Routing in a quantum network

Hilal Sultan Duranoglu Tunc, Joy Halder, Muhammad Idham Habibie +4 more

Sijia Yu, Zefan Tang, Zimin Jiang +1 more

Quantum networks present a potent solution to secure microgrid communication in the quantum era. Efficient quantum network routing protocols play an important role in developing practical and resilient quantum network-based microgrids. In this paper, we make the following contributions: 1) establish lightweight-yet-holistic routing tables for scalable and low-latency quantum routing in microgrids; 2) devise efficient distributed local routing protocols for quantum network-enabled microgrids; and 3) integrate the devised protocols in a real-time QNetGrid testbed and evaluate their performance under different scenarios. Experiments validate the efficacy of the devised methods and provide insights for developing efficient quantum network routing for cyber-resilient microgrids,

Günter Mahler A, Volker A. Weberruß

Linh Le, Tu N. Nguyen

Quantum routing plays a key role in the development of the next-generation network system. In particular, an entangled routing path can be constructed with the help of quantum entanglement and swapping among particles (e.g., photons) associated with nodes in the network. From another side of computing, machine learning has achieved numerous breakthrough successes in various application domains, including networking. Despite its advantages and capabilities, machine learning is not as much utilized in quantum networking as in other areas. To bridge this gap, in this article, we proposea novel quantum routing modelfor quantum networks that employs machine learning architectures to construct the routing path for the maximum number of demands (source–destination pairs) within a time window. Specifically, we present a deep reinforcement routing scheme that is called Deep Quantum Routing Agent (DQRA). In short, DQRA utilizes an empirically designed deep neural network that observes the current network states to accommodate the network’s demands, which are then connected by a qubit-preserved shortest path algorithm. The training process of DQRA is guided by a reward function that aims toward maximizing the number of accommodated requests in each routing window. Our experiment study shows that, on average, DQRA is able to maintain a rate of successfully routed requests at above 80% in a qubit-limited grid network and approximately 60% in extreme conditions, i.e., each node can be repeater exactly once in a window. Furthermore, we show that the model complexity and the computational time of DQRA are polynomial in terms of the sizes of the quantum networks.

Hui Han, Bo Liu, Bang-Ying Tang +4 more

Abstract The entanglement distribution networks with various topologies are mainly implemented by active wavelength multiplexing routing strategies, which directly transmit entangled photons between quantum network nodes. However, designing an entanglement routing scheme, which achieves the maximized network connections and the optimal overall network efficiency simultaneously, remains a huge challenge for quantum networks. In this article, we propose a differentiated service entanglement routing (DSER) scheme, which firstly finds out the lowest loss paths and supported wavelength channels with the tensor-based path searching algorithm, and then allocates the paired channels with the differentiated routing strategies. The evaluation results show that the proposed DSER scheme can be performed for constructing various large scale quantum networks.

Günter Mahler A, Volker A. Weberruß