1202.5136 (Hui Khoon Ng et al.)

A simple minimax estimator for quantum states    [PDF]

Hui Khoon Ng, Berthold-Georg Englert

Quantum tomography requires repeated measurements of many copies of the
physical system, all prepared by a source in the unknown state. In the limit of
very many copies measured, the often-used maximum-likelihood (ML) method for
converting the gathered data into an estimate of the state works very well. For
smaller data sets, however, it often suffers from problems of rank deficiency
in the estimated state. For many systems of relevance for quantum information
processing, the preparation of a very large number of copies of the same
quantum state is still a technological challenge, which motivates us to look
for estimation strategies that perform well even when there is not much data.
In this article, we review the concept of minimax state estimation, and use
minimax ideas to construct a simple estimator for quantum states. We
demonstrate that, for the case of tomography of a single qubit, our estimator
significantly outperforms the ML estimator for small number of copies of the
state measured. Our estimator is always full-rank, and furthermore, has a
natural dependence on the number of copies measured, which is missing in the ML
estimator.

View original: http://arxiv.org/abs/1202.5136