Characterizing a universal cloning machine by maximum-likelihood estimation

We apply a general method for the estimation of completely positive maps to the one-to-two universal covariant cloning machine. The method is based on the maximum-likelihood principle, and makes use of random input states, along with random projective measurements on the output clones. The downhill simplex algorithm is applied for the maximization of the likelihood functional.