We consider 1-qubit mixed quantum state estimation by adaptively updating
measurements according to previously obtained outcomes and measurement
settings. Updates are determined by the average-variance-optimality
(A-optimality) criterion, known in the classical theory of experimental design
and applied here to quantum state estimation. In general, A-optimization is a
nonlinear minimization problem; however, we find an analytic solution for
1-qubit state estimation using projective measurements, reducing computational
effort. We compare numerically two adaptive and two nonadaptive schemes for
finite data sets and show that the A-optimality criterion gives more precise
estimates than standard quantum tomography.Comment: 15 pages, 7 figure
