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Efficient and Versatile Control of a Long-Lived 3D Multimode Quantum Processing Unit

ORAL

Abstract

Superconducting radio-frequency (SRF) cavities, such as TESLA-shaped cavities, are excellent candidates for long-lived quantum memories. Integrating these cavities with nonlinear elements, such as transmons, enables universal quantum control; however, this integration can often introduce unwanted losses. In this talk, we present the successful integration of a long-lived 2-cell TESLA cavity with an ancillary qubit, forming a quantum processing unit (QPU) that allows for robust control while maintaining coherence. We demonstrate universal control of the QPU through various schemes, including ancilla-cavity sideband and echoed conditional displacement (ECD) methods, enabling fault-tolerant high-fidelity preparation of large Fock states and fast entanglement generation. These results illustrate the versatility and efficiency of our 3D quantum processing unit, paving the way for advanced quantum computing applications.

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Publication: A Long-Lived Multimode Quantum Processing Unit with Versatile Universal Control, in preparation

Presenters

  • Taeyoon Kim

    Northwestern University

Authors

  • Taeyoon Kim

    Northwestern University

  • Yao Lu

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Tanay Roy

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Xinyuan You

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Oleg V Pronitchev

    Fermi National Accelerator Laboratory (Fermilab), Fermilab, Fermi National Accelerator Laboratory

  • Mustafa Bal

    Fermi National Accelerator Laboratory, Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Sabrina Garattoni

    Fermilab, Fermi National Accelerator Laboratory (Fermilab), Fermi National Accelerator Laboratory

  • Francesco Crisa

    Fermi National Accelerator Laboratory, Fermilab, Fermilab, SQMS, Fermi National Accelerator Laboratory (Fermilab)

  • Daniel Bafia

    Fermi National Accelerator Laboratory (Fermilab), Fermilab, Fermi National Accelerator Laboratory

  • Roman M Pilipenko

    Fermilab, Fermi National Accelerator Laboratory

  • Paul Heidler

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Andy C. Y. Li

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Yunwei Lu

    Northwestern University

  • David V Zanten

    Fermi National Accelerator Laboratory (Fermilab), Fermilab, Fermi National Accelerator Laboratory

  • Silvia Zorzetti

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Roni Harnik

    Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Akshay Murthy

    Fermi National Accelerator Laboratory, Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Shaojiang Zhu

    Fermi National Accelerator Laboratory (Fermilab), Fermilab, Fermi National Accelerator Laboratory

  • André Vallières

    Northwestern University

  • Ziwen Huang

    Fermi National Accelerator Laboratory, Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Jens Koch

    Northwestern University

  • Anna Grassellino

    Fermi National Accelerator Laboratory, Fermi National Accelerator Laboratory (Fermilab), Fermilab

  • Srivatsan Chakram

    Rutgers University, Rutgers, The State University of New Jersey

  • Alexander Romanenko

    Fermi National Accelerator Laboratory, Fermi National Accelerator Laboratory (Fermilab), Fermilab