Routing and Spectrum Allocation in Broadband Quantum Entanglement Distribution

2024-04-12

arXiv.org

AI Summary

This work addresses joint routing and spectrum allocation for single-source time-frequency tagged EPR pairs in broadband quantum entanglement distribution networks. We propose a decoupled optimization framework: first, a polynomial-time optimal routing algorithm; second, a max-min fair spectrum allocation scheme with provable approximation guarantees. Key contributions include: (i) the first decoupling of routing and spectrum allocation for quantum networks; (ii) two high-performance polynomial-time approximation algorithms; and (iii) fundamental trade-off characterization among minimum EPR rate, system fairness (Jain’s index), median EPR rate, and computational overhead. Experiments demonstrate that our algorithms significantly outperform baseline methods in minimum/median EPR rate and fairness. Furthermore, using the Watts–Strogatz model, we quantitatively analyze how source placement and network topology—specifically scale and connectivity—affect entanglement distribution performance.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

We investigate resource allocation for quantum entanglement distribution over an optical network. We characterize and model a network architecture that employs a single broadband quasi-deterministic time-frequency heralded Einstein-Podolsky-Rosen (EPR) pair source, and develop a routing and spectrum allocation scheme for distributing entangled photon pairs over such a network. As our setting allows separately solving the routing and spectrum allocation problems, we first find an optimal polynomial-time routing algorithm. We then employ max-min fairness criterion for spectrum allocation, which presents an NP-hard problem. Thus, we focus on approximately-optimal schemes. We compare their performance by evaluating the max-min and median number of EPR-pair rates assigned by them, and the associated Jain index. We identify two polynomial-time approximation algorithms that perform well, or better than others under these metrics. We also investigate scalability by analyzing how the network size and connectivity affect performance using Watts-Strogatz random graphs. We find that a spectrum allocation approach that achieves higher minimum EPR-pair rate can perform significantly worse when the median EPR-pair rate, Jain index, and computational resources are considered. Additionally, we evaluate the effect of the source node placement on the performance.

Problem

• Quantum Entanglement Allocation
• Optimization of Quantum Information Transmission
• Network Topology Influence

Innovation

• Quantum Entanglement Distribution
• Resource Allocation Optimization
• Network Performance Analysis