We use a genetic algorithm (GA) as a design aid for determining the optimal provisioning of entangled photon spectrum in flex-grid quantum networks with arbitrary numbers of channels and users. After introducing a general model for entanglement distribution based on frequency-polarization hyperentangled biphotons, we derive upper bounds on fidelity and entangled bit rate for networks comprising one-to-one user connections. Simple conditions based on user detector quality and link efficiencies are found that determine whether entanglement is possible. We successfully apply a GA to find optimal resource allocations in four different representative network scenarios and validate features of our model experimentally in a quantum local area network in deployed fiber. Our results show promise for the rapid design of large-scale entanglement distribution networks.
We use a genetic algorithm (GA) as a design aid for determining the optimal provisioning of entangled photon spectrum in flex-grid quantum networks with arbitrary numbers of channels and users. After introducing a general model for entanglement distribution based on frequency-polarization hyperentangled biphotons, we derive upper bounds on fidelity and entangled bit rate for networks comprising one-to-one user connections. Simple conditions based on user detector quality and link efficiencies are found that determine whether entanglement is possible. We successfully apply a GA to find optimal resource allocations in four different representative network scenarios and validate features of our model experimentally in a quantum local area network in deployed fiber. Our results show promise for the rapid design of large-scale entanglement distribution networks.
As practical quantum networks approach large-scale deployment, the need for efficient user-to-user frequency allocation is increasing, yet current approaches only provide partial solutions to the routing and spectrum allocation problem for an arbitrary quantum network. We address this challenge for repeater-less flex-grid quantum networks based on hyperentangled photons using an efficient three-stage pipeline combining leading tools in classical networking with recent advances in numerical optimization. First, double instantiations of Yen's algorithm obtain low-loss route candidates between each pair of users and the entanglement sources. Second, the advanced process optimizer (APOPT) obtains frequency channel allocations that maximize distribution rates under fidelity constraints. Finally, the constraint programming solver using satisfiability methods (CP-SAT) assigns specific frequency bins to each link, ensuring that there is no contention between frequencies from different sources. We numerically demonstrate this approach on a representative ring network and a Manhattan incumbent local exchange carrier topology, realizing significant improvements over prior genetic algorithm approaches in speed, accuracy, and scalability. Overall, this pipeline provides an efficient heuristic workflow for optimizing broadband entanglement distribution, applicable to arbitrarily connected quantum networks integrated within the existing lightwave infrastructure.
Flexible grid wavelength division multiplexing is a powerful tool in lightwave communications to maximize spectral efficiency. In the emerging field of quantum networking, the need for effective resource provisioning is particularly acute, given the generally lower power levels, higher sensitivity to loss, and inapplicability of optical detection and retransmission. In this letter, we leverage flex grid technology to demonstrate reconfigurable distribution of quantum entanglement in a four-user tabletop network. By adaptively partitioning bandwidth with a single wavelength-selective switch, we successfully equalize two-party coincidence rates that initially differ by over two orders of magnitude. Our scalable approach introduces loss that is fixed with the number of users, offering a practical path for the establishment and management of quality-of-service guarantees in large quantum networks.
Quantum networks facilitate communication among quantum devices, playing a crucial role in enabling applications beyond the reach of classical networks. However, creating a quantum network that supports reliable long-distance entanglement distribution remains a significant challenge. Unlike classical networks, connections in quantum networks are established through entanglement generation. Effective communication between quantum devices requires a routing strategy that efficiently manages the establishment of entanglement. In addition to fidelity, the quality of communication is also determined by the capacity of the generated entanglement. Therefore, we proposed a capacity allocation scheduling scheme based on a metaheuristic approach, namely a Genetic Algorithm (GA), to ensure efficient capacity allocation for multiple communication paths within each communication request. Simulations were conducted in four different scenarios, and the results were compared to an existing capacity allocation scheduling algorithm, Progressive Filling (PF), to verify the effectiveness of the proposed scheme. The average capacity utilisation, U and weighted throughput, F results indicate that PF outperforms GA in a scenario with four communication requests, while GA performs better in scenarios involving six, eight, and ten communication requests. Specifically, the improvement in average capacity utilisation ranges from 8% to 46%, and the improvement in weighted throughput ranges from 24% to 94%. These results suggest that GA can serve as a valuable reference for designing optimal routing and capacity allocation schemes in more complex networks with multiple communication requests.
Abstract Quantum communication networks enable applications ranging from highly secure communication to clock synchronization and distributed quantum computing. Miniaturized, flexible, and cost-efficient resources will be key elements for ensuring the scalability of such networks as they progress towards large-scale deployed infrastructures. Here, we bring these elements together by combining an on-chip, telecom-wavelength, broadband entangled photon source with industry-grade flexible-grid wavelength division multiplexing techniques, to demonstrate reconfigurable entanglement distribution between up to 8 users in a resource-optimized quantum network topology. As a benchmark application we use quantum key distribution, and show low error and high secret key generation rates across several frequency channels, over both symmetric and asymmetric metropolitan-distance optical fibered links and including finite-size effects. By adapting the bandwidth allocation to specific network constraints, we also illustrate the flexible networking capability of our configuration. Together with the potential of our semiconductor source for distributing secret keys over a 60 nm bandwidth with commercial multiplexing technology, these results offer a promising route to the deployment of scalable quantum network architectures.
Multipartite entangled states (MES) are useful resources for a wide range of quantum applications, including quantum secret sharing, and quantum sensing. In this work, we propose a scalable architecture for distributing multipartite entangled states (MES) using arbitrary bipartite quantum networks. In particular, we address the problem of joint tree selection and rate allocation in multipartite entanglement distribution networks in order to optimize the weighted aggregate MES generation rate across different user groups. To obtain optimal solutions, we develop a mixed-integer programming (MIP) model and employ a heuristic approach based on the Genetic algorithm (GA) to obtain feasible solutions efficiently.