Deterministic remote entanglement using a chiral quantum interconnect (Part 2)

ORAL

Abstract

Quantum interconnects facilitate entanglement distribution between non-local computational nodes. For superconducting processors, microwave photons are a natural means to mediate this distribution. However, many existing architectures are constrained by node connectivity and lack of directionality. In this work, we construct a chiral quantum interconnect between two nominally identical modules in separate microwave packages. We leverage quantum interference to emit and absorb microwave photons on demand and in a chosen direction between these modules [1, 2, 3]. We optimize the protocol using model-free reinforcement learning to maximize absorption efficiency. By halting the emission process halfway through its duration, we generate remote entanglement between modules in the form of a four-qubit W state with 62.4 ± 1.6% (leftward photon propagation) and 62.1 ± 1.2% (rightward) fidelity, limited mainly by propagation loss. This quantum network architecture enables all-to-all connectivity between non-local processors for modular and extensible quantum computation. In Part 2 of this series of talks, we will discuss future directions.



[1] Gheeraert, N. et al. Phys. Rev. A 102, 053720 (2020)



[2] Kannan, B., Almanakly, et al. Nat. Phys. 19, 394–400 (2023).



[3] Almanakly, A., Yankelevich, B. et al. arXiv:2408.05164 (2024)

*This research was funded in part by the Army Research Office under Award No. W911NF-23-1-0045 and by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. B.Y. acknowledges support from the Hertz Foundation and the National Science Foundation Graduate Research Program. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government.

–

Publication: Almanakly, A., Yankelevich, B. et al. arXiv:2408.05164 (2024)

Presenters

  • Beatriz Sarah Yankelevich

    • Massachusetts Institute of Technology

Authors

  • Beatriz Sarah Yankelevich

    • Massachusetts Institute of Technology

  • Aziza Almanakly

    • Massachusetts Institute of Technology

  • Max Hays

    • MIT
    • Massachusetts Institute of Technology (MIT)
    • Massachusetts Institute of Technology

  • Bharath Kannan

    • Atlantic Quantum

  • Réouven Assouly

    • Massachussets Institute of Technology
    • Ecole Normale Superieure de Lyon

  • Alex Greene

    • Google LLC

  • Michael Gingras

    • MIT Lincoln Laboratory

  • Bethany M Niedzielski

    • MIT Lincoln Laboratory

  • Hannah M Stickler

    • MIT Lincoln Laboratory

  • Mollie E Schwartz

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology

  • Kyle Serniak

    • MIT Lincoln Laboratory
    • Lincoln Laboratory, Massachusetts Institute of Technology

  • Joel I-Jan Wang

    • Massachusetts Institute of Technology

  • Terry P Orlando

    • Massachusetts Institute of Technology

  • Simon Gustavsson

    • Massachusetts Institute of Technology

  • Jeffrey A Grover

    • Massachusetts Institute of Technology

  • William D Oliver

    • Massachusetts Institute of Technology
    • Massachusetts Institute of Technology (MIT)