Probability and statistical mechanics·OpenAI Math·Result 225
Gaussian free field limits throughout the balanced six-vertex regime
One of the 372 results in OpenAI's public mathematics catalogue, filed under probability and statistical mechanics: 1 preprint, the latest dated 23 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 free field limit of the balanced six-vertex model with variance multiplier 1/arcsin(c/2)
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What OpenAI claims
The balanced square-lattice six-vertex height field with a=b=1 and 0 < c ≤ 2 converges to a Gaussian free field, including at the endpoint c = 2. The plane state is defined by balanced-torus limits. For unit height increments and Green kernel -(2π)-1 log|x-y|, the exact variance multiplier is 1/arcsin(c/2).
Paper
The Gaussian free field limit of the balanced six-vertex model with variance multiplier 1/arcsin(c/2)
We prove that the height function of the square-lattice six-vertex model with weights a=b=1 and 0 < c ≤ 2, in the plane state obtained from balanced tori, converges to a multiple of the Gaussian free field. For unit height jumps and Green kernel -(2π)-1 log|x-y|, the squared multiplier is 1/arcsin(c/2).
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.
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