Efficient entanglement scheduling in quantum data centers

Modular quantum computing scales quantum systems by connecting Quantum Processing Units (QPUs) through a quantum network. A key challenge in such architectures is efficiently scheduling entanglement generation to enable distributed circuit execution. This work investigates how architectural factors—such as network topology, switch placement, and communication qubit allocation—impact entanglement scheduling and resource utilization. Through simulation, we evaluate static and dynamic scheduling strategies under realistic constraints including probabilistic entanglement generation, limited communication qubits, reconfiguration delays, and qubit coherence time. Our results show that dynamic scheduling performs better in highly connected architectures, while sparse topologies lead to contention and entanglement loss. We also profile Bell State Measurement (BSM) demand to identify architectural bottlenecks and inform provisioning. These insights highlight the critical role of architecture in enabling scalable, efficient distributed quantum computing.