Quantum networks (QNs) are a promising platform for secure communications, enhanced sensing, and efficient distributed quantum computing. However, due to the fragile nature of quantum states, these networks face significant challenges in terms of scalability. In this paper, the scaling limits of quantum repeater networks (QRNs) are analyzed. The goal of this work is to maximize the overall length, or scalability of QRNs such that long-distance quantum communications is achieved while application-specific quality-of-service ($Q$oS) requirements are satisfied. In particular, a novel joint optimization framework that aims at maximizing QRN scalability, while satisfying$Q$oS constraints on the end-to-end fidelity and rate is proposed. The proposed approach optimizes the number of QRN repeater nodes, their separation distance, and the number of distillation rounds to be performed at both link and end-to-end levels. Extensive simulations are conducted to analyze the tradeoffs between QRN scalability, rate, and fidelity under gate and measurement errors. The obtained results characterize the QRN scaling limits for a given QoS requirement. The proposed approach offers a promising solution and design guidelines for future QRN deployments.
Quantum networks (QNs) are a promising platform for secure communications, enhanced sensing, and efficient distributed quantum computing. However, due to the fragile nature of quantum states, these networks face significant challenges in terms of scalability. In this paper, the scaling limits of quantum repeater networks (QRNs) are analyzed. The goal of this work is to maximize the overall length, or scalability of QRNs such that long-distance quantum communications is achieved while application-specific quality-of-service (QoS) requirements are satisfied. In particular, a novel joint optimization framework that aims at maximizing QRN scalability, while satisfyingQoS constraints on the end-to-end fidelity and rate is proposed. The proposed approach optimizes the number of QRN repeater nodes, their separation distance, and the number of distillation rounds to be performed at both link and end-to-end levels. Extensive simulations are conducted to analyze the tradeoffs between QRN scalability, rate, and fidelity under gate and measurement errors. The obtained results characterize the QRN scaling limits for a given QoS requirement. The proposed approach offers a promising solution and design guidelines for future QRN deployments.
The scalability of quantum communication networks is crucial for enabling secure information exchange and distributed quantum computing across global infrastructures. However, achieving scalability remains a significant challenge due to the effects of decoherence, photon loss, and fidelity degradation over extended distances. This paper performs a critical investigation into the scalability limits of quantum communication networks, focusing on the interplay between entanglement generation rates, end-to-end fidelity, and network parameters such as node separation, noise levels, and total distance. Leveraging the SeQUeNCe simulation framework, we model adaptable trapped-ion repeater networks to uncover fundamental insights into both homogeneous and heterogeneous configurations. Our findings reveal transformative insights that help reshape system designs for near term quantum networks. We identify maximum node separation thresholds critical for practical implementations, illuminate the non-linear degradation of fidelity with increasing distance, and expose how routing and swapping protocols influence entanglement success rates at scale. Most notably, we demonstrate that while additional repeaters can mitigate distance-induced failures, excessive node counts introduce compounding fidelity losses that threaten network viability under certain architectures. These results provide a roadmap for revolutionizing quantum networks, with actionable design strategies such as optimized node placement, advanced routing algorithms, and the adoption of cutting-edge qubit technologies like topological qubits. By addressing key bottlenecks in quantum communication scalability, our work lays the foundation for the next generation of global quantum networks.
This paper presents a comprehensive study on the scalability challenges and opportunities in quantum communication networks, with the goal of determining parameters that impact networks most as well as the trends that appear when scaling networks. We design simulations of quantum networks comprised of router nodes made up of trapped-ion qubits, separated by quantum repeaters in the form of Bell State Measurement (BSM) nodes. Such networks hold the promise of securely sharing quantum information and enabling high-power distributed quantum computing. Despite the promises, quantum networks encounter scalability issues due to noise and operational errors. Through a modular approach, our research aims to surmount these challenges, focusing on effects from scaling node counts and separation distances while monitoring low-quality communication arising from decoherence effects. We aim to pinpoint the critical features within networks essential for advancing scalable, large-scale quantum computing systems. Our findings underscore the impact of several network parameters on scalability, highlighting a critical insight into the trade-offs between the number of repeaters and the quality of entanglement generated. This paper lays the groundwork for future explorations into optimized quantum network designs and protocols.
Long-distance quantum communication presents a significant challenge as maintaining the fidelity of qubits can be difficult. This issue can be addressed through the use of quantum repeaters to transmit entanglement information through Bell measurements. However, despite its necessity to enable wide-area quantum internet, the deployment cost of quantum repeaters can be prohibitively expensive, thus it is important to develop a quantum repeater deployment model that can strike a balance between cost and effectiveness. In this work, we present novel heuristic models to quickly determine a minimum number of quantum repeaters to deploy in large-scale networks to provide end-to-end connectivity between all end hosts. The results show that, compared to the linear programming approach, the heuristic methods can find near-optimal solutions while reducing the execution time from days to seconds when evaluated against several synthetic and real-world networks such as SURFnet and ESnet. As reliability is key for any network, we also demonstrate that the heuristic method can determine deployment models that can endure up to two link/node failures.
Long-distance quantum communication presents a significant challenge due to the degrading fidelity of transmitted qubits. Quantum repeaters are proposed to overcome this issue through Bell measurements on entangled qubit pairs. However, despite its necessity to enable wide-area quantum internet, the deployment cost of quantum repeaters can be prohibitively expensive; thus, developing a quantum repeater deployment model that can strike a balance between cost and effectiveness is essential. In this work, we present novel heuristic models to quickly determine a minimum number of quantum repeaters to deploy in large-scale networks to provide end-to-end connectivity between all end hosts. The results show that, compared to the integer linear programming approach, the heuristic methods can find near-optimal solutions while reducing the execution time from days to seconds when evaluated against several synthetic and real-world networks such as SURFnet and ESnet. As reliability is critical for any network, we demonstrate that the heuristic method can estimate deployment models to endure up to two link/node failures.
Future quantum networks will enable the interconnection of multiple users distributed across vast geographic distances. Due to these large separations and limited physical resources, communication will often rely on multi-path routing strategies, where physical resources are distributed across channels of varying lengths and delivered to end users. Efficient long-distance quantum communication therefore requires optimizing the allocation of these resources across available paths. In this work, we introduce a performance-oriented approach to quantum network routing by extending the classical concept of Quality of Service (QoS) to the context of multi-path quantum resources distribution. Unlike prior models that consider entanglement generation or quantum memory coherence in isolation, we investigate the interplay between path assignment strategies, coherence time constraints, and quantum error correction (QEC), and how they jointly impact end-to-end communication fidelity. We analyze both unencoded and encoded transmissions over aggregated network paths, quantifying the effects of resource allocation on transmission success. Our findings show that fidelity cannot be optimized independently of memory lifetimes, and that while QEC can enhance performance under specific conditions, it also imposes additional constraints depending on network topology and path-length asymmetries. This work provides a foundation for developing QoS-aware quantum routing protocols that balance fidelity, throughput, and memory utilization -- key considerations for near-term quantum repeater networks.
The quantum internet enables distribution of quantum states across distant nodes, supporting secure communication, distributed computing, and quantum sensing. Unlike classical networks, it is constrained by the no cloning theorem, probabilistic entanglement generation, decoherence, and hardware drift, making classical abstractions inadequate. Scalable quantum networking therefore requires new architectures, protocols, and optimisation methods that explicitly account for these limitations.
This thesis studies the architecture, routing, and operation of quantum networks under realistic constraints, focusing on bipartite entanglement distribution over quantum repeater networks. Key metrics include end to end fidelity, throughput, scalability, and fairness. At the network layer, routing strategies are developed beyond assumptions of homogeneous nodes and full network knowledge. Routing under heterogeneous repeater efficiencies shows how partial knowledge of node quality improves fidelity and reduces path blocking. A grey box routing approach is then introduced, where path selection relies only on topology and end to end estimates, achieving robustness and fairness without detailed link information.
At the link layer, calibration and hardware drift are addressed through a calibration aware model separating activation and calibration phases. For linear repeater chains, an optimal calibration schedule is derived to balance operation time and calibration overhead. This is extended to general topologies with shared links, where a greedy orchestration heuristic is proposed.
Finally, the thesis connects network protocols with hardware via an instruction set architecture for programmable quantum repeater nodes based on NV centers, enabling coherent programmability and linking physical operations to higher layer protocols.