Benchmarking a Quantum Random Number Generator with Machine Learning

Jing Yan Haw*, Nhan Duy Truong, Hong Jie Ng, Raymond Ho, Syed Assad, Chao Wang, Ping Koy Lam, Omid Kavehei

*Corresponding author for this work

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

    Abstract

    We develop a predictive machine learning (ML) analysis to examine the uniformity and unpredictability aspects of a random number generator. We show that our tool is capable of uncovering hidden correlations and experimental imperfections.

    Original languageEnglish
    Title of host publicationQuantum Information and Measurement, ICQI 2021
    PublisherOptica Publishing Group
    ISBN (Electronic)9781957171012
    Publication statusPublished - 2021
    EventConference on Quantum Information and Measurement, ICQI 2021 - Virtual, Online, United States
    Duration: 1 Nov 20215 Nov 2021

    Publication series

    NameOptics InfoBase Conference Papers
    ISSN (Electronic)2162-2701

    Conference

    ConferenceConference on Quantum Information and Measurement, ICQI 2021
    Country/TerritoryUnited States
    CityVirtual, Online
    Period1/11/215/11/21

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