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Future Generation Computer Systems

Entanglement in the trees: Optimal entanglement distribution in binary tree quantum network topologies

Iulian Ioan Bîrlică, Alin-Bogdan Popa, Bogdan-Călin Ciobanu, Florin Pop, Pantelimon George Popescu

Published May 15, 2026• 1 citation
Publisher

Abstract

Quantum entanglement is the most important resource in quantum networks, with no classical equivalent, and therefore, efficient entanglement distribution plays a key role in quantum communications and technologies. Optimal distribution of entanglement in a general network is a known hard problem. In this paper we analyze entanglement distribution via entanglement swapping in tree topologies showing how the problem can be reduced to chordal graph coloring. Our proposed solutions are mathematically sound for any tree network, providing polynomial-time optimal scheduling for entanglement distribution. The binary tree topology requires only one Bell State Measurement device per node, i.e. minimal hardware configuration, so, providing an optimal polynomial-time entanglement distribution algorithm for this topology establishes a fundamental building block that can be extended to more general tree topologies with diverse hardware setups. Through numerical simulation, we present a comprehensive analysis of the requests distribution per timeslot, optimal number of timeslots, variance, and running time, in terms of tree size, request distance bias, and parametrized balance in the tree topology construction. A complete optimality and complexity analysis is also provided.

DOI
10.1016/j.future.2026.108597

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Quantum entanglement is the most important resource in quantum networks, with no classical equivalent, and therefore, efficient entanglement distribution plays a key role in quantum communications and technologies. Optimal distribution of entanglement in a general network is a known hard problem. In this paper we analyze entanglement distribution via entanglement swapping in tree topologies showing how the problem can be reduced to chordal graph coloring. Our proposed solutions are mathematically sound for any tree network, providing polynomial-time optimal scheduling for entanglement distribution. The binary tree topology requires only one Bell State Measurement device per node, i.e. minimal hardware configuration, so, providing an optimal polynomial-time entanglement distribution algorithm for this topology establishes a fundamental building block that can be extended to more general tree topologies with diverse hardware setups. Through numerical simulation, we present a comprehensive analysis of the requests distribution per timeslot, optimal number of timeslots, variance, and running time, in terms of tree size, request distance bias, and parametrized balance in the tree topology construction. A complete optimality and complexity analysis is also provided.
Entanglement distribution networks are essential for enabling secure, reliable, and sustained communication through the future Quantum Internet. Multi-ring network topologies offer improved scalability and redundancy, but also introduce additional routing complexity for the task of efficiently distributing entanglement. This paper solves the problem of optimal entanglement distribution in multi-ring quantum network topologies. Two separate multi-ring network configurations are analyzed, one where requests can only be routed within a single ring layer, and involves a less complex node setup, and one where requests may switch ring layers when passing through the network's nodes, at the cost of additional complexity within the nodes themselves. We propose algorithms that solve the problem of entanglement distribution in terms of optimal time needed to satisfy a set of entanglement resupply requests with given network resources, as well as the problem of optimal resources in order to satisfy a set of entanglement resupply requests within a single entanglement transmission and measurement step. We provide a comprehensive analysis of the proposed algorithms through computer simulations, which indicate that the additional complexity of a network which allows switching between ring layers brings little benefit in terms of time to serve requests, but may reduce the number of resources needed to satisfy the entanglement distribution requests in a non-blocking manner.
Quantum network communication is challenging, as the no-cloning theorem in the quantum regime makes many classical techniques inapplicable; in particular, the direct transmission of qubit states over long distances is infeasible due to unrecoverable errors. For the long-distance communication of unknown quantum states, the only viable communication approach (assuming local operations and classical communications) is the teleportation of quantum states, which requires a prior distribution of the entangled pairs (EPs) of qubits. The establishment of EPs across remote nodes can incur significant latency due to the low probability of success of the underlying physical processes. The focus of our work is to develop efficient techniques that minimize EP generation latency. Prior works have focused on selecting entanglementpaths; in contrast, we selectentanglement swapping trees—a more accurate representation of the entanglement generation structure. We develop a dynamic programming algorithm to select an optimal swapping tree for a single pair of nodes, under the given capacity and fidelity constraints. For the general setting, we develop an efficient iterative algorithm to compute a set of swapping trees. We present simulation results, which show that our solutions outperform the prior approaches by an order of magnitude and are viable for long-distance entanglement generation.
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.
Quantum networks are designed to transmit quantum bits (qubits) among quantum devices to enable new network resources for the applications. Entanglement distribution and entanglement swapping are fundamental procedures that are required in several network operations. However, they are probabilistic operations, which can lead to severe network performance degradation. This article investigates the engineering problem of resource allocation in quantum networks, considering factors like entanglement distribution probability, quantum memory characteristics, and fidelity. We model this as an optimization model to obtain an optimal solution. In particular, we formulate an integer linear programming (ILP) and develop a heuristic algorithm, aiming to minimize the number of required entangled qubit pairs (Bell pairs or EPR pairs) in any adjacent pair in the quantum network. Extensive simulations are performed to compare the performance of proposed ILP and heuristic. In all the cases, the heuristic produces a comparable solution to the optimal one. Simulation results ensure that the value of maximum utilized Bell pairs in a quantum network highly depends on the value of the probability of entangled pairs established, considering the time in the quantum memory besides the number of incoming requests.
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.
Swapping and purification are the two fundamental building blocks for high-fidelity entanglement distribution in multi-hop quantum networks. Unfortunately, it is still a mystery how they intertwine with each other to affect the fidelity and cost of end-to-end entanglements. Current scheduling algorithms consider this problem under relatively limited assumptions and a critical yet unjustified conjecture. In this work, we first consider more general assumptions with operation failures and, accordingly, extend a tree-based modeling for joint swapping and purification. Then, we analytically prove the previous conjecture that the optimal strategy underBinary systemis always to purify the entanglements before any swapping. This sheds light on the protocol and device design for quantum networks. We then further propose a tree-based algorithm, which can efficiently schedule swapping and purification along a path for bothBinaryandWerner systems. Extensive simulations of the proposed method against state-of-the-art solutions show that our method uses fewer entanglements to establish qualified end-to-end entanglements, and thus achieves higher network throughput.