Entanglement Distillation and Swapping Scheduling in Quantum Repeaters with Noisy Memories

As near-term quantum networks face significant limitations from finite memory coherence times, researchers must determine the optimal timing and ordering of entanglement distillation and swapping. This paper investigates how to schedule these operations in one-hop and two-hop repeater chains to maximize the quality and utility of the final entangled state.

To isolate the effects of memory decoherence, the authors analyze elementary building blocks of quantum networks. For a one-hop link, they analytically compare three strategies: Distill-ASAP (as soon as possible), Distill-ALAP (as late as possible), and Discard-Oldest. For two-hop repeater chains, they extend the analysis using Monte Carlo simulations to evaluate seven distinct scheduling strategies, measuring performance through expected output fidelity, success probability, and weighted coherent information.

The study reveals that the optimal strategy depends heavily on the memory coherence regime. In low-coherence environments, simply discarding the oldest entangled state is effective for maintaining fidelity. However, in high-coherence regimes, delaying distillation until the end of the time window (Distill-ALAP) provides the highest weighted coherent information. In two-hop chains, deferring distillation remains superior, with specific strategies like Distill-ALAP-then-Swap-ALAP and Swap-ASAP-then-Distill-ALAP performing best depending on the operational deadline. These findings demonstrate that memory decoherence fundamentally reshapes the optimal timing of network operations.

These results provide critical link-level principles for designing larger-scale quantum repeater architectures. By clarifying the tradeoffs between immediate operation and deferred processing, the study offers a roadmap for optimizing quantum network performance under realistic, noisy conditions, moving beyond the idealized assumption of perfect quantum memories.