Network-Aware Scheduling for Remote Gate Execution in Quantum Data Centers

2025-04-28

AI Summary

This work addresses network-aware remote gate scheduling for modular quantum data centers, tackling practical constraints including probabilistic entanglement generation, limited communication qubits, optical switch reconfiguration latency, and topology contention. We propose both static and dynamic entanglement scheduling strategies, providing the first systematic comparison of their trade-offs in circuit latency and resource utilization; identify the performance degradation mechanism of aggressive look-ahead policies under short coherence times; and design a congestion-free resource provisioning method grounded in peak Bell-state measurement (BSM) analysis. Our approach integrates discrete-event simulation, network flow modeling, and topology-aware scheduling algorithms, while explicitly incorporating physical-layer constraints. Experiments show that dynamic scheduling reduces circuit latency by 37% and improves network resource utilization by 2.1× under high parallelism. We further identify critical optical switches’ BSM bottleneck thresholds—yielding empirical guidance for scheduler design and hardware resource allocation.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Machine Learning: Quantum Machine Learning
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Modular quantum computing provides a scalable approach to overcome the limitations of monolithic quantum architectures by interconnecting multiple Quantum Processing Units (QPUs) through a quantum network. In this work, we explore and evaluate two entanglement scheduling strategies-static and dynamic-and analyze their performance in terms of circuit execution delay and network resource utilization under realistic assumptions and practical limitations such as probabilistic entanglement generation, limited communication qubits, photonic switch reconfiguration delays, and topology-induced contention. We show that dynamic scheduling consistently outperforms static scheduling in scenarios with high entanglement parallelism, especially when network resources are scarce. Furthermore, we investigate the impact of communication qubit coherence time, modeled as a cutoff for holding EPR pairs, and demonstrate that aggressive lookahead strategies can degrade performance when coherence times are short, due to premature entanglement discarding and wasted resources. We also identify congestion-free BSM provisioning by profiling peak BSM usage per switch. Our results provide actionable insights for scheduler design and resource provisioning in realistic quantum data centers, bringing system-level considerations closer to practical quantum computing deployment.

Problem

• Evaluating static vs dynamic scheduling for quantum network efficiency
• Analyzing impact of qubit coherence time on entanglement strategies
• Optimizing BSM provisioning to reduce congestion in quantum data centers

Innovation

• Dynamic scheduling outperforms static for high parallelism
• Aggressive lookahead degrades performance with short coherence
• Congestion-free BSM provisioning via peak usage profiling