Direct Detection of Surface Spins using Superconducting Qubits

ORAL

Abstract

Superconducting circuits are a promising platform for quantum sensing and information processing - applications which benefit from high coherence and minimal parasitic environmental coupling. A major impediment to realizing these traits is the presence of low-frequency magnetic flux noise which, in the case of flux-tunable qubits, promotes qubit dephasing. Flux noise is commonly blamed on the presence of paramagnetic surface environments created by adsorbed species such as molecular oxygen. We discuss the theory and experimental progress of high-sensitivity magnetic resonance experiments utilizing superconducting qubits with an applied in-plane magnetic field to detect parasitically coupled spins. Specifically, we focus on two categories of techniques: 1) passive techniques without spin excitation, and 2) active techniques that utilize spin excitation with local flux lines. Regarding passive methods, we discuss spin-locking and dynamical decoupling schemes. Regarding active methods, we implement local flux lines that strongly couple to native defects on the surface of SQUIDs and discuss schemes using either pulsed or continuous-wave surface spin driving.

*This material is based upon work supported in part by the National Science Foundation Graduate Research Fellowship under Grant No. 1745302, and in part by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the US Government.

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Presenters

  • David A Rower

    • MIT, Department of Physics
    • Massachusetts Institute of Technology MIT

Authors

  • David A Rower

    • MIT, Department of Physics
    • Massachusetts Institute of Technology MIT

  • Lauren Li

    • Massachusetts Institute of Technology MIT

  • Lamia Ateshian

    • Massachusetts Institute of Technology MIT

  • Bharath Kannan

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology MI

  • Kyle Serniak

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Dolev Bluvstein

    • Harvard University

  • Leon Ding

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology MI

  • Aziza Almanakly

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  • Jochen Braumueller

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology

  • David K Kim

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Alexander Melville

    • MIT Lincoln Laboratory
    • MIT Lincoln Lab

  • Bethany M Niedzielski

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Jonilyn L Yoder

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Mollie E Schwartz

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Terry P Orlando

    • Massachusetts Institute of Technology MIT

  • Joel I Wang

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology MI

  • Simon Gustavsson

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology

  • Riccardo Comin

    • Massachusetts Institute of Technology MI
    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology MIT

  • William D Oliver

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Research Laboratory of Electronics
    • MIT Lincoln Laboratory and Department of Electrical Engineering & Computer Science and Department of Physics, Massachusetts Institute of Technology