Coherence and fidelity aware routing in quantum networks

Spatio-temporal Path Optimization for Stabilizer-Code-Protected Quantum Networks

Quantum Error Correction~(QEC)-protected direct transmission is a fundamental approach to preserve fragile quantum states while they are physically forwarded across noisy quantum networks. When a logical qubit traverses multiple hops, selected QEC-capable nodes may recover the encoded state before it continues along the route. The feasibility and cost of the final transmission strategy therefore depend on how we jointly choose the path, the recovery locations, and the protection schemes. In this paper, we formulate and analyze a cross-layer spatio-temporal path optimization problem for block-style stabilizer-code-protected direct transmission. Our main results include fixed-scheme and flexible-scheme single-flow routing algorithms, as well as a multi-flow routing algorithm. The framework developed in this paper can serve as an algorithmic building block for QEC-aware routing under logical-error and logical-lifetime constraints. Simulations show that it reduces single-flow average routing cost by approximately 25--30\% over Decode-Always and lowers multi-flow throughput-normalized congestion by approximately 28--31\% over Greedy-Assignment.

Multipartite Entanglement Routing in Integrated Ground–Satellite Quantum Networks

Resource Management for Distributed Quantum Computing in Quantum Data Centers

In recent years, advances in quantum computing have been driven by substantial improvements in both the number and quality of qubits. As the field progresses, there is growing interest in interconnecting quantum systems to enable scalable computation through Distributed Quantum Computing (DQC) architectures. Consider a distributed quantum application executed across multiple Quantum Processing Units (QPUs) within a quantum data center, where remote gates require establishing entanglement between different QPUs. The creation of such end-to-end entanglement can lead to network congestion and resource contention. To address these challenges, we propose a resource management framework that maximizes fidelity-guaranteed throughput while satisfying dependency constraints. We first formulate the problem as a Mixed-Integer Linear Programming (MILP) model to provide a performance benchmark. Building on this, we develop efficient approximate scheduling algorithms that achieve performance comparable to the optimization solver. Although a trade-off exists between execution time and network throughput, simulation results demonstrate that one of the proposed strategies, Weighted Group Least Resource First (WGLRF), closely approximates the solver’s performance across most scenarios. These findings suggest that the lightweight strategy is sufficient for current DQC settings, offering a practical solution for managing remote-gate resource contention in distributed quantum circuits and improving overall system performance.

Efficient routing and spectrum allocation in arbitrary flex-grid entanglement 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.

Demand-Aware Identification of High-Fidelity Link Sets in Quantum Networks

Ensuring the reliability of quantum networks requires the accurate evaluation of fidelity-a metric representing link quality-and the selection of high-fidelity links. However, since fidelity estimation consumes a large number of measurements, an efficient method for identifying high-quality communication links with limited resources is desirable. Existing studies have primarily focused on identifying high-fidelity links between a pair of nodes, leaving adaptive resource allocation insufficiently explored in multi-destination environments where destinations differ in network importance (e.g., communication demand or the quantum memory capacity of nodes). In this study, we propose DaTopLinks (Demand-aware Top- $K$ HighFidelity Links), a method for efficiently identifying the top- $K$ destinations and their best link for each selected destination according to a utility function that combines destination importance and link fidelity. The algorithm introduces a dual-criterion link elimination mechanism that simultaneously performs intradestination link elimination and top- $K$ destination elimination. It also incorporates an early confirmation mechanism that allows early termination of measurements for destinations once their inclusion in the top- $K$ set and the identification of their best link are statistically guaranteed. In our theoretical analysis, we derive an upper bound on the sample complexity based on an effective gap that captures both inter-destination utility differences and intra-destination fidelity differences. Simulation results demonstrate that the proposed method functions effectively under depolarizing, dephasing, and bit-flip noise models.

Dynamic Entanglement Distribution for Multi-User and Multi-Protocol Quantum Networking

A metropolitan-scale entanglement-based quantum communication network enabled by a quantum reconfigurable optical add-drop multiplexer (q-ROADM), which dynamically distributes polarisation-entangled photon pairs from a broadband source to six users over deployed campus and metropolitan fibre, is demonstrated.