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arXiv · 0812.4323

Quantum Process Tomography via L1-norm Minimization

Robert L. Kosut
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Abstract

For an initially well designed but imperfect quantum information system, the process matrix is almost sparse in an appropriate basis. Existing theory and associated computational methods (L1-norm minimization) for reconstructing sparse signals establish conditions under which the sparse signal can be perfectly reconstructed from a very limited number of measurements (resources). Although a direct extension to quantum process tomography of the L1-norm minimization theory has not yet emerged, the numerical examples presented here, which apply L1-norm minimization to quantum process tomography, show a significant reduction in resources to achieve a desired estimation accuracy over existing methods.

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Robert L. Kosut. 2009-03-05. Quantum Process Tomography via L1-norm Minimization. https://arxiv.org/abs/0812.4323

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