SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks
In this article, a space–air–ground quantum (SPARQ) network is developed as a means for providing a seamless on-demand entanglement distribution. The node mobility in SPARQ poses significant challenges to entanglement routing. Existing quantum routing algorithms focus on statio...
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IEEE
2024-01-01
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| Series: | IEEE Transactions on Quantum Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10684482/ |
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| author | Mohamed Shaban Muhammad Ismail Walid Saad |
| author_facet | Mohamed Shaban Muhammad Ismail Walid Saad |
| author_sort | Mohamed Shaban |
| collection | DOAJ |
| description | In this article, a space–air–ground quantum (SPARQ) network is developed as a means for providing a seamless on-demand entanglement distribution. The node mobility in SPARQ poses significant challenges to entanglement routing. Existing quantum routing algorithms focus on stationary ground nodes and utilize link distance as an optimality metric, which is unrealistic for dynamic systems, like SPARQ. Moreover, in contrast to the prior art that assumes homogeneous nodes, SPARQ encompasses heterogeneous nodes with different functionalities further complicates the entanglement distribution. To solve the entanglement routing problem, a deep reinforcement learning (RL) framework is proposed and trained using deep Q-network (DQN) on multiple graphs of SPARQ to account for the network dynamics. Subsequently, an entanglement distribution policy, third-party entanglement distribution (TPED), is proposed to establish entanglement between communication parties. A realistic quantum network simulator is designed for performance evaluation. Simulation results show that the TPED policy improves entanglement fidelity by 3% and reduces memory consumption by 50% compared with benchmark. The results also show that the proposed DQN algorithm improves the number of resolved teleportation requests by 39% compared with shortest path baseline and the entanglement fidelity by 2% compared with an RL algorithm that is based on long short-term memory. It also improved entanglement fidelity by 6% and 9% compared with state-of-the-art benchmarks. Moreover, the entanglement fidelity is improved by 15% compared with DQN trained on a snapshot of SPARQ. Additionally, SPARQ enhances the average entanglement fidelity by 23.5% compared with existing networks spanning only space and ground layers. |
| format | Article |
| id | doaj-art-9fc2ae0990e94537ae3326ea5754b2f5 |
| institution | Kabale University |
| issn | 2689-1808 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Transactions on Quantum Engineering |
| spelling | doaj-art-9fc2ae0990e94537ae3326ea5754b2f52025-01-28T00:02:30ZengIEEEIEEE Transactions on Quantum Engineering2689-18082024-01-01512010.1109/TQE.2024.346457210684482SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum NetworksMohamed Shaban0https://orcid.org/0000-0002-7924-5953Muhammad Ismail1https://orcid.org/0000-0002-8051-9747Walid Saad2https://orcid.org/0000-0003-2247-2458Cybersecurity Education, Research, and Outreach Center and the Department of Computer Science, Tennessee Tech University, Cookeville, TN, USACybersecurity Education, Research, and Outreach Center and the Department of Computer Science, Tennessee Tech University, Cookeville, TN, USABradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USAIn this article, a space–air–ground quantum (SPARQ) network is developed as a means for providing a seamless on-demand entanglement distribution. The node mobility in SPARQ poses significant challenges to entanglement routing. Existing quantum routing algorithms focus on stationary ground nodes and utilize link distance as an optimality metric, which is unrealistic for dynamic systems, like SPARQ. Moreover, in contrast to the prior art that assumes homogeneous nodes, SPARQ encompasses heterogeneous nodes with different functionalities further complicates the entanglement distribution. To solve the entanglement routing problem, a deep reinforcement learning (RL) framework is proposed and trained using deep Q-network (DQN) on multiple graphs of SPARQ to account for the network dynamics. Subsequently, an entanglement distribution policy, third-party entanglement distribution (TPED), is proposed to establish entanglement between communication parties. A realistic quantum network simulator is designed for performance evaluation. Simulation results show that the TPED policy improves entanglement fidelity by 3% and reduces memory consumption by 50% compared with benchmark. The results also show that the proposed DQN algorithm improves the number of resolved teleportation requests by 39% compared with shortest path baseline and the entanglement fidelity by 2% compared with an RL algorithm that is based on long short-term memory. It also improved entanglement fidelity by 6% and 9% compared with state-of-the-art benchmarks. Moreover, the entanglement fidelity is improved by 15% compared with DQN trained on a snapshot of SPARQ. Additionally, SPARQ enhances the average entanglement fidelity by 23.5% compared with existing networks spanning only space and ground layers.https://ieeexplore.ieee.org/document/10684482/Entanglement distributionentanglement fidelityentanglement swappingquantum routingspace–air–ground quantum (SPARQ) |
| spellingShingle | Mohamed Shaban Muhammad Ismail Walid Saad SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks IEEE Transactions on Quantum Engineering Entanglement distribution entanglement fidelity entanglement swapping quantum routing space–air–ground quantum (SPARQ) |
| title | SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks |
| title_full | SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks |
| title_fullStr | SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks |
| title_full_unstemmed | SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks |
| title_short | SPARQ: Efficient Entanglement Distribution and Routing in Space–Air–Ground Quantum Networks |
| title_sort | sparq efficient entanglement distribution and routing in space x2013 air x2013 ground quantum networks |
| topic | Entanglement distribution entanglement fidelity entanglement swapping quantum routing space–air–ground quantum (SPARQ) |
| url | https://ieeexplore.ieee.org/document/10684482/ |
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