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About this paper
Álvaro G. Iñesta, Gayane Vardoyan, Lara Scavuzzo, Stephanie Wehner
Iñesta et al. from QuTech developed a generalized Markov Decision Process (MDP) model for quantum repeater chains that accounts for imperfect quantum memories and cutoff times to maintain entanglement fidelity. Their optimal global-knowledge policies can reduce the expected entanglement delivery time by up to 13.2% compared to immediate-swapping strategies, with the advantage becoming more pronounced in longer chains.
Key insights
- The success probability of entanglement swaps (p_s) is a dominant parameter, with deterministic swaps (p_s=1) yielding orders of magnitude faster expected delivery times.
- Optimal policies frequently involve strategic waiting and do not always perform all possible entanglement swaps, especially in longer chains or under specific entanglement generation and cutoff conditions.
- The performance advantage of optimal global-knowledge policies over simple 'swap-asap' strategies consistently increases with the number of nodes (n) in the repeater chain.
Summary by alphaXiv.
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