Efficient algorithm for optimizing data pattern tomography
arXiv:1407.0959 · doi:10.1103/PhysRevA.89.054102
Abstract
We give a detailed account of an efficient search algorithm for the data pattern tomography proposed by J. Rehacek, D. Mogilevtsev, and Z. Hradil [Phys. Rev. Lett.~\textbf{105}, 010402 (2010)], where the quantum state of a system is reconstructed without a priori knowledge about the measuring setup. The method is especially suited for experiments involving complex detectors, which are difficult to calibrate and characterize. We illustrate the approach with the case study of the homodyne detection of a nonclassical photon state.
5 pages, 5 eps-color figures
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- When quantum state tomography benefits from willful ignorance
- Sampling and the complexity of nature