Realizing Lattice Surgery on Two Distance-Three Repetition Codes with Superconducting Qubits, Part 1: Logical Bell State Preparation

ORAL

Abstract

Quantum error correction provides a pathway toward quantum computers capable of fault-tolerantly executing algorithms involving millions of qubits. A recent experiment with superconducting qubits has demonstrated sub-threshold distance-scaling of error rates for a single logical qubit [1]. However, the realization of universal quantum computation requires logical entangling gates, for which lattice surgery offers a practical approach. In this work, we encode a logical qubit in a distance-three surface code of superconducting qubits and employ a lattice surgery split operation to prepare an entangled state of two distance-three repetition codes. By stabilizing the surface code qubit and performing mid-cycle data qubit readout followed by Pauli frame updates, we herald one of the four logical Bell states. Using a quantum circuit fault-tolerant to bit-flip errors, we achieve an improvement in the value of the decoded ZZ logical two-qubit observable compared to a similar non-encoded circuit, demonstrating the effectiveness of our error-correction scheme, focusing on bit-flip errors.

[1] Google Quantum AI, arXiv:2408.13687 (2024)

*Research was sponsored by IARPA and the Army Research Office, under the Entangled Logical Qubits program, and was accomplished under Cooperative Agreement Number W911NF-23-2-0212, by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number UeM019-11, by Innosuisse via the Innovation project (104.020 IP-ICT / Agreement Nr. 2155012229), by the SNSF R'equip grant 206021-170731, by the Baugarten Foundation and the ETH Zurich Foundation, and by ETH Zurich. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of IARPA, the Army Research Office, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

Presenters

  • Michael Kerschbaum

    • ETH Zurich
    • ETH Zurich, Paul Scherrer Institute

Authors

  • Michael Kerschbaum

    • ETH Zurich
    • ETH Zurich, Paul Scherrer Institute
  • Ilya Besedin

    • ETH Zurich, Paul Scherrer Institute
  • Jonathan Knoll

    • ETH Zurich
  • Ian Hesner

    • ETH Zurich
    • ETH Zurich, Paul Scherrer Institute
  • Lukas Bödeker

    • Forschungszentrum Jülich GmbH, RWTH Aachen
  • Luis Colmenarez

    • Forschungszentrum Jülich GmbH, RWTH Aachen
  • Luca Hofele

    • ETH Zurich
  • Nathan Lacroix

    • Google LLC, ETH Zurich
    • ETH Zurich
  • Christoph Hellings

    • ETH Zurich
  • François Swiadek

    • ETH Zurich
  • Alexander Flasby

    • ETH Zurich
    • ETH Zurich, Paul Scherrer Institute
    • ETH Zürich
  • Mohsen Bahrami Panah

    • ETH Zurich, Paul Scherrer Institute
  • Dante Colao Zanuz

    • ETH Zurich
  • Markus Müller

    • Forschungszentrum Jülich GmbH
    • Forschungszentrum Jülich GmbH, RWTH Aachen
  • Andreas Wallraff

    • ETH Zurich
    • ETH Zurich, Paul Scherrer Institute