ABSTRACT:

Quantum datacenter (QDC) architectures must support communication among quantum processing units (QPUs) under limited communication qubits, optical switching and measurement re sources, probabilistic entanglement generation, and physical-layer noise. This paper presents Q-REFINE, a framework for Quantum Resource Exploration via Factorial & Iterative N-factor Experiments. For a given QDC topology, it answers two design questions, namely which physical-layer factors and combinations of factors most change the completion rate, the rate at which requests are served above a fidelity threshold, and over what range improving each factor still pays off. Q-REFINE combines a discrete-event simulator, controllable inter-QPU request workloads, topology-specific resource descriptions, and N-factor design of experiments, and we apply it to five topology families, Fat-tree, Clos, QFly, BCube and DCell. For each topology, load selection first fixes the concurrency limit, the number of requests in service at once, at the smallest value at which the completion rate saturates. At that limit, a 2N full-factorial design of experiments ranks the N factors and their interactions by their share of the response variation, and one factor-at-a-time (OFAT) sweeps around the favorable corner, where every factor is at its best level, trace each factor’s response curve. The designer can then weigh where improvements pay off against current component costs. Although we use a particular workload, performance metric, and configurations, the framework applies to any workload, metric(s), or configurations

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