Convex and metric geometry·OpenAI Math·Result 096·Lean formalisation listed

The Gaussian propeller conjecture in every dimension

One of the 372 results in OpenAI's public mathematics catalogue, filed under convex and metric geometry: 1 preprint, the latest dated 24 September 2026. This page quotes OpenAI's own summary of the claim, links the paper and abstract, and will embed the animation.

Latest paper

The Gaussian propeller bound in every dimension

24 September 2026 · PDF

The animation for this result has not been released yet. Subscribe on YouTube to catch it.

What OpenAI claims

Proves that the sum of squared Gaussian first moments of any finite measurable partition is at most 9/(8π). In dimension at least two, three planar sectors of angle 2π/3, extended orthogonally, attain the bound. Combined with the separate Unique Games theorem, this proves NP-hardness of improving the loss factor (8π/9)(1-1/k) for identity-target kernel clustering with fixed k ≥ 3 on rational centered positive semidefinite inputs. (Lean)

Paper

  1. The Gaussian propeller bound in every dimension

    · Preprint, not peer reviewed · PDF

    We prove the Gaussian propeller conjecture: for every finite measurable partition of a Euclidean space, the sum of the squared lengths of its Gaussian first moments is at most 9/(8π). For dimension at least two and at least three cells, three planar sectors of angle 2π/3, extended by an orthogonal Euclidean factor, attain the bound.

Status

Preprint. The paper has not been independently reviewed. Treat the result as OpenAI's claim until other mathematicians have checked it. If a video exists, it illustrates the statement; it is not the proof.

Related results in Convex and metric geometry

All 15 results in Convex and metric geometry →