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.
Separate stationary solve residual from generator error
Statement
Let Q be the true finite column generator, let satisfy , and put . Suppose for some . Let be any computed matrix model on the same finite state set, let , and let x be a column probability vector with . Then, for the unique stationary probability of Q,
The first residual is the solve residual for the computed model; the second is the model perturbation evaluated at the chosen candidate. If , the solve-residual term vanishes. Every term must be supplied as an exact value or a certified outward upper bound before the displayed expression is reported as a numerical certificate.
In particular, if P and y are rational and the exact branch of Correct and certify a finite-chain stationary candidate returns certified, its output x and c satisfy these conditions.
Facts & Assumptions
Given: Q, , P, m, q, y, a computed model , a column probability vector x, and .
Correct and certify a finite-chain stationary candidate: on exact-branch success for rational P, y, and m, x is a column probability vector and .
Uniformized finite-generator stationary residual certificate: for the true generator Q and the chosen column probability vector x.
Proof
Given: Q, , , P, q, m, y, x, and c under the stated hypotheses.
Proof technique: write the exact generator residual as the sum of the computed solve residual and the model discrepancy.
The exact generator residual decomposes as . The triangle inequality gives .
By [F2], the generator certificate gives . Substitute the estimate from step 1.1; since , the result is the stated separate solve-residual and model-error bound. An outward upper bound for either norm preserves the inequality. If P and y are rational and the exact algorithm returns certified, [F1] supplies the required probability x and correction c.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
8 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Yuanyuan Liu, Perturbation Bounds for the Stationary Distributions of Markov Chains (standard reference, not scraped)
- Ilse C. F. Ipsen and Teresa M. Selee, Ergodicity Coefficients Defined by Vector Norms (standard reference, not scraped)