Characterization and comparison of energy relaxation in planar fluxonium qubits

ORAL

Abstract

Fluxonium superconducting qubits have demonstrated high coherence times and high single and two qubit gate fidelities, making them a promising building block for superconducting quantum processors. In this work, we characterize the energy relaxation times T1 of multiple fluxonium qubits across their tunable frequency range in order to assess the dominant contributors to decoherence. Of the mechanisms considered, a circuit-based model for capacitive loss best captures the trends in the data over the majority of the tuning range. Motivated by this, we also consider modifications to this model accounting for a frequency-dependent effective capacitive quality factor. Furthermore, we use this analysis to bound the contributions of various other loss mechanisms. Finally, we utilize a composite model to compare these loss mechanisms on equal footing across individual qubits, and compare qubits fabricated with different materials processing techniques.

*This material is based upon work supported under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. government or the U.S. Air Force.

Presenters

  • Kate Azar

    • Wellesley College

Authors

  • Kate Azar

    • Wellesley College
  • Mallika T Randeria

    • MIT Lincoln Laboratory
  • Renée D DePencier Piñero

    • MIT Lincoln Laboratory
  • Jeffrey M Gertler

    • MIT Lincoln Laboratory
  • Lamia Ateshian

    • Massachusetts Institute of Technology
  • Helin Zhang

    • Massachusetts Institute of Technology
  • Junyoung An

    • Massachusetts Institute of Technology
  • Felipe Contipelli

    • MIT Lincoln Laboratory
  • Michael Gingras

    • MIT Lincoln Laboratory
  • Kevin A Grossklaus

    • MIT Lincoln Laboratory
  • Max Hays

    • MIT
    • Massachusetts Institute of Technology (MIT)
    • Massachusetts Institute of Technology
  • Thomas M Hazard

    • MIT Lincoln Laboratory
  • David K Kim

    • MIT Lincoln Lab
    • Lincoln Laboratory, Massachusetts Institute of Technology
  • Junghyun Kim

    • Massachusetts Institute of Technology
  • Bethany M Niedzielski

    • MIT Lincoln Laboratory
  • Ilan T Rosen

    • Massachusetts Institute of Technology
  • Hannah M Stickler

    • MIT Lincoln Laboratory
  • Kunal L. Tiwari

    • MIT Lincoln Laboratory
  • Jeffrey A Grover

    • Massachusetts Institute of Technology (MIT)
    • Massachusetts Institute of Technology
    • MIT
  • Jonilyn L Yoder

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology
  • Mollie E Schwartz

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology
  • William D Oliver

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

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology