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CounterexampleConstruction: AI-generatedVerification: AI-generatedPipeline-generatedprecheck passjudge pass (gpt-6-luna)
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

A repeated unit root causes a linearly growing parasitic mode

Statement refuted

Every consistent two-step linear multistep method is zero-stable.

Facts & Assumptions

Given: The method and consistency conventions of Linear multistep methods, consistency, order, and the root condition.

[F1]

Taylor moment conditions characterize the order of a linear multistep method says consistency is equivalent to ρ(1)=0 and ρ′(1)=σ(1).

Counterexample

Take ρ(ζ)=(ζ−1)2 and σ(ζ)=0, so the recurrence is Yn+2−2Yn+1+Yn=0. This is a consistent first-order two-step method, but its double unit root is not zero-stable.

1.1F1algebra

Here ρ(1)=0 and ρ′(1)=0=σ(1), so [F1] proves consistency.

1.2givenalgebra

The characteristic polynomial has a root 1 of multiplicity two, so it violates the root condition in Linear multistep methods, consistency, order, and the root condition.

1.3givenconstruct

Apply the recurrence to y′=0, whose exact solution is y=0, with Y0=0 and Y1=h. The sequence Yn=nh satisfies the recurrence because its second difference is zero.

2.1step 1.3algebra∎

On the grid h=T/N, the starting error is h→0, but ∣YN−y(T)∣=Nh=T. Thus convergence fails even for starting errors of order h, and the proposed claim is false.

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