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arXiv:1303.1792 · Physical Review A

Experimental adaptive Bayesian tomography

Konstantin Kravtsov, Stanislav S. Straupe, I. V. Radchenko, Neil Houlsby, Ferenc Huszár, S. P. Kulik

Published Jun 28, 2013• 87 citations
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Abstract

We report an experimental realization of an adaptive quantum state tomography protocol. Our method takes advantage of a Bayesian approach to statistical inference and is naturally tailored for adaptive strategies. For pure states, we observe close to ${N}^{\ensuremath{-}1}$ scaling of infidelity with overall number of registered events, while the best nonadaptive protocols allow for ${N}^{\ensuremath{-}1/2}$ scaling only. Experiments are performed for polarization qubits, but the approach is readily adapted to any dimension.

DOI
10.1103/physreva.87.062122

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Adaptive measurements have recently been shown to significantly improve the performance of quantum state and process tomography. Adaptive tomography is especially useful in complicated experiments with low outcome generation rate, since it allows one to extract maximal information from a limited amount of data. However, the existing methods either cannot be simply applied to high-dimensional systems or are prohibitively computationally expensive. Here we propose and experimentally implement a tomographic protocol specially designed for the reconstruction of high-dimensional quantum states. The protocol shows qualitative improvement in infidelity scaling with the number of measurements and is fast enough to allow for complete state tomography of states with dimensionality up to 36.