Imperfect suppression of quasiparticle-induced dissipation in fluxonium qubits

ORAL

Abstract

Nonequilibrium quasiparticles generated by stray infrared and ionizing radiation present a challenge to the coherence and scaling of superconducting-qubit-based quantum processors. Standard models of quasiparticle-induced errors typically assume that the characteristic energy of the quasiparticles and the qubit frequency are small relative to the superconducting gap. Under these assumptions, flux tunable qubits such as fluxonium would exhibit suppressed sensitivity to quasiparticle loss at specific bias points. Motivated by the notion that these assumptions would not hold during error "burst" events caused by ionizing radiation, we numerically study the rate of quasiparticle-induced qubit errors in fluxonium qubits for arbitrary quasiparticle energy distributions. We find even away from burst events, with typical qubit frequencies and "cold" quasiparticles, the aforementioned assumptions do not necessarily hold, necessitating a reevaluation of quasiparticle protection in various qubit circuits. This presentation will discuss the interplay of various assumptions in the theory of quasiparticle-induced errors and describe experimental prospects for validating this theory.

*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

    • Massachusetts Institute of Technology
    • MIT

Authors

  • Kate Azar

    • Massachusetts Institute of Technology
    • MIT
  • Max Hays

    • Massachusetts Institute of Technology
  • Renée D DePencier Piñero

    • MIT Lincoln Laboratory
  • Jeffrey M Gertler

    • MIT Lincoln Laboratory
  • Felipe Contipelli

    • MIT Lincoln Laboratory
  • Michael A Gingras

    • MIT Lincoln Laboratory
  • Bethany M Niedzielski

    • MIT Lincoln Laboratory
  • Mallika T Randeria

    • MIT Lincoln Laboratory
  • Hannah M Stickler

    • MIT Lincoln Laboratory
  • Kunal L. Tiwari

    • MIT Lincoln Laboratory
  • Jeffrey A Grover

    • Massachusetts Institute of Technology
  • Mollie E. Schwartz

    • MIT Lincoln Laboratory
  • William D Oliver

    • Massachusetts Institute of Technology
  • Kyle Serniak

    • MIT Lincoln Laboratory