≥n+2m\ge n+2) or point separation.

What the AI did

The release README says the results were produced by an unreleased internal OpenAI model with a fixed procedure, on average about three hours of ChatGPT Pro thinking compute per result, and that some outputs build on earlier model results. This result is not among the README's exceptions (the Hodge conjecture for CM abelian varieties and the Re(s) > 11/12 zero-free region). The manuscript is authored 'OpenAI' and names no human author. The README also cautions that unformalized results could have issues.

Verification

No independent mathematician has checked this yet. Checked here: the abstract, introduction and Theorem 1.1 were read against Fujita's conjecture as the manuscript cites it. The proof was not refereed. No Lean formalization: the manuscript is not in lean/formalization.yaml and lean/docs/038.md does not exist at the pinned commit. Scope the paper itself states: only the freeness (global generation) part is proved, not separation of points or tangents and not the very-ampleness half of Fujita's conjecture. Readers should know a previous claimed proof (Chan, arXiv 2411.07129) was withdrawn in November 2024; the manuscript cites that withdrawal. A brief web search on 7 October 2026 found no public dispute of this manuscript.

Sources

Changelog1 change

Discussion