Adaptive Quantum Process Tomography via Linear Regression Estimation

Qi Yu, Daoyi Dong, Yuanlong Wang, Ian R. Petersen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    4 Citations (Scopus)

    Abstract

    This paper proposes a recursively adaptive tomography protocol to improve the precision of quantum process estimation for finite dimensional systems. The problem of quantum process tomography is firstly formulated as a parameter estimation problem which can then be solved by the linear regression estimation method. An adaptive algorithm is proposed for the selection of subsequent input states given the previous estimation results. Numerical results show that the proposed adaptive process tomography protocol can achieve an improved level of estimation performance.

    Original languageEnglish
    Title of host publication2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4173-4178
    Number of pages6
    ISBN (Electronic)9781728185262
    DOIs
    Publication statusPublished - 11 Oct 2020
    Event2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 - Toronto, Canada
    Duration: 11 Oct 202014 Oct 2020

    Publication series

    NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    Volume2020-October
    ISSN (Print)1062-922X

    Conference

    Conference2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
    Country/TerritoryCanada
    CityToronto
    Period11/10/2014/10/20

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