In this work, we describe a routing algebra corresponding to the problem of establishing end-to-end quantum entanglements between nodes connected through a network of first generation quantum repeaters. Our goal is to design an algorithm which can determine all the routes and swapping schedules to achieve maximal rates of end-to-end entanglement. We aim to provide an improvement in terms of complexity over an existing solution while increasing the number of routes and schedules available to offer more alternatives for the entanglement generation layer of a quantum protocol stack.
In this work, we describe a routing algebra corresponding to the problem of establishing end-to-end quantum entanglements between nodes connected through a network of first generation quantum repeaters. Our goal is to design an algorithm which can determine all the routes and swapping schedules to achieve maximal rates of end-to-end entanglement. We aim to provide an improvement in terms of complexity over an existing solution while increasing the number of routes and schedules available to offer more alternatives for the entanglement generation layer of a quantum protocol stack.
With the emergence of the Quantum Internet, the need for advanced quantum networking techniques has significantly risen. Various models of quantum repeaters have been presented, each delineating a unique strategy to ensure quantum communication over long distances. We focus on repeaters that employ entanglement generation and swapping. This revolves around establishing remote end-to-end entanglement through repeaters, a concept we denote as the “quantum-native” repeaters (also called “first-generation” repeaters in some literature). The challenges in routing with quantum-native repeaters arise from probabilistic entanglement generation and restricted coherence time. Current approaches use synchronized time slots to search for entanglement-swapping paths, resulting in inefficiencies. Here, we propose a new set of asynchronous routing protocols for quantum networks by incorporating the idea of maintaining a dynamic topology in a distributed manner, which has been extensively studied in classical routing for lossy networks, such as using a destination-oriented directed acyclic graph or a spanning tree. The protocols update the entanglement-link topology asynchronously, identify optimal entanglement-swapping paths, and preserve unused direct-link entanglements. Our results indicate that asynchronous protocols achieve a larger upper bound with an appropriate setting and significantly higher entanglement rate than existing synchronous approaches, and the rate increases with coherence time, suggesting that it will have a much more profound impact on quantum networks as technology advances.
To fully unleash the potentials of quantum computing, several new challenges and open problems need to be addressed. From a routing perspective, the optimal routing problem, i.e., the problem of jointly designing a routing protocol and a route metric assuring the discovery of the route providing the highest quantum communication opportunities between an arbitrary couple of quantum devices, is crucial. In this paper, the optimal routing problem is addressed for generic quantum network architectures composed by repeaters operating through single atoms in optical cavities. Specifically, we first model the entanglement generation through a stochastic framework that allows us to jointly account for the key physical-mechanisms affecting the end-to-end entanglement rate, such as decoherence time, atom-photon and photon-photon entanglement generation, entanglement swapping, and imperfect Bell-state measurement. Then, we derive the closed-form expression of the end-to-end entanglement rate for an arbitrary path and we design an efficient algorithm for entanglement rate computation. Finally, we design a routing protocol and we prove its optimality when used in conjunction with the entanglement rate as routing metric.
First-generation quantum repeaters are essential in distributing entanglement over long distances since they could mitigate losses in optical fiber. Repeaters split the total distance into shorter, easier to generate links. Then, entanglement swapping establishes long range entanglement by performing local measurements at the repeaters and heralding their results. In this work, we develop an analytical model that estimates the impact of decoherence during heralding for a given protocol. Furthermore, we identify a competition between two phenomena: as repeater count increases, so does entanglement generation, but the additive impact of memory decoherence on final entanglement rate increases too. Therefore, we find that an optimal number of repeaters exists. These findings could lead the design of future quantum networks, both in the inter-repeater distance and swapping timings.
Future quantum internet aims to enable quantum communication between arbitrary pairs of distant nodes through the sharing of end-to-end entanglement, a universal resource for many quantum applications. As in classical networks, quantum networks also have to resolve problems related to routing and satisfaction of service at a sufficient rate. We deal here with the problem of scheduling when multiple commodities must be served through a quantum network based on first generation quantum repeaters, or quantum switches. To this end, we introduce a novel discrete-time algebraic model for arbitrary network topology, including transmission and memory losses, and adapted to dynamic scheduling decisions.Our algebraic model allows the scheduler to use the storage of temporary intermediate links to optimize the performance, depending on the information availability, ranging from full global information for a centralized scheduler to partial local information for a distributed one. As an illustrative example, we compare a simple greedy scheduling policy with several Max-Weight inspired scheduling policies and illustrate the resulting achievable rate regions for two competing pairs of clients through a network.
Entanglement generation in long-distance quantum networks is a difficult process due to resource limitations and the probabilistic nature of entanglement swapping. To maximize success probability, existing quantum routing algorithms employ computationally expensive solutions (e.g., linear programming) to determine which links to entangle and use for end-to-end entanglement generation. Such optimization methods, however, cannot meet the delay requirements of real-world quantum networks, necessitating swift yet efficient real-time optimization models. In this paper, we propose reinforcement learning (RL)-based models to determine which links to entangle and proactively swap to meet connection requests. We show that the proposed RL-based approach is 20x faster compared to linear programming. Moreover, we show that one can take advantage of the longevity of entanglements to (i) cache entangled links for future use and (ii) proactively swap entanglement on high-demand path segments, thereby increasing the likelihood of request success. Through comprehensive simulations, we demonstrate that caching unused entanglements leads to a 10-15% improvement in the performance of state-of-the-art quantum routing algorithms. Complementing caching with proactive entanglement swapping further enhances the request success rate by up to 52.55%.
This paper considers the problem of finding an optimal order for entanglement swapping in a heterogeneous path of quantum repeaters so as to maximize the path throughput defined as the delivery rate of end-to-end entanglements. The primary difficulty in addressing this problem lies in the vast array of possible swapping orders for large paths and the complexity of the expected throughput, which depends on the attributes of each node and edge along the path, as well as the order of swapping. To cope with these issues, we first propose simple approximations in estimating the swapping outcome between two entanglement distributions that can run in constant time, thereby providing an efficient approach for evaluating and comparing different swapping orders, allowing us to solve the problem exactly for small paths. Second, as the number of possible orders grows exponentially with the number of repeaters in the path, we develop an efficient heuristic based on the greedy selection of nodes to sequentially perform swaps according to their swapping scores, defined as the expected number of entanglements resulting from their swaps. The scores are local but dynamic in the sense that they depend not just on the entanglement distributions available on the path but also on prior swapping decisions. Finally, we illustrate the efficiency and effectiveness of our proposed model and approach through extensive experimentation conducted using a general quantum network simulator.