Quantum-Enhanced Bayesian Network Propagation

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel algorithm for Bayesian network propagation, utilizing quantum algorithms to accelerate inference and enhance the accuracy of network analysis. Traditional Bayesian network methods are computationally demanding, limiting their applicability in complex scenarios. We propose a framework that leverages quantum walk and quantum Monte Carlo to explore network structure and update probabilities with significantly improved efficiency. The core mechanism centers around employing quantum algorithms to tackle the inherent computational bottlenecks associated with Bayesian network inference. This approach promises a substantial improvement in speed and accuracy, opening doors to broader applications across various domains.

DOI: 10.5281/zenodo.22324634

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