• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Journal articles
    • View Item
    • Home
    • Griffith Research Online
    • Journal articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Characterization and control of open quantum systems beyond quantum noise spectroscopy

    Thumbnail
    View/Open
    Paz Silva457141-Published.pdf (1.580Mb)
    File version
    Version of Record (VoR)
    Author(s)
    Youssry, A
    Paz-Silva, GA
    Ferrie, C
    Griffith University Author(s)
    Paz Silva, Gerardo A.
    Year published
    2020
    Metadata
    Show full item record
    Abstract
    The ability to use quantum technology to achieve useful tasks, be they scientific or industry related, boils down to precise quantum control. In general it is difficult to assess a proposed solution due to the difficulties in characterizing the quantum system or device. These arise because of the impossibility to characterize certain components in situ, and are exacerbated by noise induced by the environment and active controls. Here, we present a general purpose characterization and control solution making use of a deep learning framework composed of quantum features. We provide the framework, sample datasets, trained models, ...
    View more >
    The ability to use quantum technology to achieve useful tasks, be they scientific or industry related, boils down to precise quantum control. In general it is difficult to assess a proposed solution due to the difficulties in characterizing the quantum system or device. These arise because of the impossibility to characterize certain components in situ, and are exacerbated by noise induced by the environment and active controls. Here, we present a general purpose characterization and control solution making use of a deep learning framework composed of quantum features. We provide the framework, sample datasets, trained models, and their performance metrics. In addition, we demonstrate how the trained model can be used to extract conventional indicators, such as noise power spectra.
    View less >
    Journal Title
    npj Quantum Information
    Volume
    6
    Issue
    1
    DOI
    https://doi.org/10.1038/s41534-020-00332-8
    Copyright Statement
    © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
    Subject
    Nanotechnology
    Publication URI
    http://hdl.handle.net/10072/400733
    Collection
    • Journal articles

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander