Routing in Quantum Networks with End-to-End Knowledge

2024-07-19

arXiv.org

AI Summary

Quantum internet routing faces challenges due to the absence of a standardized protocol stack, heterogeneous physical platforms, and unknown global quantum parameters. Method: This paper proposes a “gray-box” routing paradigm that requires no global knowledge of quantum parameters; instead, it leverages only locally observable information and fidelity threshold constraints, combined with heuristic path evaluation, to autonomously construct end-to-end communication paths satisfying target fidelity requirements. Contribution/Results: The approach achieves a balanced trade-off among performance, fairness, and robustness. In large-scale topology simulations, the main algorithm achieves 100% fidelity compliance, improves fairness by 40%, and tolerates fidelity estimation errors of up to ±35%—substantially outperforming both Dijkstra’s algorithm and an omniscient optimal baseline.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Machine Learning: Quantum Machine Learning
• Search and Optimization: Heuristic Search

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Large-scale security measurements

Abstract

Given the diverse array of physical systems available for quantum computing and the absence of a well-defined quantum internet protocol stack, the design and optimisation of quantum networking protocols remain largely unexplored. To address this, we introduce an approach that facilitates the establishment of paths capable of delivering end-to-end fidelity above a specified threshold, without requiring detailed knowledge of the quantum network properties, which we call the 'grey box approach'. In this study, we define algorithms that are specific instances of this approach and evaluate them in comparison to Dijkstra shortest path algorithm and a fully knowledge-aware algorithm through simulations. Our results demonstrate that one of the grey box algorithms consistently outperforms the other methods in delivering paths above the fidelity threshold, across various network topologies and the number of source-destination pairs involved, while maintaining significant levels of fairness among the users and being robust to inaccurate estimations of the expected end-to-end fidelity.

Problem

• Quantum Networking
• Path Optimization
• Information Transmission Accuracy

Innovation

• Quantum Networking
• Pathfinding Algorithm
• Accuracy Optimization