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Irreducible recurrence/transience dichotomy
Statement
Assume AC. Let the countable-state chain, transition matrix, fixed-start canonical laws, and positive-time recurrence convention be as in Recurrence and transience are class properties. Irreducibility means that every pair of states communicates (Accessibility, communication, and irreducibility). If , the universal conclusions below are vacuous. Otherwise, if the chain is irreducible, then either every state is recurrent or every state is transient.
Facts & Assumptions
Given: AC and a chain in the countable-state setup of the class-property theorem.
AC supplies the fixed-start canonical laws and is an explicit hypothesis of the class-property theorem used here. (The Axiom of Choice)
Irreducibility means for every pair . (Accessibility, communication, and irreducibility)
Communicating states have the same recurrence status. In particular, recurrence of one state transfers to every state that communicates with it. (Recurrence and transience are class properties)
A state is recurrent when its positive-time return probability is one and transient when that probability is less than one; these alternatives exhaust all states because the probability lies in . (Recurrent and transient states)
Every probability-kernel row has total mass one. On a one-state space, this forces the sole transition probability to equal one. (Measure kernel and probability kernel)
Proof
If , there are no states to classify. Both universal conclusions in the disjunction hold vacuously.
Now suppose and fix one state . For every , irreducibility [F1] gives . This fixes one witness state only; no family of choices is made.
If is recurrent, [F2] and step 1.2 imply that every is recurrent. Hence the first alternative holds.
If is not recurrent, consider any . If were recurrent, [F2] and step 1.2 would imply that is recurrent, a contradiction. Thus no state is recurrent. By [F3], every state is transient, so the second alternative holds.
By [F3], the fixed state is either recurrent or transient. Step 2.1 handles the recurrent case and step 2.2 handles the transient case. Therefore one of the two asserted universal alternatives always holds.
If has one state , [F4] gives , so its positive-time return probability is one. If has more than one state, an absorbing row at any state would make the chain reducible; zero one-step weights are allowed, since irreducibility requires communication by some positive-probability finite path, not a positive one-step transition. The zero-step accessibility alone does not establish recurrence, which requires a positive-time return [F3]. For a deterministic transition map on a nonempty irreducible state space with more than one state, fix and choose . The unique forward orbit from reaches and then returns to by irreducibility. It therefore contains a finite cycle through ; every state is reachable from , so every state lies on this cycle and returns to itself. Steps 2.1 and 2.2 prove the forward and reverse uses of the class-property equivalence. AC [A1] is inherited by the canonical laws and class-property theorem; fixing one state in step 1.2 uses no choice principle.
Source notes
Durrett, Probability: Theory and Examples, 5th ed., §5.3, Theorem 5.3.2 and its complete proof, printed p. 282/PDF p. 289 (official PDF parser lines 19113–19149), proves the stronger countable-chain statement that recurrence is contagious along accessibility and that the reverse hitting probability is one. Example 5.3.6 explicitly says that an infinite irreducible chain is either wholly recurrent or wholly transient, printed p. 284/PDF p. 291 (official parser lines 19241–19243). The example alone has an infinite-state hypothesis; this item's finite and empty cases are handled locally. The proof here uses the pair's completed class-property theorem and the definition that recurrence and transience exhaust the return-probability alternatives.
Depends on
Used by
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Dependency tree · two levels
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Sources
- Durrett, Probability: Theory and Examples, fifth edition (standard reference, not scraped)