The quantum internet will extend today's networks with a capability no classical infrastructure can offer: the distribution of entanglement between distant nodes. That single resource underlies services provably beyond classical reach, such as secure communication against computationally unbounded adversaries, blind delegated computation on remote quantum servers, and entangled networks of atomic clocks. Most of these services require a single multipartite state shared among several nodes at once — for the most part a graph state: one qubit per vertex of a graph, one entangling interaction per edge. This Thesis addresses the distribution of one such state: given an arbitrary network of entanglement switches, deliver the m-qubit path graph state, in the order the application requests, to m single-qubit end nodes — the weakest client model in the literature. Prior protocols support arbitrary topologies or such minimal end nodes, never both. The strongest of them are also centralized: the construction and the memory demand concentrate at a single node. The Thesis takes the opposite approach: a distributed protocol. The Path Graph State Distribution (PathGSD) protocol grows the target state one end node at a time behind a single reference qubit that walks a classically planned route, the shortest ordered Steiner walk. The work is partitioned among the switches, which coordinate only through entanglement and classical messages; no single node ever builds or stores the whole state. The design is deliberately simple, guided by engineering principles, and the simplicity pays at scale: planning is polynomial and completes in seconds on a network of 22,500 switches, where the closest optimization-based alternatives face exponential blow-up. Correctness is proved in the graph-state measurement calculus; a memory-reuse discipline and a parallel multi-domain execution mode complete the protocol. The protocol is implemented as communicating discrete-event processes on the QuantumSavory simulator, validated against exact theoretical expectations, and evaluated against the strongest available baselines: the star-specific Piecemaker and Factory protocols, simulated under noise, and the Graph State Transfer (GST) algorithm's proved cost expressions, evaluated exactly on arbitrary topologies. PathGSD consumes fewer Einstein-Podolsky-Rosen (EPR) pairs than the exact GST baseline on every single-domain family tested, keeps switch memory constant in the network size where the centralized baseline's grows, matches the star-specific protocols on their home topology, and reaches measured speed-ups of up to 1.9× when two administrative domains execute in parallel.
The quantum internet will extend today's networks with a capability no classical infrastructure can offer: the distribution of entanglement between distant nodes. That single resource underlies services provably beyond classical reach, such as secure communication against computationally unbounded adversaries, blind delegated computation on remote quantum servers, and entangled networks of atomic clocks. Most of these services require a single multipartite state shared among several nodes at once — for the most part a graph state: one qubit per vertex of a graph, one entangling interaction per edge. This Thesis addresses the distribution of one such state: given an arbitrary network of entanglement switches, deliver the m-qubit path graph state, in the order the application requests, to m single-qubit end nodes — the weakest client model in the literature. Prior protocols support arbitrary topologies or such minimal end nodes, never both. The strongest of them are also centralized: the construction and the memory demand concentrate at a single node. The Thesis takes the opposite approach: a distributed protocol. The Path Graph State Distribution (PathGSD) protocol grows the target state one end node at a time behind a single reference qubit that walks a classically planned route, the shortest ordered Steiner walk. The work is partitioned among the switches, which coordinate only through entanglement and classical messages; no single node ever builds or stores the whole state. The design is deliberately simple, guided by engineering principles, and the simplicity pays at scale: planning is polynomial and completes in seconds on a network of 22,500 switches, where the closest optimization-based alternatives face exponential blow-up. Correctness is proved in the graph-state measurement calculus; a memory-reuse discipline and a parallel multi-domain execution mode complete the protocol. The protocol is implemented as communicating discrete-event processes on the QuantumSavory simulator, validated against exact theoretical expectations, and evaluated against the strongest available baselines: the star-specific Piecemaker and Factory protocols, simulated under noise, and the Graph State Transfer (GST) algorithm's proved cost expressions, evaluated exactly on arbitrary topologies. PathGSD consumes fewer Einstein-Podolsky-Rosen (EPR) pairs than the exact GST baseline on every single-domain family tested, keeps switch memory constant in the network size where the centralized baseline's grows, matches the star-specific protocols on their home topology, and reaches measured speed-ups of up to 1.9× when two administrative domains execute in parallel.
I present a protocol that converts |E| elementary two-qubit resource states, one per edge of a target graph G=(V,E), into the distributed graph state |G> using only operations local to each party and classical communication, reaching arbitrary graph topologies rather than the GHZ class of prior walk-based schemes. The elementary step is obtained from the coined discrete-time quantum walk by replacing the position-permuting shift with a diagonal CZ gate, the phase quantum walk (PQW); on each edge it realises the entanglement-assisted non-local CZ gate. Because every gate and correction is diagonal, all edges run in a single round with the local correction C_v = Z_v^{g_v}, verified exhaustively on 22 connected graphs (32,212 outcomes) at F = 1.0. The central result is an exact fidelity theory under independent Pauli noise on the resource qubits, with a separate channel on each. When the noise acts after the local gate, the fidelity factorises over vertices; for depolarising noise F* = prod_v [1 + (1 - 4p/3)^{deg v}]/2, with the degree sequence entering only at second order. When it acts on the stored pair, as link-generation, transmission and storage noise does, it becomes an edge-cover partition function, F* = 2^{-|V|} sum_{S subset V} (1 - 4p/3)^{2|E(S)|}, bounded above by the vertex product and with a leading-order loss coefficient 3/2 times larger. Dephasing gives the same fidelity at both placements. On ibm_kingston, direct fidelity estimation certifies F = 0.815(3) for |L_4>, 0.776(3) for |GHZ_4> and 0.733(3) for |C_4>. Native SWAP-free execution at coupling girth gamma requires target girth at least gamma/3 and maximum degree at most 3; on heavy-hex this forbids triangles, though |K_4>, being LC-equivalent to a star, remains reachable.
Graph states are a particular class of entangled quantum states, that play essential roles in distributed quantum computing and quantum communication. In both cases, graph states are usually used as resources for a specific set of quantum computers to share information. Therefore, distributing a graph state across a quantum network is an important problem. Currently, we do not have an efficient method for generating Einstein-Podolsky-Rosen(EPR) pairs on demand. Hence EPR pairs needed to distribute graph states are critical resources, and it is important to design distribution algorithms that reduce the need for such resources. Meignant et al. [1] presented the edge-decorated complete graph algorithm that uses n(n – 1)/2 number of EPR pairs to distribute the given graph state, where n is number of node in the network. Fischer et al [2] proposed the Graph State Transfer (GST) algorithm, which consumes fewer EPR pairs. However, GST requires an unbounded amount of memory at each node and preparation of the entire graph state in a single network node. In this poster, we present an integer programming formulation that removes these two assumptions. The model accounts for both the topology of the quantum network and memory constraints at each network node. Meanwhile, we propose a greedy algorithm to solve the problem.
Graph states form an important class of multipartite entangled quantum states. We propose a new approach for distributing graph states across a quantum network. We consider a quantum network consisting of nodes—quantum computers within which local operations are free—and EPR pairs shared between nodes that can continually be generated. We prove upper bounds for our approach on the number of EPR pairs consumed, completion time, and amount of classical communication required, all of which are equal to or better than that of prior work [10]. We also reduce the problem of minimizing the completion time to distribute a graph state using our approach to a network flow problem having polynomial time complexity.
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.
Distributing multipartite entanglement over a quantum network means routing it through a shared resource state. Existing measurement-based schemes search for a fresh path and re-verify the topology before every request, placing a network-wide classical exchange on the critical path of each one. We introduce DODAG-X, which removes it. A single destination-oriented directed acyclic graph spanning tree is computed once and reused across all requests, so each party's route is recovered by following parent pointers instead of by a new search. The per-request routing cost drops from O(N) to O(N) on symmetric grids and to O(logN) on small-world networks for N nodes, and only the N−1 tree links need be maintained under link loss. Routing on the sparse tree also shrinks the neighborhoods cleared to isolate the parties, lowering measurements per request by roughly 19\% on small-world graphs and up to 34\% on moderately dense, strongly rewired ones; on a fixed tree the two protocols use identical counts. We prove correctness for up to three parties with no restriction on topology, and prove a sufficient condition under which one application yields an n-party GHZ state for any n. We then delimit it, exhibiting requests outside the hypothesis whose output is multipartite entangled yet in a different local-Clifford class. Under a discrete-time Markov failure model the classical repair layer matches the reachability of full-graph re-search up to a failed-edge fraction of one half, and a coherence criterion relating tree depth to memory lifetime identifies the viable hardware platforms.
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.