Bayesian Networks (BN) are probabilistic graphical models that are widely used for uncertainty modeling, stochastic prediction and probabilistic inference. A Quantum Bayesian Network (QBN) is a quantum version of the Bayesian network that utilizes the principles of quantum mechanical systems to improve the computational performance of various analyses. In this paper, we experimentally evaluate the performance of QBN on various IBM QX hardware against Qiskit simulator and classical analysis. We consider a 4-node BN for stock prediction for our experimental evaluation. We construct a quantum circuit to represent the 4-node BN using Qiskit, and run the circuit on nine IBM quantum devices: Yorktown, Vigo, Ourense, Essex, Burlington, London, Rome, Athens and Melbourne. We will also compare the performance of each device across the four levels of optimization performed by the IBM Transpiler when mapping a given quantum circuit to a given device. We use the root mean square percentage error as the metric for performance comparison of various hardware.

中文翻译：

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IBM QX 硬件上量子贝叶斯网络的实验评估

贝叶斯网络 (BN) 是概率图形模型，广泛用于不确定性建模、随机预测和概率推理。量子贝叶斯网络 (QBN) 是贝叶斯网络的量子版本，它利用量子力学系统的原理来提高各种分析的计算性能。在本文中，我们通过实验评估 QBN 在各种 IBM QX 硬件上针对 Qiskit 模拟器和经典分析的性能。我们考虑使用 4 节点 BN 进行股票预测以进行实验评估。我们使用 Qiskit 构建了一个量子电路来表示 4 节点 BN，并在九个 IBM 量子设备上运行该电路：Yorktown、Vigo、Ourense、Essex、Burlington、伦敦、罗马、雅典和墨尔本。在将给定的量子电路映射到给定的设备时，我们还将比较每个设备在 IBM Transpiler 执行的四个优化级别上的性能。我们使用均方根百分比误差作为衡量各种硬件性能的指标。