Math-2913-A1 · revision r1 · on Math-2913

OpenAI claim summary for Math-2913

Literature report · LLM-generated · unknown ·

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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.

For each fixed $\beta>1$, typical SK equilibrium configurations held as starts are claimed to remain unmixed until at least $\exp(n^{1/10000})$. The question retains these same parameters and conventions. Within these assumptions, this is a claimed affirmative answer to the stated question.

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

Manuscript

Contents
  1. Stretched-exponential mixing barriers for typical low-temperature SK starts
  2. OpenAI's claim
  3. Mathematical statement of the claimed result
  4. Result 1.
  5. Outline of the argument
  6. Formal verification
  7. Status caveat
  8. Sources

Stretched-exponential mixing barriers for typical low-temperature SK starts

OpenAI's claim

OpenAI presents a proof in the selected manuscript. For each fixed $\beta>1$, typical SK equilibrium configurations held as starts are claimed to remain unmixed until at least $\exp(n^{1/10000})$.

Mathematical statement of the claimed result

Result 1.
For independent standard Gaussian $J_{ij}$, $i<j$, with $J_{ji}=J_{ij},J_{ii}=0$, use the zero-field SK measure \[ \pi_{n,\beta}^J(x)=Z^{-1}\exp\left(\frac\beta{\sqrt n}\sum_{i<j}J_{ij}x_ix_j\right),\qquad x\in\{-1,1\}^n. \] Continuous heat-bath dynamics refreshes every site at rate one; a discrete step refreshes one uniformly selected site, including attempts that retain its spin. For fixed $\beta>1$, sample $x_0$ from $\pi_{n,\beta}^J$ and then use its realized value as the initial state. With $d^J(x,t)$ and $d_{\mathrm{disc}}^J(x,k)$ the corresponding total-variation distances, and $\kappa=1/10000$, \[ \mathbb P_{J,x_0\sim\pi}\{d^J(x_0,e^{n^\kappa})>1/4\}\to1,\qquad \mathbb P_{J,x_0\sim\pi}\{d_{\mathrm{disc}}^J(x_0,\lfloor e^{n^\kappa}\rfloor)>1/4\}\to1. \] The probability averages the interactions and the initial Gibbs sample; each transition-law distance holds the sample fixed.

Outline of the argument

Quantitative Parisi and constrained-overlap bounds produce a locked overlap sign around a reference sample. Disorder rotation and narrow-annulus coverage control rare sign-passage paths over the stretched-exponential horizon; spin reversal gives an equilibrium half-space that those paths cannot reach.

Formal verification

For family 227, the selected statements include the high-temperature gap for $\beta<1$, cutoff ratios only for $\beta<1/2$, critical lower mixing scales with a subexponential upper bound, and low-temperature barriers. They do not provide the full critical exponent, the full cutoff location, or the newer autocorrelation limits. The listed Comparator files are CriticalSK.lean, CriticalSKMixing.lean, SKBarriers.lean, SKHighTemperature.lean, SKRatio.lean. Named declarations include OAI.CriticalSK.covariance_and_linear_tests, OAI.CriticalSK.critical_mixing_bounds. This site has not executed the Lean code. The scope descriptions do not certify the remaining manuscript arguments.

Status caveat

OpenAI attributes these manuscripts to work by an internal model. Its release cautions that arguments without formalization can contain mistakes. This catalogue has not independently checked the proofs; the labels report the mathematical claims attributed to OpenAI.

Sources