Long-range, genuine multipartite entanglement (GME) between distant parties in a quantum network is a crucial resource for distributed quantum information processing. Through controlled manipulation of short-range GME states in the network via stochastic local operations aided by classical communication (SLOCC), long-range GME can be established between selected target nodes on demand. Optimizing such multipartite entanglement distribution protocols under constraints imposed by the network architecture, target-node set, and available resource budget is a key challenge in resource-efficient manipulation of GME. We present a general operational framework for manipulating GME in quantum networks by classifying the relevant networking operations into three broad primitives-inflation, deflation, and purification-reflecting their effect on the proliferation of GME through general bounds and illustrative examples. We show how these primitives can be combined to construct a broad class of multipartite quantum repeater protocols, enabling their systematic optimization, and demonstrate the framework with a simple example. Applying our approach to networks of Dür-Cirac-Tarrach states reveals a rich landscape of achievable end-to-end GME and accessible entanglement classes. More generally, our framework provides a systematic approach to the construction and optimization of multipartite quantum repeater protocols for scalable and resource-efficient GME distribution in quantum networks.
Long-range, genuine multipartite entanglement (GME) between distant parties in a quantum network is a crucial resource for distributed quantum information processing. Through controlled manipulation of short-range GME states in the network via stochastic local operations aided by classical communication (SLOCC), long-range GME can be established between selected target nodes on demand. Optimizing such multipartite entanglement distribution protocols under constraints imposed by the network architecture, target-node set, and available resource budget is a key challenge in resource-efficient manipulation of GME. We present a general operational framework for manipulating GME in quantum networks by classifying the relevant networking operations into three broad primitives-inflation, deflation, and purification-reflecting their effect on the proliferation of GME through general bounds and illustrative examples. We show how these primitives can be combined to construct a broad class of multipartite quantum repeater protocols, enabling their systematic optimization, and demonstrate the framework with a simple example. Applying our approach to networks of Dür-Cirac-Tarrach states reveals a rich landscape of achievable end-to-end GME and accessible entanglement classes. More generally, our framework provides a systematic approach to the construction and optimization of multipartite quantum repeater protocols for scalable and resource-efficient GME distribution in quantum networks.
We establish operational limits on the broadcasting of genuine multipartite entanglement (GME) in quantum networks. Using a distributed protocol in which each of N parties locally implements optimal 1 → 2 cloning via beam-splitter interactions, we derive exact expressions for the broadcast fidelity of Greenberger-Horne-Zeilinger (GHZ), W states, and Cluster states in a limited setting. We show that the fidelity decays exponentially with system size as [c(R)]N, providing a quantitative expression of multipartite entanglement monogamy in the broadcasting setting, and that both state families share a universal normalisation factor arising from independent post-selection probabilities. Most significantly, we prove a no-go result for simultaneous GME certification: for all reflectivities and all system sizes, the two broadcast copies cannot be simultaneously certified as genuinely multipartite entangled within the standard framework of fidelity-based witnesses. We further check this behaviour for three- and four-party cluster states, finding consistent results that support the generality of the no-go beyond the GHZ and W families. This obstruction arises from the redistribution of multipartite coherence, which both reduces the achievable fidelity and increases the corresponding certification threshold. Our results reveal a fundamental trade-off between the broadcastability of multipartite entanglement and its operational certifiability, and delineate intrinsic limits on entanglement distribution in quantum networks.
Building large-scale quantum computers, essential to demonstrating quantum advantage, is a key challenge. Quantum networks can help address this challenge by enabling the construction of large, robust, and more capable quantum computing platforms by connecting smaller quantum computers. Moreover, unlike classical systems, quantum networks can enable fully secured long-distance communication. Thus, quantum networks lie at the heart of the success of future quantum information technologies. In quantum networks, multipartite entangled states distributed over the network help implement and support many quantum network applications for communications, sensing, and computing. Our work focuses on developing optimal techniques to generate and distribute multipartite entanglement states efficiently. Prior works on generating general multipartite entanglement states have focused on the objective of minimizing the number of maximally entangled pairs while ignoring the heterogeneity of the network nodes and links as well as the stochastic nature of underlying processes. In this work, we develop a hypergraph-based linear programming framework that delivers optimal (under certain assumptions) generation schemes for general multipartite entanglement represented by graph states, under the network resources, decoherence, and fidelity constraints, while considering the stochasticity of the underlying processes. We illustrate our technique by developing generation schemes for the special cases of path and tree graph states and discuss optimized generation schemes for more general classes of graph states. Using extensive simulations over a quantum network simulator, we demonstrate the effectiveness of our developed techniques and show that they outperform prior known schemes by up to orders of magnitude.
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.
Quantum information science is an interdisciplinary field that investigates the principles and applications of quantum mechanics in information processing. Upcoming quantum technologies promise a range of valuable applications, including powerful simulation of complex systems, enhanced computational capabilities, high-precision sensing and metrology, and secure communication via quantum key distribution. A central concept is entanglement, a unique type of correlation between quantum systems that has no classical counterpart. Entanglement plays a pivotal role in many quantum protocols, particularly as a key resource in quantum communication, where protocols such as distributed quantum computation and secret sharing are executed in a distributed setting. Hence, distributing entanglement over long distances and manipulating it locally is essential for enabling quantum communication applications. However, the effectiveness of such applications is limited by the challenges of transmitting quantum information and maintaining precise control over quantum systems. For example, quantum information carriers, such as photons traveling through optical fibers, may be lost, or the operations performed may not be perfect. Consequently, it is crucial to develop robust tools for distributing and manipulating entanglement in distributed settings in order to fully unlock the capabilities of quantum technologies. In this thesis, we explore the influence of noise on the manipulation of entanglement in entanglement-based quantum networks. First, we examine the noise resilience of various resource states, i.e., pre-established entangled states, used to achieve bipartite or tripartite communication. This is followed by an analysis of a fully asymmetric network scenario, incorporating the noise introduced by the delays from classical messaging within the quantum network. We then propose classical communication protocols to achieve bipartite communication and evaluate their noise impact under the optimization of the arrangement of the pre-established entanglement. In addition, we propose an alternative approach to quantum repeaters, a key device for entanglement distribution, based on growing multipartite states, allowing entanglement to be recycled and patched. All investigations have been carried out employing a novel formalism, also developed in this thesis, for efficiently and accurately simulating noisy quantum processes on classical hardware, with broader applicability beyond quantum communication.
Quantum networks form the backbone of long-distance quantum information processing. Genuine multipartite entanglement (GME) serves as a key indicator of network performance and overall state quality. However, the widely used methods for certifying GME suffer from a major drawback that they either detect only a limited range of states or are applicable only to systems with a small number of parties. To overcome these limitations, we propose a family of sub-symmetric witnesses (SSWs), which are tractable both theoretically and experimentally. Analytically, we establish a connection between SSWs and the cut space of graph theory, enabling several powerful detection criteria tailored to practical quantum networks. Numerically, we show that the optimal detection can be formulated as a linear program, offering a significant efficiency advantage over the semidefinite programs commonly employed in quantum certification. Experimentally, SSWs can be evaluated via local measurements, with resource requirements independent of the local dimension in general, and even independent of the overall network size in many practical networks.
We introduce a repeater scheme to efficiently distribute multipartite entangled states in a quantum network with optimal scaling. The scheme allows to generate graph states such as 2D and 3D cluster states of growing size or GHZ states over arbitrary distances, with a constant overhead per node/channel that is independent of the distance. The approach is genuine multipartite, and is based on the measurement-based implementation of multipartite hashing, an entanglement purification protocol that operates on a large ensemble together with local merging/connection of elementary building blocks. We analyze the performance of the scheme in a setting where local or global storage is limited, and compare it to bipartite and hybrid approaches that are based on the distribution of entangled pairs. We find that the multipartite approach offers a storage advantage, which results in higher efficiency and better performance in certain parameter regimes. We generalize our approach to arbitrary network topologies and different target graph states.