Re: First Year Linear Algebra Marathon
In fact, the matrix A is a doubly stochastic (in fact, symmetric) Markov matrix. By inspection it is the transition matrix of an irreducible Markov chain, and thus this chain (being irreducible and finite) has a unique stationary distribution. As it is doubly stochastic, this unique stationary distribution is the uniform distribution (1/3, 1/3, 1/3). It is also clear the period of the chain is 1, i.e. it is aperiodic (e.g. because state 1 can go to state 1 in two steps or three steps), so regardless of the initial distribution, we converge to the uniform distribution state vector. If the initial vector is (a, b, c), then since the state vector will have constant sum, we converge to ((a+b+c)/3, (a+b+c)/3, (a+b+c)/3) (this formula also clearly holding if the initial vector was the zero vector).