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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.

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