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Radius of comparison equals half the mean dimension

OpenAI · September 25, 2026

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Abstract

We prove the integer-action case of the Phillips–Toms conjecture: for every minimal homeomorphism of an infinite compact metrizable space, the radius of comparison of its crossed product equals one half of its mean dimension, including equality at infinity. For these systems, zero mean dimension and the small boundary property are equivalent to Jiang–Su stability and to finite nuclear dimension of the crossed product; in this case its nuclear dimension is at most one.

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Collected automatically by AI tools (Claude Opus 5.5 and GPT-6 Astra, 2026-10-21) and not checked by a person. May be wrong or incomplete. Report an error.

Follow-up works

  • George A. Elliott and Zhuang Niu, Mean dimension and radius of comparison (arXiv:2610.11143v1, 2026-10-08). This follow-up, whose authors disclose ChatGPT use, adapts the comparison and cover-reconstruction arguments using the companion's torus-compression theorem to obtain equality for diagonal AH algebras and free minimal amenable actions with both the uniform Rokhlin property and Cuntz comparison of open sets. [family-level]

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Cite

@misc{OAI:Radius-of-comparison-equals-half-the-mean-dimension-September-25-2026,
  author = {{OpenAI}},
  title = {{Radius of comparison equals half the mean dimension}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Radius-of-comparison-equals-half-the-mean-dimension-September-25-2026/paper.pdf}{OAI:Radius-of-comparison-equals-half-the-mean-dimension-September-25-2026}},
  year = {2026}
}

Family 302: Radius of comparison equals half the mean dimension

For every minimal homeomorphism h of an infinite compact metrizable space X, the radius of comparison of $C(X)\rtimes_h\mathbb Z$ equals $\tfrac12\mathrm{mdim}(X,h)$, including infinite values. Zero mean dimension is equivalent to the small boundary property, Jiang–Su stability and finite nuclear dimension; in this case nuclear dimension is at most one.

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