Quantum-Enhanced Bayesian Network Propagation for Risk Assessment

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the potential of quantum computing to enhance Bayesian Network (BN) propagation for risk assessment. Traditional BN models struggle with scalability and computational complexity, particularly when dealing with long-time horizons and complex scenarios. We propose a novel framework that leverages quantum algorithms to accelerate probabilistic model updates, thereby improving accuracy and enabling more sophisticated risk assessment. This work explores the feasibility of quantum-enhanced BN propagation through the application of variational quantum eigensolver (VQE) and quantum annealing techniques. The core claim is that quantum computing offers a significant advantage in risk assessment by improving model accuracy and providing a more robust representation of uncertainty.

DOI: 10.5281/zenodo.22187318

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