The Metropolis method is simply the power method for computing the right eigenvector of \( M \) with the largest magnitude eigenvalue. By construction, the correct probability distribution is a right eigenvector with eigenvalue 1. Therefore, for the Metropolis method to converge to this result, we must show that \( M \) has only one eigenvalue with this magnitude, and all other eigenvalues are smaller.