Quantum Walk-Enhanced Hybrid Routing: Integrating Local and Non-Local Best-Effort Strategies for Robust Quantum Networks

Abstract

network nodes. Unlike classical networks, quantum networks require specialized routing strategie due to the no-cloning theorem, entanglement decay, and limited quantum memory. This paper investigates the performance of different distributed routing algorithms for entanglement distribution in a quantum internet. We analyze five routing algorithms, including modified greedy routing, local best effort, and non-local best effort approaches. Additionally, we propose a hybrid algorithm that combines local best effort and non-local best effort routing to optimize entanglement distribution. To further improve performance, we introduce an enhanced version of the hybrid algorithm that leverages quantum walks for path discovery and selection. Our study evaluates these algorithms through extensive simulations across multiple network topologies, including grid, ring, and hierarchical structures. We also examine the impact of different virtual graph models—deterministic, power-law, and uniform virtual graphs—on entanglement routing efficiency. Our study evaluates these algorithms through extensive simulations on multiple network topologies—grid, ring, and hierarchical structures—as well as different virtual graph models, including deterministic, power-law, and uniform virtual graphs. The results reveal that the hybrid best effort algorithm (d=2) is the most consistent performer, demonstrating low latency, high fidelity, and stable scaling across all network topologies. The quantum-enhanced hybrid approach achieves the highest fidelity in most cases but exhibits occasional fluctuations and slightly higher latency. Meanwhile, the non-local best effort algorithm (d=2) proves to be the best choice for latency-sensitive applications, maintaining low latency and reliable scaling. Our findings suggest that integrating quantum walks into hybrid routing strategies can significantly enhance fidelity without sacrificing scalability, making it a promising approach for future quantum networks. Furthermore, our analysis provides practical insights into selecting optimal routing algorithms based on specific network requirements—whether prioritizing fidelity, latency, or overall stability. This work contributes to the ongoing development of scalable and efficient quantum routing protocols, paving the way for real-world deployment of quantum internet infrastructures. Future research will explore adaptive learning-based routing strategies to further improve the robustness and adaptability of quantum network routing