Result 302, Operator algebras

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)⋊hZC(X)\rtimes_h\mathbb Z equals 12mdim(X,h)\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.

Proof

The bigger picture

Why it matters

A dynamical system's average dimension and an associated algebra's ability to compare positive elements look like different kinds of complexity. The manuscript claims an exact formula linking them for a broad class of reversible systems.

What changes?

For every minimal homeomorphism of an infinite compact metrizable space, meaning a continuous reversible map whose every orbit is dense, the manuscript reports that radius of comparison equals half the mean dimension, including infinite values. Mean dimension measures dimension per iterate. The algebra is the crossed product, combining continuous functions on the space with its integer-time dynamics. Its radius of comparison measures the size gap needed for size information to guarantee comparison of positive elements.

What does that help mathematicians do?

The reported formula lets researchers infer an algebraic comparison obstruction directly from dynamical dimension. It also singles out a regularity threshold: zero mean dimension is equivalent to the small boundary property, a condition on neighborhood boundaries, and to both Jiang–Su stability and finite nuclear dimension of the crossed product. In this case, nuclear dimension is at most one. Conversely, any positive mean dimension rules out both of those algebraic regularity properties.

Are there practical applications?

Its immediate value is foundational, connecting topological dynamics with the structure of operator algebras. Nuclear dimension describes how an algebra can be approximated through finite-dimensional pieces, so the zero-mean-dimension conclusion gives a particularly restrictive approximation bound. The formula also provides a way to determine radius of comparison whenever mean dimension can be computed.

This section was generated by GPT-6 Astra Medium. This explanation is based on the result summary and manuscript abstracts below. This context is separate from OpenAI's source text.

2 manuscripts

Filtered products and boundary-preserving compression in complex cobordism

September 25, 2026 25 pages

We prove that, in sufficiently large smash powers, an MUMU-null restriction to a finite pointed subcomplex becomes stably null on the entire union of products with a fixed positive proportion of restricted factors. This coherent vanishing theorem yields boundary-preserving compression of cube-valued maps on every compact metrizable input space. When the torus slot bundle embeds continuously into a trivial bundle of rank less than twice the source rank, the compression places a positive proportion of slots on their boundaries in arbitrarily large powers and fixes every original boundary slot exactly. An example at equality shows that the strict rank inequality cannot be removed.

Cite (BibTeX)
@misc{OAI:Filtered-products-and-boundary-preserving-compression-in-complex-cobordism-September-25-2026,
  author = {{OpenAI}},
  title = {{Filtered products and boundary-preserving compression in complex cobordism}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Filtered-products-and-boundary-preserving-compression-in-complex-cobordism-September-25-2026/paper.pdf}{OAI:Filtered-products-and-boundary-preserving-compression-in-complex-cobordism-September-25-2026}},
  year = {2026}
}

Radius of comparison equals half the mean dimension

September 25, 2026 24 pages

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.

Cite (BibTeX)
@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}
}

Data from github.com/openai/math at commit adc7f12, committed October 6, 2026 at 21:58 UTC, last checked for changes about 9 hours ago. Titles, subjects, summaries, abstracts and Lean notes are OpenAI's; page counts are read from the PDFs. The map, related results, search, kinds of results and the named-problem index are Emergent Mind's, built with text embeddings and an LLM, and may contain errors.

An Emergent Mind Labs project. Emergent Mind is not affiliated with OpenAI. None of these results has been peer reviewed. Cite the manuscripts themselves, using the BibTeX on each result's page.