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arXiv · 1203.3391

Adaptive experimental design for one-qubit state estimation with finite data based on a statistical update criterion

Takanori Sugiyama·Peter S. Turner·Mio Murao
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Abstract

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.

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Takanori Sugiyama, Peter S. Turner, Mio Murao. 2012-05-18. Adaptive experimental design for one-qubit state estimation with finite data based on a statistical update criterion. https://doi.org/10.1103/physreva.85.052107

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