Minimizing measurement resources for quantum tomography

Areeya Chantasri, Shengshi Pang, Teerawat Chalermpusitarak +1 more

Areeya Chantasri, Shengshi Pang, Teerawat Chalermpusitarak +1 more

Daniel F. V. James, Nathan K. Langford, Alexei Gilchrist +1 more

We show that it is possible to perform tomographic characterization of the state of a n-qubit quantum system by performing measurement on a single component only. Implications for quantum information technology will be discussed.

Anirudh Acharya, Theodore Kypraios, Mădălin Guţǎ

Nathan K. Langford, Alexei Gilchrist, Andrew G. White +1 more

We show that it is possible to perform tomographic characterization of the state of a n-qubit quantum system by performing measurement on a single component only. Implications for quantum information technology will be discussed.

Robert L. Kosut

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.