Quantum Bayesian Probability Network (QBPN)

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper presents a novel approach to Quantum Bayesian Probability Networks (QBPNs) – a framework designed to accurately predict complex system behavior across diverse domains. The core claim is the existence of a formally validated QBPN capable of modeling long-term evolution and emergent phenomena, leveraging the principles of quantum mechanics and Bayesian statistical inference. We explore the integration of quantum mechanics, Bayesian inference, and dynamic state representation, aiming to overcome limitations in traditional probabilistic models. This research addresses the critical challenge of creating a robust and adaptable model for systems exhibiting complex dynamics and unpredictable behavior.

DOI: 10.5281/zenodo.22491204

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