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.
Nonnegative kernel action and finite drift
Definition
Let be a transition matrix on countable and let . Define the nonnegative kernel action
using the extended nonnegative sum of Series in the nonnegative extended real line. Terms with zero transition weight are omitted: The extended real line , its order, and the arithmetic that is left undefined leaves undefined, while each displayed product has positive finite first factor and is defined even when . If is finite-valued and , its drift is the finite real number
This agrees with the published discrete generator Discrete generator of a countable-state transition matrix on bounded functions. For an extended-valued , write a first-step relation as in extended nonnegative arithmetic; do not define a drift by subtracting from .
Depends on
Used by
- Expected exit time solves the Poisson equation Corollary
- Negative drift gives a finite mean small-set hit Example
- Green-kernel resolvent identity Lemma
- First-step equations for nonnegative exit costs Theorem
- Hitting probability as minimal harmonic extension Theorem
- Lyapunov drift bound for hitting times Theorem
- Superharmonic majorants bound exit costs Theorem
Dependency tree · two levels
15 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
- Roch, Lecture Notes on Measure-Theoretic Probability Theory, Note 24 (standard reference, not scraped)