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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Uniformized finite-generator stationary residual certificate
Statement
Let be a finite column generator, let satisfy , and put . Let and . Then the finite master equation has a unique stationary probability , characterized among column probability vectors by . For any raw vector and column probability vector , set . Then
The identity makes the generator residual directly usable by the discrete certificate. In the exact algorithm branch, returns candidate-unavailable, and returns certificate-unavailable; neither status supplies an algorithmic accuracy certificate.
In particular, when P and y are rational and the exact branch of Correct and certify a finite-chain stationary candidate returns certified with candidate x and correction c, those outputs satisfy the conditions above.
Facts & Assumptions
Given: A finite column generator Q, an admissible , its uniformized matrix P, an m-step coefficient q<1, a raw vector y, and a column probability vector x.
Finite column generator: Q has nonnegative off-diagonal entries, zero column sums, exit rates , and acts on column probability vectors.
The finite uniformized matrix is column stochastic: if and , then is column-stochastic.
Finite master equation and uniformization formula: the solution of , , is the Poisson-weighted uniformization series with matrix P, and each is a probability vector.
m-step Dobrushin certificate for a stationary probability: if , then P has a unique stationary probability and for every column probability vector x.
Correct and certify a finite-chain stationary candidate: in its exact rational domain, a certified output has a column probability candidate x and correction distance .
Proof
Given: Q, , P, m, q, y, x, and as above.
Proof technique: identify the generator-stationary law with the stationary law of its uniformized matrix, then substitute the generator residual.
By [F1] and [F2], and P is column-stochastic. Since , [F4] gives a unique stationary probability for P. The identity makes the constant trajectory a solution of the master equation; [F3] identifies it with the unique solution for that initial law. Conversely, any time-independent probability solution of satisfies , hence , so it equals .
For the probability x, follows from . By [F4] and the triangle inequality, . If P and y are rational and the exact algorithm returns certified, [F5] supplies precisely such x and c.
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Used by
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Sources
- Ilse C. F. Ipsen and Teresa M. Selee, Ergodicity Coefficients Defined by Vector Norms (standard reference, not scraped)
- Yuanyuan Liu, Perturbation Bounds for the Stationary Distributions of Markov Chains (standard reference, not scraped)