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.

*This work was supported by the Royal Society, the EPSRC National Quantum Technology Hub in Networked Quantum Information Technology (EP/M013243/1), Quantum Technology Capital (EP/N014995/1), EPSRC Platform Grant (EP/R029229/1), the European Research Council (Grant agreement 948932), the Scientific Service Units of IST Austria through resources provided by the nanofabrication facility and, the FWF-P 30207 and FWF-I 05060 projects.

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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