Quantum-Enhanced Bayesian Inference for Predictive Modeling

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum-enhanced Bayesian inference offers a promising paradigm shift in predictive modeling, potentially surpassing the limitations of classical methods. This paper explores the application of quantum superposition to enhance Bayesian inference, specifically focusing on improving the accuracy of complex systems. We outline a novel algorithm that utilizes quantum superposition to represent probability distributions, enabling efficient exploration of parameter spaces and ultimately leading to more accurate predictions. The core mechanism centers around exploiting the unique properties of quantum systems to accelerate the Bayesian inference process. The research presents a theoretical framework and preliminary implementation demonstrating the potential of this approach.

DOI: 10.5281/zenodo.22298392

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