The Markov property says that, conditional on the present state, the next state is independent of the earlier history:
Two states communicate if each is reachable from the other with positive probability in finitely many steps. The equivalence classes are communicating classes; a class is closed if no positive-probability transition leaves it.
The displayed probabilities require ; negative values allowed by the printed one-sided inequality are not transition probabilities. For , every state is an absorbing singleton, so all singleton classes are closed. For , neighboring states communicate in both directions, so there is one closed irreducible class and no open classes.
For , the detailed balance relations give . Normalization yields
For , positive holding probabilities make the finite irreducible chain aperiodic, so its transition probabilities converge to from every initial state. At , every step changes parity and the period is two; convergence from a fixed initial state fails. A stationary initial mixture still has distribution at every time, but this does not give convergence of the transition probabilities asked for.

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