Charge-Ramp Demodulated Sensing in an Offset-Charge Sensitive Transmon Array

Oral-In-person

Abstract

Modern quantum error correction can be hampered by spatiotemporal-correlated errors, limiting the utility of superconducting qubit processors. The underlying dynamics of nonequilibrium quasiparticles during such an event can be investigated by monitoring the charge-parity in offset-charge-sensitive transmons. However, continuous monitoring is impeded by low-frequency charge noise; some protocols require frequent recalibration of the offset-charge bias point, obscuring visibility of the charge-parity following large discrete offset-charge jumps. In this work, we propose a novel charge-sensing scheme, using direct-dispersive readout in the ground-state manifold, while applying an external voltage modulation, for high-bandwidth extraction of the offset-charge (thus inferring the charge-parity state without interruption). We use this technique to investigate spatiotemporally correlated errors by simultaneously monitoring 4 qubits in an OCS transmon array, demonstrating an offset-charge resolution within 0.1e at a ~1kHz detection bandwidth.

Presenters

  • Felipe Contipelli

    • MIT Lincoln Laboratory

Authors

  • Felipe Contipelli

    • MIT Lincoln Laboratory
  • Jeffrey Gertler

    • MIT Lincoln Laboratory
  • Serra Erdamar

  • Doug Pinckney

    • Massachusetts Institute of Technology
  • Kate Azar

    • MIT Lincoln Laboratory
  • Renée DePencier Piñero

  • Michael Gingras

    • MIT Lincoln Laboratory
  • Patrick Harrington

    • Massachusetts Institute of Technology
  • Max Hays

    • Massachusetts Institute of Technology
  • David Kim

    • MIT Lincoln Lab
  • Bethany Niedzielski

    • MIT Lincoln Laboratory
  • Mallika Randeria

    • MIT Lincoln Laboratory
  • Hannah Stickler

    • MIT Lincoln Laboratory
  • Jeffrey Grover

    • Massachusetts Institute of Technology
  • Joseph Formaggio

    • Massachusetts Institute of Technology
  • Mollie Schwartz

    • MIT Lincoln Laboratory
  • William Oliver

    • Massachusetts Institute of Technology
  • Kyle Serniak

    • MIT Lincoln Laboratory