Efficient identification of unitary quantum processes

Yuanlong Wang, Qi Yin, Daoyi Dong, Bo Qi, Ian R. Petersen, Zhibo Hou, Hidehiro Yonezawa, Guo Yong Xiang

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

    2 Citations (Scopus)

    Abstract

    Identifying an unknown unitary quantum process is a fundamental task in the development of quantum technology. In this paper, we propose an efficient identification algorithm for estimating unitary processes. In the method, input pure states are used and a fast quantum state tomography algorithm is developed to reconstruct the output states. Then the information of the output states is used to estimate the unitary process. The identification algorithm has computational complexity O(d3) for a d-dimensional system. Numerical results show that the proposed identification algorithm is much more efficient than the maximum likelihood estimation method and works well for input mixed states with high purity. An analytical upper bound for the identification error is also provided, and numerical simulations and experimental results on quantum optical systems verify the theoretical results.

    Original languageEnglish
    Title of host publication2017 Australian and New Zealand Control Conference, ANZCC 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages196-201
    Number of pages6
    ISBN (Electronic)9781538621783
    DOIs
    Publication statusPublished - 2 Jul 2017
    Event1st Australian and New Zealand Control Conference, ANZCC 2017 - Gold Coast, Australia
    Duration: 17 Dec 201720 Dec 2017

    Publication series

    Name2017 Australian and New Zealand Control Conference, ANZCC 2017
    Volume2018-January

    Conference

    Conference1st Australian and New Zealand Control Conference, ANZCC 2017
    Country/TerritoryAustralia
    CityGold Coast
    Period17/12/1720/12/17

    Fingerprint

    Dive into the research topics of 'Efficient identification of unitary quantum processes'. Together they form a unique fingerprint.

    Cite this