The realization of a global quantum network capable of supporting secure communication and other quantum information processing (QIP) tasks hinges on the ability to distribute high-fidelity entanglement across long distances while optimizing resource usage. This work describes a scalable approach for building large quantum networks by connecting quantum sub-networks using entanglement backbones as interconnections and a swapping based entanglement distribution protocol. Using a statistical model for parametrized quantum sub-networks we derive a set of equations whose solutions give the optimal values of average network parameters that meet threshold requirements for QIP tasks while minimizing resource cost functions. Our analysis extends to the scenario where multiple sub-networks must be interconnected simultaneously based on the formulation of a global resource cost function. The probability of successfully satisfying the parameter thresholds of a QIP task as a function of average parameters of the sub-networks for random network demands reveals a transition from zero to full satisfiability above critical network parameter values. Moreover, we find that the satisfiability transition can be smooth or discontinuous depending on the topology of the sub-networks. Our results present a pathway for calculating optimal resource requirements in quantum sub-networks interconnected to form the global quantum internet.
The realization of a global quantum network capable of supporting secure communication and other quantum information processing (QIP) tasks hinges on the ability to distribute high-fidelity entanglement across long distances while optimizing resource usage. This work describes a scalable approach for building large quantum networks by connecting quantum sub-networks using entanglement backbones as interconnections and a swapping based entanglement distribution protocol. Using a statistical model for parametrized quantum sub-networks we derive a set of equations whose solutions give the optimal values of average network parameters that meet threshold requirements for QIP tasks while minimizing resource cost functions. Our analysis extends to the scenario where multiple sub-networks must be interconnected simultaneously based on the formulation of a global resource cost function. The probability of successfully satisfying the parameter thresholds of a QIP task as a function of average parameters of the sub-networks for random network demands reveals a transition from zero to full satisfiability above critical network parameter values. Moreover, we find that the satisfiability transition can be smooth or discontinuous depending on the topology of the sub-networks. Our results present a pathway for calculating optimal resource requirements in quantum sub-networks interconnected to form the global quantum internet.
This paper investigates the scalability and transmission efficiency of entanglement swapping protocols within multi-node quantum networks. As the realization of a global quantum internet relies heavily on long-distance entanglement distribution, quantum repeaters utilizing entanglement swapping serve as a critical backbone. However, scalability remains a bottleneck due to photon loss, operational infidelities, and quantum memory coherence times. In this study, we analytically model a multi-node quantum chain and evaluate how the end-to-end entanglement fidelity degrades as the number of intermediate nodes scales up. Our analysis highlights the critical thresholds for Bell state measurement (BSM) success rates required to maintain quantum state integrity across large distances. The findings provide optimization constraints for designing scalable and fault-tolerant routing protocols in future quantum information networks.
Quantum computing promises computational capabilities beyond those of classical systems by exploiting superposition, entanglement, and quantum interference. However, the scalability of current noisy intermediate-scale quantum (NISQ) devices is limited by physical and engineering constraints, restricting the number of available qubits. Distributed quantum computing (DQC) mitigates this limitation by interconnecting multiple quantum processing units (QPUs) via quantum networks capable of distributing high-fidelity entanglement. Realizing such networks requires overcoming probabilistic entanglement generation, finite memory coherence, photon loss, and architectural constraints. This dissertation conducts an in-depth and comprehensive study of resource allocation in quantum networks, aiming to support high-throughput and high-fidelity entanglement distribution over lossy infrastructures. Our work spans the quantum networking stack, from physical-layer entanglement distribution protocols to network planning, quantum storage architectures, and distributed quantum computing. We begin by introducing two asynchronous entanglement distribution protocols-Sequential and Parallel-designed for early-stage quantum networks without global synchronization. Unlike many prior models, our protocols account for classical communication delays and quantum memory decoherence, reflecting practical constraints. Through simulations on real-world topologies such as SURFnet, we show that simple mechanisms such as cutoff-based memory management and sequential asynchronous entanglement distribution protocols can deliver competitive performance while significantly simplifying coordination, narrowing the gap between theoretical proposals and deployable protocols. Next, we formulate quantum network planning as a utility maximization problem that jointly considers entanglement distribution rate and fidelity, treating repeater and memory placement as optimization variables. We propose scalable heuristics and mixed-integer formulations, evaluating them under realistic conditions such as finite coherence time of quantum memories, limited number of memories per repeaters and end nodes, and real network topologies such as ESNet. Our findings offer practical design guidance and highlight how optimal placements depend on underlying physical constraints. To support dynamic workloads and respond to traffic bursts, we propose the Quantum Storage Network (QSN) architecture, where storage nodes buffer EPR pairs in advance of demand as an overlay network. This temporal decoupling improves responsiveness and throughput. Simulations across multiple topologies show that QSNs reduce entanglement distribution service latency by up to 40% and provide improved robustness compared to non-overlay designs, underscoring the value of storage-aware planning in future quantum networks. Finally, we focus on DQC, where large-scale quantum circuits are executed across networked QPUs. We propose a window-based circuit partitioning algorithm that minimizes nonlocal gate execution while balancing load across QPUs. Building on this partitioning, we design an adaptive, dependency-aware entanglement generation scheduler that opportunistically initiates remote entanglement as soon as dependent gates are ready, while accounting for realistic constraints such as coherence limits, probabilistic link generation, and Bell-state measurement (BSM) contention. Applied to benchmark circuits such as QAOA and QFT, this joint approach reduces execution delay by up to 35%. We further perform a two-qubit gate fidelity-sensitivity analysis under to show when the distributed quantum computing can be beneficial. Results show that the number of QPUs significantly impacts sensitivity to non-local gate fidelity: with fewer QPUs, distributed execution can outperform monolithic execution under looser fidelity constraints, whereas with more QPUs, achieving the same advantage requires substantially higher non-local gate fidelities relative to local gate fidelities. These findings identify the parameter regimes in which distributed quantum computing is beneficial, mapping break-even regions (as a function of number of QPUs) and quantifying how much cross-QPU (non-local) gate fidelity must improve—or, equivalently, how much per-QPU local gate fidelity must improve under modularization—for distributed execution to outperform a monolithic baseline. Together, these contributions form a cohesive framework for resource allocation in quantum networks in order to build scalable, delay-tolerant quantum networks and distributed computing systems. By grounding architectural design in realistic physical assumptions, this work advances the state of the art from theoretical modeling to practical, deployable quantum infrastructure.
Quantum information technology has the potential to revolutionize computing, communications, and security. To fully realize its potential, quantum processors with millions of qubits are needed, which are still far from being accomplished. Thus, it is important to establish quantum networks to enable distributed quantum computing to leverage existing and near-term quantum processors into more powerful resources. This paper proposes an efficient entanglement distribution protocol for classical-quantum networks with a limited number of quantum links, enabling quantum teleportation in near-term hybrid networks. The proposed protocol uses entanglement swapping and classical network coding to distribute entanglements efficiently while overcoming bottlenecks and minimizing qubit and link usage. Experimental results show that the proposed protocol requires quantum resources that scale linearly with network size, with individual nodes only requiring a fixed number of qubits. For small network sizes of up to three transceiver pairs, the proposed protocol outperforms the benchmark by using 17% fewer qubit resources, achieving 8.8% higher accuracy, and with a 35% faster simulation time. The percentage improvement increases significantly for large network sizes. We also propose a protocol for securing entanglement distribution against malicious entanglements using quantum state encoding through rotation. Our analysis shows that this method requires no communication overhead and reduces the chance of a malicious node retrieving the teleported state to 7.2%. The achieved results point toward a protocol that enables a highly scalable, efficient, and secure near-term quantum Internet.
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.
The quantum internet is one of the frontiers of quantum information science. It will revolutionize the way we communicate and do other tasks, and it will allow for tasks that are not possible using the current, classical internet. The backbone of a quantum internet is entanglement distributed globally in order to allow for such novel applications to be performed over long distances. Experimental progress is currently being made to realize quantum networks on a small scale, but much theoretical work is still needed in order to understand how best to distribute entanglement and to guide the realization of large-scale quantum networks, and eventually the quantum internet, especially with the limitations of near-term quantum technologies. This work provides an initial step towards this goal. The main contribution of this thesis is a mathematical framework for entanglement distribution protocols in a quantum network, which allows for discovering optimal protocols using reinforcement learning. We start with a general development of quantum decision processes, which is the theoretical backdrop of reinforcement learning. Then, we define the general task of entanglement distribution in a quantum network, and we present ground- and satellite-based quantum network architectures that incorporate practical aspects of entanglement distribution. We combine the theory of decision processes and the practical quantum network architectures into an overall entanglement distribution protocol. We also define practical figures of merit to evaluate entanglement distribution protocols, which help to guide experimental implementations.
Topology is one of the most critical properties of networks. Quantum networks, as a new type of network, have fundamentally different principles for establishing connections compared to classical networks, leading to distinct challenges in topology design. Finding the optimal topology for quantum networks to meet traffic demands is a crucial yet not fully understood problem. In this paper, we explore the topology design problem for quantum networks, considering both resource allocation and entanglement distribution. We propose and investigate both flow-based and path-based formulations, along with their associated solutions, aimed at minimizing the topology cost. For the path-based formulation, we also provide the first theoretical analysis of the cost associated with swapping strategies over a quantum path. Extensive simulations demonstrate that our enhanced path-based formulation is both efficient and effective.