Improving readout of a superconducting qubit using the path signature method

ORAL

Abstract

One major challenge in quantum computing is to implement fast, high-accuracy quantum state readout. For superconducting circuits, this problem reduces to a time series classification problem [1]. We propose that using path signature methods to extract features can enhance existing techniques for quantum state discrimination [2]. We demonstrate the superior performance of our proposed approach over conventional methods in distinguishing three different quantum states on real experimental data from a superconducting transmon qubit.

[1] J Heinsoo, C Andersen, A Remm, S Krinner, T Walter, Y Salathé, S Gasparinetti, J Besse, A Potočnik, A Wallraff, C Eichler. Phys. Rev. Applied 10, 034040

[2] J Morrill, A Fermanian, P Kidger, T Lyons. arXiv preprint arXiv:2006.00873, 2020

* This project is supported by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a Schmidt Future program. S. C. was supported by Schmidt Futures. J.Q. Z. was supported by the Kennedy Trust Prize Studentship [AZT00050-AZ04]. Z. S. was supported by the EPSRC [EP/S026347/1]. T. L. was funded in part by the EPSRC [EP/S026347/1], in part by The Alan Turing Institute under the EPSRC [EP/N510129/1], the Data Centric Engineering Programme (under the Lloyd's Register Foundation grant G0095), the Defence and Security Programme (funded by the UK Government) and in part by the Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA). The authors would like to acknowledge the use of the University of Oxford Advanced Research Computing (ARC) facility in carrying out this work.

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Presenters

  • Shuxiang Cao

    University of Oxford

Authors

  • Shuxiang Cao

    University of Oxford

  • Zhen Shao

    University of Oxford

  • Jian-Qing Zheng

    University of Oxford

  • Mohammed Alghadeer

    University of California, Berkeley, University of Oxford

  • Simone D Fasciati

    University of Oxford

  • Michele Piscitelli

    University of Oxford

  • Sajjad Taravati

    University of Oxford

  • Mustafa S Bakr

    University of Oxford

  • Terry Lyons

    University of Oxford

  • Peter J Leek

    University of Oxford