Entanglement From Sky: Optimizing Satellite-Based Entanglement Distribution for Quantum Networks
The advancement of satellite-based quantum networks shows promise in transforming global communication infrastructure by establishing a secure and reliable quantum Internet. These networks use optical signals from satellites to ground stations to distribute high-fidelity quantum entanglements over long distances, overcoming the limitations of traditional terrestrial systems. However, the complexity of satellite-based entanglement distribution and terrestrial quantum swapping in the integrated network requires joint optimization with satellite assignment, resource allocation, and path selection. To address this challenge, we introduce a hybrid quantum-classical algorithm to solve the optimization problem by leveraging the strengths of both quantum and classical computing. The original problem is decomposed into a master problem and several subproblems using Dantzig-Wolfe decomposition and linearization techniques. Through experiments, this study demonstrates the effectiveness and reliability of the proposed methods in optimizing large-scale networks and managing qubit usage compared to the classical optimization techniques. The findings provide valuable insights for designing and implementing satellite-based entanglement distribution in quantum networks, paving the way for a secure global quantum communication infrastructure.
Authors
- Xinliang Wei (ORCID: https://orcid.org/0000-0001-9136-2178)
- Zhu Han
- Yuanxiong Guo (ORCID: https://orcid.org/0000-0003-2241-125X)
- Yu Wang (ORCID: https://orcid.org/0000-0003-3511-0288)
- Lei Fan (ORCID: https://orcid.org/0000-0001-9426-7029)
Institutions
- University of Houston (US)
- The University of Texas at San Antonio (US)
- Temple University (US)
Publication Details
- Journal
- IEEE/ACM Transactions on Networking
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1109/tnet.2024.3456789
- Citations
- 10
- Primary Topic
- Quantum Information and Cryptography
- Type
- article
- Field-Weighted Citation Impact
- 3.47