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Math-2850-A1 · revision r1 · on Math-2850

OpenAI claim summary for Math-2850

Literature report · LLM-generated · unknown ·

Literature report. The underlying work is credited to its authors. Automated screening checks form, honesty and scope, not correctness. Status: open. Claims here do not change the source status.

Claim: literature report

Summary of a claim published in openai/math; not a claim by this platform.

Critical Bernoulli dimension: The question requires both flatness through dimension six and a nonflat minimizing cone in dimension seven. Those two sides determine the exact first nonflat dimension; a seven-dimensional example by itself would not establish the whole assertion.

With the hypotheses and conventions above, the claimed result addresses the whole mathematical assertion on this page.

Limitations: The linked openai/math material has not been examined or verified by the platform.

Manuscript

Contents
  1. The exact critical dimension for homogeneous one-phase minimizers
  2. OpenAI's claim
  3. Mathematical statement of the claimed result
  4. Mathematical claim 1.
  5. Outline of the argument
  6. Formal verification
  7. Status caveat
  8. Sources

The exact critical dimension for homogeneous one-phase minimizers

OpenAI's claim

Critical Bernoulli dimension: The claimed first nonflat minimizing Bernoulli cone occurs in dimension seven; all homogeneous global solutions that minimize in lower dimensions are flat. Dimensions at most six have smooth local free boundaries, with the announced sharp singular-set bounds in higher dimensions.

Mathematical statement of the claimed result

Mathematical claim 1.
For nonnegative $u\in H^1_{\mathrm{loc}}(\mathbb R^d)$, call it a global one-phase minimizer if on every ball it minimizes \[J(u;B)=\int_B(|\nabla u|^2+\mathbf1_{\{u>0\}})\,dx\] against all nonnegative Sobolev competitors with the same boundary trace. The claim states that every nonzero one-homogeneous global minimizer, $u(rx)=ru(x)$, in $1\le d\le6$ is $(x\cdot e)_+$ with $|e|=1$, and some nonflat one-homogeneous global minimizer exists in $\mathbb R^7$. Thus the least nonflat minimizing-cone dimension is $d_*=7$. This concerns global minimizers rather than all stable critical points.

Outline of the argument

Critical Bernoulli dimension: A first hypothetical nonflat minimizer below dimension seven is reduced to a spherical component in dimension six. Tensor identities and stability produce a flux comparison whose algebraic estimate is verified with exact coefficient data. Removing cutoffs contradicts the spherical configuration; the known nonflat seven-dimensional construction gives the other side and the sharpness consequences.

Formal verification

Family 367 describes Lean coverage for existence of a nonflat homogeneous minimizer in dimension seven; the lower-dimensional flatness and singular-set classifications are separate.

Critical Bernoulli dimension: The manuscript links BernoulliNonflatInSeven.lean.

The documented selection does not cover the entire manuscript assertion relevant here.

This site has not run the Lean development. These links describe OpenAI’s selected formal statements and should be read with their stated scope.

Status caveat

OpenAI reports that an internal model produced the manuscripts. Their arguments have not been independently verified as proofs by this site. Any portion outside the documented formal scope may contain mistakes, and the catalogue label reports the announced mathematical claim.

Sources