Quantum networks are essential for secure quantum communication and distributed quantum computing. However, their performance is highly vulnerable to targeted attacks that disrupt entanglement distribution, leading to significant network degradation. To address this challenge, we propose two heuristic routing algorithms Quantum Entanglement Distribution Algorithm 1 (QEDA1) and Quantm Entanglement Distribtion Algorithm 2 (QEDA2) that minimize loss of fidelity by reducing the number of intermediate nodes while optimizing entanglement swapping and purification strategies. In QEDA1 we only applied purification as a recovery mechanism, while in QEDA2 we utilized a purificationrerouting approach. Furthermore, unlike previous studies, which relied primarily on idealized or small-scale topologies, we evaluated our approach on a real-world network topology (Surfnet), analyzing throughput variations under both normal conditions and targeted attacks. Furthermore, we compare the performance of the algorithm in memory-assisted and memoryless quantum networks, demonstrating the impact of quantum memory on network resilience. In addition, we introduce an attack model based on centrality-driven node failures and propose a recovery mechanism that integrates rerouting and entanglement purification to mitigate the effects of targeted attacks. Our results indicate that QEDA2 is more effective in mitigating the effect of attacks on throughput. Moreover, our findings highlight the trade-offs between network robustness, resource allocation, and fidelity constraints, providing valuable insights for the design of resilient large-scale quantum networks.
Quantum networks are essential for secure quantum communication and distributed quantum computing. However, their performance is highly vulnerable to targeted attacks that disrupt entanglement distribution, leading to significant network degradation. To address this challenge, we propose two heuristic routing algorithms Quantum Entanglement Distribution Algorithm 1 (QEDA1) and Quantm Entanglement Distribtion Algorithm 2 (QEDA2) that minimize loss of fidelity by reducing the number of intermediate nodes while optimizing entanglement swapping and purification strategies. In QEDA1 we only applied purification as a recovery mechanism, while in QEDA2 we utilized a purificationrerouting approach. Furthermore, unlike previous studies, which relied primarily on idealized or small-scale topologies, we evaluated our approach on a real-world network topology (Surfnet), analyzing throughput variations under both normal conditions and targeted attacks. Furthermore, we compare the performance of the algorithm in memory-assisted and memoryless quantum networks, demonstrating the impact of quantum memory on network resilience. In addition, we introduce an attack model based on centrality-driven node failures and propose a recovery mechanism that integrates rerouting and entanglement purification to mitigate the effects of targeted attacks. Our results indicate that QEDA2 is more effective in mitigating the effect of attacks on throughput. Moreover, our findings highlight the trade-offs between network robustness, resource allocation, and fidelity constraints, providing valuable insights for the design of resilient large-scale quantum networks.
Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the failure of entanglement generations, which, however, rarely include the considerations on the most important metric to evaluate the quality of connection, entanglement fidelity. To solve this problem, we propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (SD) pairs in quantum networks. In our proposal, we first consider the single S-D pair scenario and design an iterative routing algorithm, Q-PATH, to find the optimal purification decisions along the routing path with minimum entangled pair cost. Further, a low-complexity routing algorithm using an extended Dijkstra algorithm, Q-LEAP, is designed to reduce the computational complexity by using a simple but effective purification decision method. Then we consider the common scenario with multiple S-D pairs and design a greedy-based algorithm considering resource allocation and rerouting process for multiple routing requests. To verify the effectiveness and superiority of the proposed algorithms, extensive simulations are conducted, and the simulation results show that the proposed algorithms not only can provide fidelity-guarantee routing solutions, but also has superior performance in terms of throughput, fidelity of end-to-end entanglement connection, and resource utilization ratio, compared with the existing routing scheme.
Quantum networks rely on the efficient distribution of entanglement to enable long-distance quantum communication and information processing. A key challenge in these networks is the design of routing protocols capable of maintaining high quality entanglement in the presence of noise, decoherence, and imperfect operations, which progressively degrade the fidelity of entangled states through entanglement swapping. Entanglement purification provides an effective mechanism to mitigate this degradation at the cost of additional resources. In this work, we study purification-aware quantum routing and formulate the problem of selecting optimal purification strategies as an optimization task. By employing dynamic programming techniques, we identify strategies that optimally balance resource consumption and end-to-end fidelity, demonstrating the effectiveness of our approach across different scenarios.
Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the failure of entanglement generations, which, however, rarely include the considerations on the most important metric to evaluate the quality of connection, entanglement fidelity. To solve this problem, we propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (S-D) pairs in quantum networks. In our proposal, we first consider the single S-D pair scenario and design an iterative routing algorithm, Q-PATH, to find the optimal purification decisions along the routing path with minimum entangled pair cost. Further, a low-complexity routing algorithm using an extended Dijkstra algorithm, Q-LEAP, is designed to reduce the computational complexity by using a simple but effective purification decision method. Finally, we consider the common scenario with multiple S-D pairs and design a greedy-based algorithm considering resource allocation and re-routing process for multiple routing requests. Simulation results show that the proposed algorithms not only can provide fidelity-guaranteed routing solutions, but also has superior performance in terms of throughput, fidelity of end-to-end entanglement connection, and resource utilization ratio, compared with the existing routing scheme.
Complex quantum networks can support a diverse set of long-range entanglement distribution schemes ranging from linear repeater protocols to multipath entanglement purification strategies. As a result, a network's resourcefulness, that is its ability to facilitate quantum communication, depends on the deployed distribution scheme. In this work, we analyse and compare the resourcefulness of quantum networks across a broad range of network topologies, including both regular and random networks, under two distinct entanglement distribution schemes. The first relies on entanglement swapping along a single path connecting a source-target pair, while the second exploits entanglement purification using multiple paths between the same source and target nodes. The resourcefulness of the network is quantified using a recently described metric [1] that averages over the maximum teleportation fidelity between arbitrary source-target pairs in the network. We present algorithms for estimating this metric under constraints of edge-usage and ordering of paths. Our results not only demonstrate the sensitivity of the average maximum teleportation fidelity metric to the choice of entanglement distribution protocol, but also highlight the significant improvements enabled by network purification schemes. In particular, purification-based approaches can substantially enhance average teleportation fidelity, thereby improving the overall teleportation capability of quantum networks.
We present an approach to purification and entanglement routing on complex quantum network architectures, that is, how a quantum network equipped with imperfect channel fidelities and limited memory storage time can distribute entanglement between users. We explore how network parameters influence the performance of path-finding algorithms necessary for optimizing routing and, in particular, we explore the interplay between the bandwidth of a quantum channels and the choice of purification protocol. Finally, we demonstrate multi-path routing on various network topologies with resource constraints, in an effort to inform future design choices for quantum network configurations. Our work optimizes both the choice of path over the quantum network and the choice of purification schemes used between nodes. We consider not only pair-production rate, but optimize over the fidelity of the delivered entangled state. We introduce effective heuristics enabling fast path-finding algorithms for maximizing entanglement shared between two nodes on a quantum network, with performance comparable to that of a computationally-expensive brute-force path search.
Routing plays a pivotal role in quantum communication as it directly impacts the efficiency, reliability, and scalability of quantum networks. While several studies in the literature have explored routing algorithms leveraging quantum memories, current quantum memory technologies are unable to simultaneously achieve high fidelity, extended storage durations, wide bandwidths, multimode capacity, and high efficiency. To address this limitation, our study focuses on fidelity-guaranteed entanglement routing within a memoryless network architecture, employing both distributed and centralized routing approaches. Utilizing our proposed routing algorithm, MEFID, we achieved a throughput of 72 qubits per second under a fidelity threshold of 0.8 and within three iterative rounds. By integrating a purification process to ensure that the final fidelity consistently exceeds the specified threshold, our algorithm facilitates the development of robust and high-performance quantum networks.