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    New Study uses Machine Learning to Bridge the Reality Gap in Quantum Devices

    January 11, 2024, Categories  Physics

    New study uses machine learning to bridge the reality gap in quantum devices
    (a) Device geometry including the gate electrodes (labeled G1–G8), donor ion plane, and an example disorder potential experienced by confined electrons. Typical flow of current from source to drain is indicated by the white arrow. (b) Schematic of the disorder inference process. Colors indicate the following: red for experimentally controllable variables, green for quantities relevant to the electrostatic model, blue for experimental device, and yellow for machine learning methods. Dashed arrows represent the process of generating training data for the deep learning approximation and are not part of the disorder inference process. Credit: Physical Review X (2024). DOI: 10.1103/PhysRevX.14.011001

    A study led by the University of Oxford has used the power of machine learning to ove...

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