Sequential vs. Simultaneous Entanglement Swapping under Optimal Link-Layer Control
Priyam Srivastava, Akshat R. Sabavat, Siddharth Jain, Alan Scheller-Wolf, Sridhar Tayur, David Tipper, Prashant Krishnamurthy, Amy Babay, Kaushik P. Seshadreesan

TL;DR
This study compares sequential and simultaneous entanglement swapping in quantum networks, revealing that memory coherence time critically impacts the effectiveness of sequential swapping, which can outperform simultaneous methods under certain conditions.
Contribution
The paper provides a proof-of-principle analysis showing how memory coherence time influences the performance of sequential versus simultaneous entanglement swapping.
Findings
Simultaneous SWAP-ASAP maintains a constant secret-key rate across various coherence times.
Sequential swapping fails to deliver end-to-end entanglement below a certain coherence threshold.
Performance of sequential swapping improves with increased memory coherence time, approaching simultaneous swapping rates.
Abstract
Connection-less, packet-switched quantum network architectures distribute entanglement across multi-hop paths through sequential entanglement swapping, in which each node acts on purely local state information. The architectural advantages over the connection-oriented alternative -- simultaneous SWAP-ASAP -- are compelling, but sequential swapping holds partial chains in intermediate buffers between successive swaps, exposing them to memory decoherence in a way simultaneous SWAP-ASAP avoids by design. We present a proof-of-principle study at fixed chain length in which each elementary link is governed by a fixed reinforcement-learning policy optimizing the secret-key rate of the six-state protocol, leaving the network-layer protocol as the sole independent variable. Sweeping the network-layer memory coherence time over four orders of magnitude reveals a…
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