Finite-dimensional embeddings of doubling Hilbert subsets
Status Partially solved · unsolvedmath.comLLM status Open unverified
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Definitions and mathematical statement
Shared notation.
$\mathbb N$, $\mathbb Z$, $\mathbb Q$, $\mathbb R$, and $\mathbb C$ denote the natural numbers, integers, rationals, reals, and complex numbers, respectively. All additional parameters and hypotheses are specified in the question.Statement recorded in the supplied source.
Suppose a metric space $X$ is doubling, meaning that every ball can be covered by a fixed finite number of balls of half its radius. If $X$ admits a bi-Lipschitz embedding into a Hilbert space, must it admit a bi-Lipschitz embedding into $\mathbb R^m$ for some finite $m$?Formulation references: [S1], [S2].
Short English statement
Suppose a metric space $X$ is doubling, meaning that every ball can be covered by a fixed finite number of balls of half its radius. If $X$ admits a bi-Lipschitz embedding into a Hilbert space, must it admit a bi-Lipschitz embedding into $\mathbb R^m$ for some finite $m$?Sources
- S1 ULAM.AI and the UnsolvedMath Contributors, UnsolvedMath: A Curated Collection of Open Mathematics Problems, record 20000582 (AIM-ANALYSIS-0114). Catalogue attribution under CC BY 4.0. https://huggingface.co/datasets/ulamai/UnsolvedMath.
- S2 Original problem formulation and mathematical context. http://aimpl.org/mappingmetric/2/.
Statement licence: CC-BY-4.0 · Source file
Contributions 1
OpenAI claim summary for Math-2270
The displayed question has a negative answer under the manuscript's stated construction. Its counterexample meets the conditions in this problem and defeats the universal assertion, so this is a full disproof claim. The supporting result is manuscript 1 (family 098; 2026-09-25).
Finite-dimensional embeddings of doubling Hilbert subsets
OpenAI's claim
OpenAI presents the following claims relevant to this question, with manuscript numbers following paper order in Sources. In manuscript 1 (family 098; 2026-09-25), the asserted result is that in each infinite-dimensional real Banach space one can choose a compact subset with a universal doubling constant for which every bi-Lipschitz map into a finite-dimensional normed target is impossible.Mathematical statement of the claimed result
Manuscript 1.
A single subset $S$ of real $\ell_2$, with the distance inherited from its Hilbert norm, is claimed to satisfy \[ \operatorname{dbl}(S)\le76800,\qquad \forall k\ge1\ \forall D<\infty:\ S\text{ has no bi-Lipschitz embedding into }\mathbb R^k\text{ of distortion }D. \] Here doubling means that every metric ball is covered by at most that many balls of half its radius. The obstruction concerns one fixed doubling space, not a sequence with increasing doubling constants.Outline of the argument
For manuscript 1 (family 098; 2026-09-25), sheet-like pieces are arranged so that coverings remain uniformly doubling. Near-extremal derivatives of a hypothetical finite-dimensional embedding have small quadratic variation; crossings between separated sheets then force more packed images than the target can accommodate.Formal verification
For manuscript 1 (family 098; 2026-09-25), OpenAI lists Lean statements for this assertion: in each infinite-dimensional real Banach space one can choose a compact subset with a universal doubling constant for which every bi-Lipschitz map into a finite-dimensional normed target is impossible.The selected statement includes the clause used for this problem.
The linked family Comparator checks are CompactBanach.lean, DoublingHilbert.lean.
Their named declarations include OAI.CompactBanach.main, OAI.DoublingHilbert.main.
This site has not executed the Lean code. Described statement coverage is not an independent proof check.
Status caveat
The manuscripts were produced by an internal OpenAI model. OpenAI cautions that results without formalization can contain mistakes. This site has not independently checked the proofs; the label records the scope of OpenAI's claim.Sources
- OpenAI, A doubling Hilbert subset with no finite-dimensional bi-Lipschitz embedding, 2026-09-25; citation key
OAI:A-doubling-Hilbert-subset-with-no-finite-dimensional-bi-Lipschitz-embedding-September-25-2026. PDF (GitHub); PDF (direct); Manuscript page and citation; Latest version; Statement source: thm:main. - Family 098: Lean scope.
- Comparator CompactBanach.json.
- Comparator CompactBanach.lean.
- Comparator DoublingHilbert.json.
- Comparator DoublingHilbert.lean.
- OpenAI catalogue entry.