AMARQ: Adaptive multi-application routing for quantum networks

Abstract

Abstract Future quantum networks will have to support different applications on shared infrastructure, like fidelity-critical Quantum Key Distribution (QKD) and latency-sensitive Distributed Quantum Computing (DQC). The existing approaches for entanglement routing either optimise for a single application, or rely on sequential resource allocation, which results in inefficient resource utilisation, unfairness and degraded performance when multiple applications compete for shared network resources. In this paper, we propose AMARQ, a multi-objective Deep Q-Network (DQN) based routing framework to jointly serve heterogeneous QKD and DQC traffic on shared quantum infrastructure. The agent makes adaptive and application-aware routing decisions to dynamically balance the rigid fidelity and latency requirements of QKD and the high-throughput and elastic rate requirements of DQC. The reward function combines a successful-routing throughput term with a per-edge fidelity penalty and an end-of-episode failure penalty; per-flow latency is enforced as a QoS constraint, and inter-application fairness is enforced by a dedicated admission-control loop that reserves a dynamic QKD qubit pool. We assess the performance of AMARQ on grid topologies with 25 to 625 nodes. AMARQ attains a request success ratio above 85\%, which is up to 32 percentage points higher than ESDI and 39 percentage points higher than Cicconetti, while keeping the end-to-end fidelity above 0.80 and the inference latency below 90~ms for all configurations.