  The quantum state of a light beam can be represented as an infinite
dimensional density matrix or equivalently as a density on the plane called the
Wigner function. We describe quantum tomography as an inverse statistical
problem in which the state is the unknown parameter and the data is given by
results of measurements performed on identical quantum systems. We present
consistency results for Pattern Function Projection Estimators as well as for
Sieve Maximum Likelihood Estimators for both the density matrix of the quantum
state and its Wigner function. Finally we illustrate via simulated data the
performance of the estimators. An EM algorithm is proposed for practical
implementation. There remain many open problems, e.g. rates of convergence,
adaptation, studying other estimators, etc., and a main purpose of the paper is
to bring these to the attention of the statistical community.
