OpenAI claim summary for Math-2667
mathematicsTop Open Problemscontributionliterature_reportClaim: literature report
Summary of a claim published in openai/math; not a claim by this platform.
Metric Blaschke rigidity: The manuscript claims that a closed connected manifold with injectivity radius equal to diameter is a scaled standard compact rank-one symmetric space. The assertion includes all positive dimensions and model types. The parameters, regularity assumptions and normalization in this question are retained in applying that assertion.
With the hypotheses and conventions above, the claimed result addresses the whole mathematical assertion on this page.
Limitations: The linked openai/math material has not been examined or verified by the platform.
Manuscript
Contents
Metric classification of Blaschke manifolds
OpenAI's claim
Metric Blaschke rigidity: The manuscript claims that a closed connected manifold with injectivity radius equal to diameter is a scaled standard compact rank-one symmetric space. The assertion includes all positive dimensions and model types.Mathematical statement of the claimed result
Mathematical claim 1.
For a smooth closed manifold with a Riemannian metric, assume connectedness and positive dimension, equality of global injectivity radius and diameter, $\operatorname{inj}(M,g)=\operatorname{diam}(M,g)$, is claimed to imply that after a positive constant scaling the metric is isometric to one of these standard models: a round sphere, projective space over $\mathbb R$, $\mathbb C$ or $\mathbb H$, or a Cayley plane. The conclusion classifies the metric, rather than only the diffeomorphism type.Outline of the argument
Metric Blaschke rigidity: Normal Jacobi fields along a closed geodesic are encoded as Lagrangian planes. A fixed graph chart factors the endpoint determinant using a nonsingular block and its Schur complement, with the latter controlled by the cut-time intersection data. Sharp volume comparison and equality analysis combine with the corresponding upper bound, forcing the metric to equal its model.Formal verification
Metric Blaschke rigidity: The pinned catalogue lists no Lean formalization for this result.This site has not run the Lean development. These links describe OpenAI’s selected formal statements and should be read with their stated scope.
Status caveat
OpenAI reports that an internal model produced the manuscripts. Their arguments have not been independently verified as proofs by this site. Any portion outside the documented formal scope may contain mistakes, and the catalogue label reports the announced mathematical claim.Sources
- OpenAI, The metric Blaschke theorem, 2026-09-23; citation key
OAI:The-metric-Blaschke-theorem-September-23-2026. PDF (GitHub); PDF (direct); Manuscript page and citation; Latest version; Statement source: thm:blaschke. - OpenAI catalogue entry.