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Time reversal of a stationary Markov chain
Statement
Assume AC (The Axiom of Choice). Let be a countable transition matrix (Transition matrices and n-step probabilities) with invariant probability (Invariant and stationary distribution for a Markov kernel), let be a -chain started in and let . Define the reverse kernel on by
Then:
- extended by for is a transition matrix on , and restricted to is invariant for it; no mass ever leaves .
- Every finite path segment of read backward is distributed as a -chain started in : for every and , where is a stationary -chain with initial law .
- Detailed balance for and (Reversible measure and detailed balance) is equivalent to for all .
- Rows at states outside carry no stationary mass and may be chosen arbitrarily (for instance all equal to for a fixed ) if a kernel on all of is desired.
Facts & Assumptions
Given: AC, a countable , a transition matrix with invariant probability , a -chain started in , and .
Every family of nonempty sets has a choice function; AC is assumed and is used through the stationary-chain, finite-dimensional-law and chain-construction suppliers [F2], [F3] and [F5]. (The Axiom of Choice)
On a countable state space is invariant exactly when for every , and rows of sum to one with . (Invariant and stationary distribution for a Markov kernel, Transition matrices and n-step probabilities)
If a chain has invariant initial law , then every finite-dimensional law is shift-invariant; in particular has law for every . (Invariant initial law makes a Markov chain stationary)
Assume Choice. For a -chain with initial law , times and bounded measurable , . (Finite-dimensional laws of a Markov chain)
A state measure satisfies detailed balance for when for all . (Reversible measure and detailed balance)
Assume Choice. For an initial probability and a probability kernel, a canonical chain exists on the product path space with that initial law and kernel. (Canonical Markov chain on path space)
Proof
Given: AC, a countable , a transition matrix with invariant probability , and a stationary -chain started in .
Proof technique: check that the normalized backward transition ratios form a stochastic matrix preserving , then verify the reversal by telescoping products of transition probabilities, and read off the detailed-balance equivalence.
If and then : otherwise by [F1], contradicting . Hence for every .
The formula is well defined for because , and nonnegative; for its row sum is , using [F1]; since for , the extended entries vanish off , so is a transition matrix on and no mass leaves .
The probability restricted to is invariant for : for , by step 1.1, while for both sides vanish; this is precisely invariance in the countable form [F1].
Detailed balance equivalence: for the identity is equivalent, after dividing by the positive number , to ; if and , then by step 1.1 and because . The case , follows by exchanging and ; if both states are outside , both weights vanish. Transitions from outside into need not vanish. Hence detailed balance for and holds for all pairs exactly when on .
By [F5] construct a -chain on with initial law ; it is stationary by [F2] and step 2.1. Consecutive-time reversal: for and states , [F3] with (and indicators) gives ; reading the same word backward and using the definition of , after telescoping cancellation of the , ; paths visiting have probability zero by step 1.1, so for a stationary -chain with initial law , by [F3] and step 2.1.
For every and , step 3.1 at gives . Taking the coordinates indexed by on both sides yields the asserted law of .
Null rows: since for , such a state carries no stationary mass and does not appear in the reversal statements of items 1–3, which only involve paths with positive probability; if a kernel on all of is wanted, fix (the set is nonempty because is a probability) and set for , which is a probability row and leaves every assertion about unchanged.
Boundary and axiom cases: if (the chain is irreducible and positive recurrent, or more generally has full support) then no null rows arise and clause 3 compares the two kernels on all of ; if is a singleton, and both reversal and detailed balance are trivial; the reversal identity of step 3.1 is symmetric in the two directions and does not presuppose , so the statement covers nonreversible stationary chains; AC [A1] is used in constructing through [F5], proving its stationarity through [F2], and computing finite-dimensional laws through [F3]; and all products and telescoping cancellations are finite, no infinite sum being rearranged.
Depends on
Used by
- An invariant law need not be reversible Counterexample
- Kac return-time formula for a positive-mass set Theorem
Dependency tree · two levels
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Sources
- Durrett, Probability: Theory and Examples, fifth edition, §5.5–5.6, reversibility and time reversal (standard reference, not scraped)
- Levin–Peres–Wilmer, Markov Chains and Mixing Times, second edition, §21.3 and Appendix C.1 (standard reference, not scraped)