  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.
