In the limit t→∞ we require that the two distributions wi(t+1)=wi and wi(t)=wi and we have ∑jwjTj→iAj→i=∑jwiTi→jAi→j, which is the condition for balance when the most likely state (or steady state) has been reached. We see also that the right-hand side can be rewritten as ∑jwiTi→jAi→j=∑jwiWi→j, and using the property that ∑jWi→j=1, we can rewrite our equation as wi=∑jwjTj→iAj→i=∑jwjWj→i, which is nothing but the standard equation for a Markov chain when the steady state has been reached.