OpenAI reports sharp one-third stability of Brenier maps

For the uniform measure on any compact convex body with nonempty interior in ℝᵈ, d≥2, and targets supported in one fixed compact set, the L² distance between their quadratic optimal maps is at most C times the one-third power of the targets’ 2-Wasserstein distance.

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OpenAI reports sharp one-third stability of Brenier maps

  • Mathematics

For the uniform measure on any compact convex body with nonempty interior in ℝᵈ, d≥2, and targets supported in one fixed compact set, the L² distance between their quadratic optimal maps is at most C times the one-third power of the targets’ 2-Wasserstein distance. No larger uniform exponent works in general, even for three-atom targets on a fixed cube.

AI involvementAI-led
ImportanceMajor
Technical verificationFormal (Lean 4)
Human understandingFew

Understanding the problem

Read the background

For the uniform measure on any compact convex body with nonempty interior in ℝᵈ, d≥2, and targets supported in one fixed compact set, the L² distance between their quadratic optimal maps is at most C times the one-third power of the targets’ 2-Wasserstein distance. No larger uniform exponent works in general, even for three-atom targets on a fixed cube.

Why it matters

If correct, determines the exact uniform stability exponent and refutes the proposed square-root exponent.

What counts as progress

What is the optimal uniform Wasserstein stability exponent for Brenier maps from a convex uniform source?

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