Novel Support Routing Algorithm for Quantum Satellite Networks with Finite Quantum Memory

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.

Multipartite Entanglement Routing in Integrated Ground–Satellite Quantum Networks

Adaptive Entanglement Management in Quantum Multi-Core Architectures

Scalable quantum computing architectures increasingly rely on multi-core designs, where qubits are distributed across multiple processing cores interconnected through a quantum Network-on-Chip (NoC). In such systems, inter-core communication is typically realized through entanglement-assisted quantum teleportation, making efficient entanglement generation critical for performance. In this paper, we perform a comparative study of three entanglement management paradigms for multi-core quantum processors: reactive on-demand generation (ODG), proactive continuous pre-generation (CGP), and an adaptive continuous pre-generation approach (ACGP). While ODG generates entanglement only when required, CGP reduces average teleportation latency by pre-generating EPR pairs in the background. To improve upon this, we propose ACGP which dynamically adjusts entanglement generation probabilities based on observed inter-core communication patterns. We evaluate these approaches using an extended SeQUeNCe simulator on mesh-based multi-core architectures on real benchmark circuits. Results show that ACGP significantly reduces average teleportation latency compared to ODG and CGP. Although pre-generation introduces fidelity degradation due to storage time, entanglement purification effectively restores fidelity with minimal impact on latency. These results demonstrate that adaptive entanglement managements can substantially improve communication efficiency in scalable quantum multi-core systems.

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.

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.

Coherence and fidelity aware routing in quantum networks

In this study, for the first time, a novel routing and purification approach for quantum networks is presented, using the end-to-end (E2E) relative entropy of coherence (REC) together with E2E fidelity to determine the purification level and the feasibility of candidate paths.