Erasure Qubits Based on an Integer Fluxonium

ORAL

Abstract

Within error correction architectures, erasure qubits can significantly improve error threshold and code distance by converting the most common errors in the system into detectable erasure errors. In superconducting circuits, erasure qubits have been implemented with dual-rail transmons and high-Q cavities. These designs have demonstrated improved logical state coherence and gate fidelity after erasure error correction. However, dual-rail architectures require more than a single physical qubit to implement one erasure qubit, thus increasing overhead. In this talk, we present an erasure qubit design based on a single integer fluxonium. We demonstrate basic characterization results of the integer fluxonium and assess its potential as an erasure qubit. The next phase of our work will involve implementing an erasure check protocol and quantifying the improvement in the logical state coherence time from erasure checks.

*This research was sponsored by the Army Research Office under Award No. W911NF-23-1-0045; in part by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-design Center for Quantum Advantage (C2QA) under contract number DE-SC0012704; and in part under Air Force Contract No. FA8702-15-D-0001. J.A. acknowledges support from Korea Foundation for Advanced Studies. The views and conclusions contained herein are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.

Presenters

  • Junyoung An

    • Massachusetts Institute of Technology

Authors

  • Junyoung An

    • Massachusetts Institute of Technology
  • Helin Zhang

    • Massachusetts Institute of Technology
  • Max Hays

    • Massachusetts Institute of Technology
  • Junghyun Kim

    • Massachusetts Institute of Technology
  • Ilan T Rosen

    • Massachusetts Institute of Technology
  • David A Rower

    • MIT, Department of Physics
    • MIT, Department of Physics, Google Quantum AI
  • Kate Azar

    • Massachusetts Institute of Technology
    • MIT
  • Jeffrey M Gertler

    • MIT Lincoln Laboratory
  • Michael A Gingras

    • MIT Lincoln Laboratory
  • Thomas M Hazard

    • MIT Lincoln Laboratory
  • Bethany M Niedzielski

    • MIT Lincoln Laboratory
  • Mallika T Randeria

    • MIT Lincoln Laboratory
  • Hannah M Stickler

    • MIT Lincoln Laboratory
  • Mollie E. Schwartz

    • MIT Lincoln Laboratory
  • Joel I-Jan Wang

    • Massachusetts Institute of Technology
  • Terry Philip Orlando

    • Massachusetts Institute of Technology
  • Simon Gustavsson

    • Massachusetts Institute of Technology
  • Jeffrey A Grover

    • Massachusetts Institute of Technology
  • Kyle Serniak

    • MIT Lincoln Laboratory
  • William D Oliver

    • Massachusetts Institute of Technology