Problem detail · source-aware

Ji-Zhang Question on the Power Set of a Quasinilpotent Operator

resolvedconfidence 70%

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Precise statement

Douglas and Yang attach to each nonzero vector $x$ of a quasinilpotent operator $T$ a local resolvent-growth exponent $k_x$, giving the power set $\Lambda(T) = \{k_x : x \ne 0\}$. Ji and Zhang asked whether $1$ always belongs to $\Lambda(T)$. It does, for every quasinilpotent operator on every Banach space. Moreover $\Lambda(T) = [0,1]$ for every backward unilateral weighted shift on $\ell^p$ with strictly decreasing, $p'$-summable weights, weakening the hypotheses of Hu and Ji.

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

Claude Opus

The declaration states that generative AI was used substantially, and that its contribution was decisive for the formulation and proof of Lemma 1 in particular, with further help drafting several of the standard arguments and the LaTeX source. All output was produced under the author's direction and subsequently revised and verified by him.

Provider: Anthropic · Prompt public: unknown · Independence: unknown

Verification boundary

unreviewed

Single-author arXiv preprint; not yet peer-reviewed.

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

Timeline

  1. arXiv:2607.16743 - The power set of a quasinilpotent backward weighted shift

    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

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.
  • VibeMath has not independently audited the mathematical statement, proof, or novelty claim.