Quantum networks promise unconditionally secure communication and distributed quantum computing. Realizing these capabilities requires the reliable creation and maintenance of multipartite entanglement across large-scale networks. However, distributing complex entangled states among many nodes becomes increasingly challenging due to physical imperfections, architectural constraints, and the growing demands on network resources. This thesis presents practical methods that address two key facets of this broader problem. First, we introduce graph-theoretic protocols that generate GHZ states in Bell-pair networks using only local operations and classical communication, bypassing NP-hard subroutines while minimizing gate counts and Bell-pair consumption. Benchmarked on random network topologies and validated on IBM quantum hardware, these methods provide a scalable path to distributed quantum computing and multiparty communication. Second, we improve the performance of second-generation quantum repeater networks by incorporating bosonic quantum error correction. We show that memories with shorter coherence times, when protected by error correction, can outperform unencoded memories with significantly longer coherence times. We further address the problem of optimal memory-buffer allocation across repeater networks, introducing policies that reduce waiting times, thereby improving entanglement distribution efficiency. Overall, these results demonstrate practical and effective methods for improving performance and advancing the realization of near-term quantum networks.
Quantum networks promise unconditionally secure communication and distributed quantum computing. Realizing these capabilities requires the reliable creation and maintenance of multipartite entanglement across large-scale networks. However, distributing complex entangled states among many nodes becomes increasingly challenging due to physical imperfections, architectural constraints, and the growing demands on network resources. This thesis presents practical methods that address two key facets of this broader problem. First, we introduce graph-theoretic protocols that generate GHZ states in Bell-pair networks using only local operations and classical communication, bypassing NP-hard subroutines while minimizing gate counts and Bell-pair consumption. Benchmarked on random network topologies and validated on IBM quantum hardware, these methods provide a scalable path to distributed quantum computing and multiparty communication. Second, we improve the performance of second-generation quantum repeater networks by incorporating bosonic quantum error correction. We show that memories with shorter coherence times, when protected by error correction, can outperform unencoded memories with significantly longer coherence times. We further address the problem of optimal memory-buffer allocation across repeater networks, introducing policies that reduce waiting times, thereby improving entanglement distribution efficiency. Overall, these results demonstrate practical and effective methods for improving performance and advancing the realization of near-term quantum 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.
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.
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.
Quantum communication between quantum processors offers new capabilities and applications in quantum computing. However, Noisy Intermediate-Scale Quantum (NISQ) devices face challenges such as decoherence, entanglement distillation latency, high communication-to-data qubit ratio, quantum error correction, and scalability. Inspired by distributed systems concepts, this paper presents two solutions for optimizing quantum communication: advanced quantum repeaters and machine learning for quantum network optimization. Advanced quantum repeaters will leverage topological quantum states to improve entanglement generation, swapping, and distillation efficiency. Concurrently, machine learning techniques using multi-armed bandit algorithms will dynamically allocate quantum processing resources across distributed quantum networks. This optimization enhances the efficiency of quantum teleportation protocols and reduces computational costs. By integrating advanced quantum repeaters with machine learning optimization, the proposed solutions aim to address the challenges in quantum communication.
A quantum network is expected to enhance distributed quantum computing and quantum communication over a long distance while providing unconditional security. As quantum entanglement is essential for a quantum network, major issues from various types of noise and decoherence prevent it from being realized, and research has been intensively active to obtain optimal configurations for a quantum network. In this work, we address the performance of a quantum network capable of quantum error correction and entanglement purification. Our results show that one should distribute Bell pairs as fast as possible while balancing the deployment of fidelity enhancement. We also show suitable hybrid strategies in quantum cryptography tasks under some noise regimes that need to use purification and quantum error correction together. Our results suggest that using purification to distribute high fidelity Bell pairs and preserving them for application using quantum error correction is a promising way to achieve a near-term quantum network for secure communication.
Quantum communications enable secure key transmission and entanglement distribution, but their rates and maximum transmission distances are limited due to the losses and noise introduced by quantum channels. Various techniques have been developed to address these limitations, tailored to the platform and the nature of the decoherence. In this thesis, we explore ways to enhance the performance of quantum communications, with a particular focus on increasing the key rates and transmission distances in quantum key distribution (QKD), a method that leverages quantum mechanics to securely share keys between trusted parties. Additionally, we aim to improve the purity of entangled states shared between two parties, contributing to broader advancements in quantum communications. We begin by introducing a software-enhanced continuous-variable QKD (CV-QKD) protocol, where keys are encoded onto the phase and amplitude degrees of the optical field. This protocol enhances both transmission distance and key rates through a post-selection method employing arbitrary filters, experimentally demonstrated on two different platforms. Its adaptability makes it highly promising, as it can be implemented on existing CV-QKD platforms and dynamically optimises key rates for rapidly changing channels. We then present a protocol for the pure-loss channel leveraging quantum repeaters to mitigate the channel losses by segmenting the total communication distance into smaller, more manageable intervals. This repeater-like protocol introduces a more efficient entanglement-swapping measurement at the repeater station than the state-of-the-art twin-field protocols. Instead of polarisation encoding, our protocol relies on encoding keys in the photon-number basis, optimising the states to achieve the highest key rates for each distance. Notably, this protocol shows strong potential for improving long-distance quantum communication by surpassing the capacity of the direct communication channel at a shorter distance than the existing repeater protocols such as twin-field QKD while achieving an overall higher transmission distance. Finally, in this thesis, we demonstrate that for the Pauli-dephasing channel, placing a node in the middle of the quantum channel to perform a Bell-state measurement as an entanglement-swapping operation does not result in improved key rates, even with reduced decoherence. As a result, we propose an entanglement purification protocol that refines a larger set of noisy entangled states into a smaller set of high-fidelity ones using local operations and classical communication. This purification protocol builds upon earlier purification methods, extending their application from two Bell pairs to any number of Bell pairs and thereby achieving the capacity of the dephasing channel. Through numerous recursive iterations, it produces near-perfect Bell pairs, making it well-suited for quantum repeaters and correcting dephasing errors in quantum computers.