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All RF-based tuning algorithm for quantum devices using machine learning

ORAL

Abstract

Radio-frequency measurements could satisfy DiVincenzo's readout criterion in future large-scale solid-state quantum processors, as they allow for high bandwidths and frequency multiplexing. To realise the potential for scalability of this readout technique, quantum device tuning will have to be performed using just RF measurements, making no use of measurements of current through the device. By exploiting their bandwidth and impedance matching, we demonstrate an algorithm that automatically tunes double quantum dots with only radio-frequency measurements. The tuning was completed within a few minutes without prior knowledge about the device architecture. Our results show that it is possible to eliminate the need for transport measurements for quantum dot tuning, paving the way for more scalable device architectures.

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Publication: All RF-based tuning algorithm for quantum devices using machine learning

Presenters

  • Barnaby van Straaten

    Oxford University

Authors

  • Barnaby van Straaten

    Oxford University

  • Federico Fedele

    Niels Bohr Institute, University of Copenhagen, University of Oxford, University Of Oxford

  • Florian Vigneau

    University of Oxford, University of Oxford Materials Department

  • Joseph Hickie

    University of Oxford, University of Oxford Materials Department

  • Andrea Ballabio

    L-NESS, Physics Department, Politecnico di Milano, Politecnico di Milano, L-NESS, Physics Department, Politecnico di Milano, 22100 Como, Italy, L-NESS, Physics Department, Politecnico di Milano, via Anzani 42, 22100, Como, Italy, L-NESS, Politecnico di Milano

  • Daniel Chrastina

    L-NESS, Physics Department, Politecnico di Milano, Politecnico di Milano, L-NESS, Physics Department, Politecnico di Milano, 22100 Como, Italy, L-NESS, Physics Department, Politecnico di Milano, via Anzani 42, 22100, Como, Italy, L-NESS, Politecnico di Milano

  • Georgios Katsaros

    Institute of Science and Technology Austria, IST Austria, Institute of Science and Technology Austria (ISTA), 3400 Klosterneuburg, Austria, Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria

  • Daniel Jirovec

    Delft University of Technology, Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria

  • Natalia Ares

    University of Oxford