• DocumentCode
    592515
  • Title

    Estimation of quantum channels: Identifiability and ML methods

  • Author

    Zorzi, Michele ; Ticozzi, Francesco ; Ferrante, Augusto

  • Author_Institution
    Dipt. di Ing. dell´Inf., Univ. di Padova, Padova, Italy
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    1674
  • Lastpage
    1679
  • Abstract
    We determine the minimal experimental resources that ensure a unique solution in the estimation of trace-preserving quantum channels with both direct and convex optimization methods. A convenient parametrization of the constrained set is used to develop a globally converging Newton-type algorithm that ensures a physically admissible solution to the problem. Numerical simulations are provided to support the results, and indicate that the minimal experimental setting is sufficient to guarantee good estimates.
  • Keywords
    Newton method; convex programming; discrete systems; maximum likelihood estimation; ML method; constrained set parametrization; convex optimization; direct optimization method; globally converging Newton-type algorithm; identifiability; maximum likelihood method; numerical simulation; trace-preserving quantum channel estimation; Encoding; Lead;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6426789
  • Filename
    6426789