Problem detail · source-aware

Online Shadow Tomography Matching the Classical Bounds

resolvedconfidence 70%

VibeMathed reports this item as resolved. VibeMath preserves that report as a source assertion and has not independently authored a plain-language mathematical explanation.

Precise statement

Online Shadow Tomography with $\log m$ dependence, while retaining $\mathrm{poly}(\log(d)/\epsilon)$ dependence. Also, matching the best classical bounds for Adaptive Data Analysis

The source statement is reproduced for indexing with attribution. Mathematical correctness requires domain-expert or mechanical review. VibeMath has not independently audited statement fidelity, correctness, priority, or novelty.

What AI did

ChatGPT 5.6-Sol Pro

Discovered the main proof

Provider: OpenAI · Prompt public: unknown · Independence: unknown

Verification boundary

unreviewed

Unreviewed preprint. The authors state they studied, refined and verified the model's ideas themselves and take full responsibility for every claim, proof and citation; that is the authors checking their own work, so it stays Unreviewed until someone independent looks. Recorded as Resolved rather than Partial because the stated target - matching the classical Adaptive Data Analysis rates - is fully achieved by Theorems 1.2 and 1.3. What remains open is whether those rates are optimal, which was never the question this entry records.

Correctness: unknown · statement fidelity: unaudited · peer review: none

Timeline

  1. arXiv

    VibeMathed reports this item as resolved. VibeMath preserves that report as a source assertion and has not independently authored a plain-language mathematical explanation.

Known method families

argument (source-reported)

Source-reported tools: argument.

Independent: unknown · difference confidence: 0

What remains uncertain

The source did not supply a subject field. VibeMath has not independently audited the mathematical statement, proof, or novelty claim.

  • VibeMath has not independently verified the mathematical claim.
  • AI-attempt independence and training-data exposure are unknown unless explicitly documented.
  • The source did not supply a subject field. VibeMath has not independently audited the mathematical statement, proof, or novelty claim.