Hybrid repeaters with encoding for long distance entanglement distribution

ORAL

Abstract

Long-distance entanglement distribution will require error correction/distillation in order to compensate for the loss of coherence in quantum memories and noise addition during entanglement swapping. In this paper, we argue why repeaters with error correction abilities should utilize more than one physical platform. Hybrid repeaters introduced in this work utilize the best features of different platforms, such as high entanglement generation rates of one type and the low two-qubit gate errors and high coherence times offered by another type. At the same time, taking the resource-intensive nature of hybrid repeaters (financial or difficulty of deployment) into account, we propose an architecture where only some repeaters need to be hybrid, whereas the others can be simpler with no error correction abilities. We show through detailed simulations that these hybrid repeater architectures can outperform architectures that rely only on a single kind of quantum memory platform in terms of end-to-end fidelity and entanglement distribution rates/secret key rates. The advantage is greater in more resource-constrained scenarios, making hybrid architectures relevant for current implementations. Finally, we provide a concrete implementation scheme for a hybrid repeater chain using silicon-vacancy and ion-trap qubits as examples of the two constituent physical platforms. We evaluate its performance under hardware constraints and show that hybrid retains advantage over monolithic architectures.

*This work is supported by the "NSF Engineering Research Center for Quantum Networks (CQN)" awarded under Grant 1941583.

Publication: Accepted in IEEE QCE proceedings 2025

Presenters

  • Stav Haldar

    • University of Massachusetts Amherst

Authors

  • Stav Haldar

    • University of Massachusetts Amherst
  • Saikat Guha

    • University of Maryland, College Park
    • University of Maryland
  • Don Towsley

    • University of Massachusetts Amherst
  • Filip Rozpedek

    • University of Massachusetts Amherst