Optimal entanglement distribution policies in homogeneous repeater chains with cutoffs

Journal Article (2023)
Author(s)

Álvaro G. Iñesta (Kavli institute of nanoscience Delft)

Gayane Vardoyan (TU Delft - Quantum Computer Science)

Lara Scavuzzo

S. Wehner (TU Delft - Quantum Computer Science, TU Delft - QID/Wehner Group, Kavli institute of nanoscience Delft)

Research Group
Quantum Computer Science
Copyright
© 2023 Álvaro G. Iñesta, G.S. Vardoyan, Lara Scavuzzo, S.D.C. Wehner
DOI related publication
https://doi.org/10.1038/s41534-023-00713-9
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Álvaro G. Iñesta, G.S. Vardoyan, Lara Scavuzzo, S.D.C. Wehner
Research Group
Quantum Computer Science
Issue number
1
Volume number
9
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Abstract

We study the limits of bipartite entanglement distribution using a chain of quantum repeaters that have quantum memories. To generate end-to-end entanglement, each node can attempt the generation of an entangled link with a neighbor, or perform an entanglement swapping measurement. A maximum storage time, known as cutoff, is enforced on the memories to ensure high-quality entanglement. Nodes follow a policy that determines when to perform each operation. Global-knowledge policies take into account all the information about the entanglement already produced. Here, we find global-knowledge policies that minimize the expected time to produce end-to-end entanglement. Our methods are based on Markov decision processes and value and policy iteration. We compare optimal policies to a policy in which nodes only use local information. We find that the advantage in expected delivery time provided by an optimal global-knowledge policy increases with increasing number of nodes and decreasing probability of successful swapping.