• Smart quantum technologies for secure co

    From ScienceDaily@1337:3/111 to All on Tue Mar 16 22:30:30 2021
    Smart quantum technologies for secure communication

    Date:
    March 16, 2021
    Source:
    Louisiana State University
    Summary:
    Researchers have introduced a smart quantum technology for the
    spatial mode correction of single photons. The authors exploit
    the self-learning and self-evolving features of artificial neural
    networks to correct the distorted spatial profile of single photons.



    FULL STORY ========================================================================== Researchers from Louisiana State University have introduced a smart
    quantum technology for the spatial mode correction of single photons. In
    a paper featured on the cover of the March 2021 issue of Advanced Quantum Technologies, the authors exploit the self-learning and self-evolving
    features of artificial neural networks to correct the distorted spatial
    profile of single photons.


    ==========================================================================
    The authors, PhD candidate Narayan Bhusal, postdoctoral researcher
    Chenglong You, graduate student Mingyuan Hong, undergraduate student
    Joshua Fabre, and Assistant Professor Omar S. Magan~a?Loaiza of LSU --
    together with collaborators Sanjaya Lohani, Erin M. Knutson, and Ryan
    T. Glasser of Tulane University and Pengcheng Zhao of Qingdao University
    of Science and Technology - - report on the potential of artificial intelligence to correct spatial modes at the single-photon level.

    "The random phase distortion is one of the biggest challenges in using
    spatial modes of light in a wide variety of quantum technologies, such
    as quantum communication, quantum cryptography, and quantum sensing,"
    said Bhusal. "In this paper, we use artificial neurons to correct
    distorted spatial modes of light at the single-photon level. Our method
    is remarkably effective and time- efficient compared to conventional techniques. This is an exciting development for the future of free-space quantum technologies." The newly developed technique boosts the channel capacity of optical communication protocols that rely on structured
    photons.

    "One important goal of the Quantum Photonics Group at LSU is to develop
    robust quantum technologies that work under realistic conditions,"
    said Magan~a?Loaiza. "This smart quantum technology demonstrates the possibility of encoding multiple bits of information in a single photon in realistic communication protocols affected by atmospheric turbulence. Our technique has enormous implications for optical communication and
    quantum cryptography. We are now exploring paths to implement our machine learning scheme in the Louisiana Optical Network Initiative (LONI) to
    make it smart, secure, and quantum." "We are still in the fairly early
    stages of understanding the potential for machine learning techniques
    to play a role in quantum information science," said Dr. Sara Gamble,
    program manager at the Army Research Office, an element of DEVCOM
    ARL. "The team's result is an exciting step forward in developing
    this understanding, and it has the potential to ultimately enhance
    the Army's sensing and communication capabilities on the battlefield." ========================================================================== Story Source: Materials provided by Louisiana_State_University. Note:
    Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Narayan Bhusal, Sanjaya Lohani, Chenglong You, Mingyuan Hong, Joshua
    Fabre, Pengcheng Zhao, Erin M. Knutson, Ryan T. Glasser, Omar S.

    Magan~a‐Loaiza. Spatial Mode Correction of Single Photons
    Using Machine Learning. Advanced Quantum Technologies, 2021; 4
    (3): 2000103 DOI: 10.1002/qute.202000103 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2021/03/210316093442.htm

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