Distinguishing radiation- and non-radiation-induced correlated errors in superconducting qubits

ORAL

Abstract

Spatiotemporally correlated errors in superconducting qubits pose problems for quantum error correction algorithms. Ionizing radiation from cosmic rays and terrestrial sources has been identified as a cause of correlated errors. Various mitigation strategies are being tested, including reducing the sensitivity of qubits to quasiparticles by adjusting the gap across the Josephson junctions within the qubit circuit. In order to identify and study various types of these errors, we developed algorithms to distinguish events characteristic of particle impacts in the substrate from other types of correlated errors. We examined the distinguishing features and sources of radiation- and non-radiation-induced events. We will present results from both standard and gap-engineered devices, to elucidate how gap engineering changes qubit response to different sources of spatiotemporally correlated errors.

*This research is sponsored by the U.S. Army Research Office under Award No. W911NF-23-1-0045 (Extensible and Modular Advanced Qubits), and 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 U.S. Government.

Presenters

  • Hannah P Binney

    • Massachusetts Institute of Technology

Authors

  • Hannah P Binney

    • Massachusetts Institute of Technology
  • Doug Pinckney

    • Massachusetts Institute of Technology
  • Kate Azar

    • Massachusetts Institute of Technology
    • MIT
    • MIT Lincoln Laboratory
  • Patrick M Harrington

    • MIT
    • Massachusetts Institute of Technology
  • Aranya Goswami

    • Massachusetts Institute of Technology
  • Max Hays

    • MIT
    • Massachusetts Institute of Technology (MIT)
    • Massachusetts Institute of Technology
  • Jiatong Yang

    • MIT
    • Massachusetts Institute of Technology
  • Wouter Van De Pontseele

    • Massachusetts Institute of Technology
  • Felipe Contipelli

    • MIT Lincoln Laboratory
  • Renée DePencier Piñero

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, MIT
  • Hannah M Stickler

    • MIT Lincoln Laboratory
  • Mallika T Randeria

    • MIT Lincoln Laboratory
  • Bethany M Niedzielski

    • MIT Lincoln Laboratory
  • Michael Gingras

    • MIT Lincoln Laboratory
  • Mollie E Schwartz

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology
  • Jeffrey A Grover

    • Massachusetts Institute of Technology
  • Kyle Serniak

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology
  • Joseph A Formaggio

    • Massachusetts Institute of Technology
  • William D Oliver

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology (MIT)