Ergodic theorem for a finite continuous-time Markov chain
= Ergodic theorem for a finite continuous-time Markov chain
{title2=$T^{-1}\int_0^Tf(X_t)\,dt\to\sum_n\pi(n)f(n)$}
For a finite <irreducible Markov chain> in continuous time, time averages converge almost surely to averages under its unique <stationary distribution>, from any initial state. Applying this to an activation indicator yields the corresponding <throughput>.