High-Fidelity Qutrit Entanglement in Superconducting Circuits

ORAL

Abstract

The workhorse qubit of modern superconducting systems – the transmon – has readily addressable higher states making it also a natural platform for qutrit operation. Provided high-fidelity multi-qutrit control, the larger, more connected computational space leveraged in a ternary approach to quantum computation can enable improvements to quantum simulation and error correction. Nonetheless, a significant impediment to realizing effective qutrit processing in a superconducting platform has been the ability to generate high-fidelity qutrit entangling gates. Recently, utilizing the Differential AC-Stark effect, we have demonstrated a dynamic cross-Kerr interaction between two fixed-frequency transmon qutrits and leveraged it to generate high-fidelity, maximally-entangling qutrit controlled-phase gates. Additionally, enabling coherent control over the full multi-qutrit Hilbert space allows one to compactly generate multi-controlled qubit entangling gates and achieve greater flexibility in generating two-qubit gates. In this talk, we present advanced control and characterization techniques in transmon qutrits that we leverage for high-fidelity qutrit entangling operations to improve both binary and ternary approaches to quantum computation.

*This work was funded by the Office of Advanced Scientific Computing Research, Testbeds for Science program, Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 and supported by the National Science Foundation under Grant No. 2210391 and also supported by the National Science Foundation under Grant No. 2210391.

Publication: High-Fidelity Qutrit Entangling Gates for Superconducting Circuits https://arxiv.org/abs/2206.07216

Presenters

  • Noah Goss

    • University of California Berkeley

Authors

  • Noah Goss

    • University of California Berkeley
  • Long B Nguyen

    • Lawrence Berkeley National Laboratory
  • Ravi K Naik

    • Lawrence Berkeley National Laboratory
  • Alexis Morvan

    • Google Quantum AI
  • Brian Marinelli

    • University of California, Berkeley
  • Brad Mitchell

    • Lawrence Berkeley National Laboratory
  • John Mark Kreikebaum

    • Lawrence Berkeley National Laboratory
  • Larry Chen

    • University of California, Berkeley
  • Christian Jünger

    • Lawrence Berkeley National Laboratory
    • University of California, Berkeley
  • David I Santiago

    • Lawrence Berkeley National Laboratory
  • Irfan Siddiqi

    • University of California, Berkeley
    • Lawrence Berkeley National Laboratory