Quantum Process Tomography via L1-norm Minimization

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dc.creatorKosut, Robert L.
dc.date2008-12-23
dc.date2009-03-05
dc.date.accessioned2026-07-07T12:48:54Z
dc.date.available2026-07-07T12:48:54Z
dc.descriptionFor 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.
dc.description4 pages, 2 figures, corrected typos, minor content clarifications
dc.identifierhttps://arxiv.org/abs/0812.4323
dc.identifierhttp://arxiv.org/abs/0812.4323
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/222222
dc.subjectQuantum Physics
dc.titleQuantum Process Tomography via L1-norm Minimization
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