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Diluted maximum-likelihood algorithm for quantum tomography

Jaroslav Rehacek·Zdenek Hradil·E. Knill·A. I. Lvovsky
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Abstract

We propose a refined iterative likelihood-maximization algorithm for reconstructing a quantum state from a set of tomographic measurements. The algorithm is characterized by a very high convergence rate and features a simple adaptive procedure that ensures likelihood increase in every iteration and convergence to the maximum-likelihood state. We apply the algorithm to homodyne tomography of optical states and quantum tomography of entangled spin states of trapped ions and investigate its convergence properties.

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Jaroslav Rehacek, Zdenek Hradil, E. Knill, A. I. Lvovsky. 2007-02-22. Diluted maximum-likelihood algorithm for quantum tomography. https://doi.org/10.1103/physreva.75.042108

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