Why Does A_n Converge in This Markov Chain Problem?

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SUMMARY

The discussion focuses on the convergence of the sequence A_n in a Markov chain defined by the transition matrix P = [[0, 1], [1, 0]]. It is established that while P^n does not converge to a limit, the average matrix A_n = (1/(n+1))(I + P + P^2 + ... + P^n) does converge to a steady state. Specifically, as n approaches infinity, A_n approaches the matrix [[1/2, 1/2], [1/2, 1/2]], indicating that the system stabilizes despite the non-convergence of P^n.

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Homework Statement



Consider:

[itex]P=\left( \begin{array}{cc} 0 & 1 \\ 1 & 0 \end{array} \right)[/itex]

Show that [itex]P^n[/itex] has no limit, but that: [itex]A_n=\frac{1}{n+1}(I+P+P^2+\ldots+P^n)[/itex] has a limit.

The Attempt at a Solution



I can see that [itex]P^{EVEN}=\left( \begin{array}{cc} 1 & 0 \\ 0 & 1 \end{array} \right)[/itex] and [itex]P^{ODD}=\left( \begin{array}{cc} 0 & 1 \\ 1 & 0 \end{array} \right)[/itex], so a steady state is never reached, but I can't figure out the second part.

Any suggestions?
 
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So for example

I+P+P2+P3+P4+P5 =
[3 3]
[3 3]

and when you divide this by six you get a matrix with all 1/2s. Try adding up some more guys and see what happens
 

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