Quantum networks emerge as fundamental frameworks for addressing various large-scale problems. There are two primary architectures: space-based quantum networks, which deploy satellites with free space channels to interconnect users, and ground-based quantum networks, which utilize optical fibers to interconnect users. In this paper, we explore space-ground integrated quantum networks that incorporate both satellites and optical fibers into the infrastructure. This integrated network features three forms of communication: using only free space links, only ground links, or a hybrid usage of free space and ground links. We formulate the routing problem in space-ground integrated quantum networks as an integer programming and propose two solutions: using linear relaxation or a greedy algorithm. The linear relaxation method allows timely scheduling of additional entanglement purification, whereas the greedy method enables quick scheduling. Simulation results demonstrate their effective balancing between network throughput and communication fidelity.
Quantum networks emerge as fundamental frameworks for addressing various large-scale problems. There are two primary architectures: space-based quantum networks, which deploy satellites with free space channels to interconnect users, and ground-based quantum networks, which utilize optical fibers to interconnect users. In this paper, we explore space-ground integrated quantum networks that incorporate both satellites and optical fibers into the infrastructure. This integrated network features three forms of communication: using only free space links, only ground links, or a hybrid usage of free space and ground links. We formulate the routing problem in space-ground integrated quantum networks as an integer programming and propose two solutions: using linear relaxation or a greedy algorithm. The linear relaxation method allows timely scheduling of additional entanglement purification, whereas the greedy method enables quick scheduling. Simulation results demonstrate their effective balancing between network throughput and communication fidelity.
Quantum Information networks (QIN) aim to interconnect quantum systems via quantum repeaters through end-to-end entanglement of qubits. The integration of both satellites and ground segments is essential to provide global connectivity, even over large distances. In this paper, we study the problem of entanglement routing in large-scale quantum networks -i.e., with a large number of nodes, with a hybrid space-ground architecture. We decompose the routing problem into two subcomponents: request scheduling and path selection, and structure our approach around two phases: a proactive and a reactive step. We design and implement an entanglement routing strategy in an emulated European quantum network, first in a custom Python-based simulator for performance forecasting, and then into the NetSquid quantum network simulator. Our work thus provides a tool allowing for a comparison between terrestrial and satellite segments in terms of successful end-to-end entanglement in a large-scale network and shows that both segments are required for optimal service. Our results indicate that, within the emulated European topology, terrestrial networks can support end-toend entanglement for approximately 35% of user pairs -the remaining pairs are too distant and suffer from prohibitive losses. In contrast, the satellite-based network achieves connectivity for up to 91% of user pairs, although some pairs remain unreachable due to a lack of simultaneous satellite visibility. However, while satellites can outperform terrestrial networks in total photon distribution, they may not be suitable for lowlatency requests if out of visibility, making ground networks essential. This highlights the complementary roles of space and terrestrial segments in quantum networking.
In the era of 6G and beyond, space-aerial-terrestrial quantum networks (SATQNs) are poised to advance the development of a global-scale quantum Internet. These networks leverage free space optical satellite and aerial quantum networks to complement optical fiber-based terrestrial quantum networks to enable the distribution of high-fidelity quantum entanglement over long distances. However, establishing multi-hop end-to-end quantum entanglement remains highly challenging, not only due to time-varying link conditions and structural heterogeneity inherent in SATQNs, but also because noise in quantum channels and imperfections in quantum operations can degrade the quality of entanglement. To address this challenge, we formulate an optimization problem that maximizes SATQN throughput by jointly optimizing routing path selection and entanglement generation rates (PS-EGR) while ensuring high entanglement fidelity. The resulting problem is a mixed-integer linear programming (MILP) formulation, which is NP-hard. We propose a Benders’ decomposition (BD)-based approach to solve this problem efficiently. Specifically, the MILP is decomposed into a master problem for binary routing path selection and a subproblem for continuous entanglement generation rate optimization. Numerical results validate the effectiveness of the proposed PS-EGR scheme, offering critical insights into the optimization and deployment of SATQNs.
The problem of scheduling in quantum networks amounts to choosing which entanglement swapping operations to perform to better serve user demand. The choice can be carried out following a variety of criteria (e.g. ensuring all users are served equally vs. prioritizing specific critical applications, adopting heuristic or optimization-based algorithms...), requiring a method to compare different solutions and choose the most appropriate. We present a framework to mathematically formulate the scheduling problem over quantum networks and benchmark general quantum scheduling policies over arbitrary lossy quantum networks. By leveraging the framework, we apply Lyapunov drift minimization to derive a novel class of quadratic optimization based scheduling policies, which we then analyze and compare with a Max Weight inspired linear class. We then give an overview of the pre-existing fiber quantum simulation tools and report on the development of numerous extensions to QuISP, an established quantum network simulator focused on scalability and accuracy in modeling the underlying classical network infrastructure. To integrate satellite links in the discussion, we derive an analytical model for the entanglement distribution rates for satellite-to-ground and ground-satellite-ground links and discuss different quantum memory allocation policies for the dual link case. Our findings show that classical communication latency is a major limiting factor for satellite communication, and the effects of physical upper bounds such as the speed of light must be taken into account when designing quantum links, limiting the attainable rates to tens of kHz. We conclude by summarizing our findings and highlighting the challenges that still need to be overcome in order to study the quantum scheduling problem over fiber and satellite quantum networks. [Abridged abstract, see PDF for full version]
We experimentally demonstrate a reconfigurable quantum network architecture suitable for integrating satellite links in metropolitan quantum networks. The network architecture is designed such that once a satellite is in range, it is configured in a multipoint-to-point topology where all ground nodes establish entanglement with the satellite receiver using time multiplexing to optimize long-distance transmission. Otherwise, the satellite up-link can be rerouted to the ground nodes to form a pair-wise ground network. Leveraging both the time and frequency correlations of our photon-pair source, we demonstrate an increased coincidence-to-accidental ratio without additional resource overhead in a five-node network. To contextualize these experimental findings, we project their performance in a quantum key distribution scenario and outline a feasible route toward field deployment, using integrated photonics to enable network integration of up to 72 users.
Satellite-based quantum networks leverage the advantageous properties of optical signals from satellites to ground stations, to enable the distribution of high-fidelity quantum entanglements over vast distances, thus circumventing the limitations of traditional terrestrial-based systems. However, the satellite-based entanglement distribution coupled with terrestrial quantum swapping in the space-terrestrial integrated network becomes very complex when considering the joint optimization with satellite assignment, resource allocation, and path selections. To tackle this issue, we introduce a hybrid quantum-classical Dantzig-Wolfe decomposition technique by leveraging the strengths of both quantum and classical computing, to solve the joint optimization problem. Through a series of experiments, the paper demonstrates the efficiency and robustness of the proposed methods in addressing large-scale network optimization and balancing qubit usage. The insights generated by this work offer valuable guidance for the design and implementation of satellite-based entanglement distribution for quantum networks, thereby laying the groundwork for the realization of a secure quantum communication infrastructure on a global scale.
Quantum satellite networks offer a promising solution for achieving long-distance quantum communication by enabling entanglement distribution across global scales. This work formulates and solves the quantum satellite network scheduling problem by optimizing satellite-to-ground station pair assignments under realistic system and environmental constraints. Our framework accounts for limited satellite and ground station resources, fairness, entanglement fidelity thresholds, and real world non-idealities including atmospheric losses, weather and background noise. In addition, we incorporate the complexities of multi-satellite relays enabled via inter-satellite links. We propose an integer linear programming (ILP) based optimization framework that supports multiple scheduling objectives, allowing us to analyze tradeoffs between maximizing total entanglement distribution rate and ensuring fairness across ground station pairs. Our framework can also be used as a benchmark tool to measure the performance of other potential transmission scheduling policies.