Entanglement Distribution in Satellite-based Dynamic Quantum Networks

Low Earth Orbit (LEO) satellites present a compelling opportunity for the establishment of a global quantum information network. However, satellite-based entanglement distribution from a networking perspective has not been fully investigated. Existing works often do not account for satellite movemen...

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Bibliographic Details
Published in:IEEE network 2024-01, Vol.38 (1), p.1-1
Main Authors: Chang, Alena, Wan, Yinxin, Xue, Guoliang, Sen, Arunabha
Format: Article
Language:English
Subjects:
Algorithms
Downlink
Greedy algorithms
Integer programming
Intersatellite communications
Linear programming
Low earth orbit satellites
Low earth orbits
Optimized production technology
Photonics
Polynomials
Quantum computing
Quantum entanglement
Quantum networks
Quantum phenomena
Repeaters
Satellite communications
Satellites
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Summary:Low Earth Orbit (LEO) satellites present a compelling opportunity for the establishment of a global quantum information network. However, satellite-based entanglement distribution from a networking perspective has not been fully investigated. Existing works often do not account for satellite movement over time when distributing entanglement and/or often do not permit entanglement distribution along inter-satellite links, which are two shortcomings we address in this paper. We first define a system model which considers both satellite movement over time and inter-satellite links. We next formulate the optimal entanglement distribution (OED) problem under this system model and show how to convert the OED problem in a dynamic physical network to one in a static logical graph which can be used to solve the OED problem in the dynamic physical network. We then propose a polynomial time greedy algorithm for computing satellite-assisted multi-hop entanglement paths. We also design an integer linear programming (ILP)-based algorithm to compute optimal solutions as a baseline to study the performance of our greedy algorithm. We present evaluation results to demonstrate the advantage of our model and algorithms.
ISSN:0890-8044
1558-156X
DOI:10.1109/MNET.2023.3321706