The matrices involved grow exponentially in size, however, and in actual numerical calculations they must be truncated at each step. One way of doing this is to keep the n largest eigenvalues at each step, for some fixed n. In most cases, the sequence of approximations obtained by taking n = 1,2,3,... converges rapidly, and to the exact value (for an exactly solvable model).