Quantum Adaptive Probability Model

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Adaptive Probability Model is a novel approach to probabilistic modeling that leverages quantum mechanics to enhance prediction accuracy, particularly for complex systems. This paper explores the potential of utilizing quantum properties to simulate probabilistic processes and build a more robust and accurate model for complex behavior. The core mechanism centers on employing a quantum-enhanced probability model, offering an alternative to classical probability methods. We present a detailed theoretical framework and preliminary experimental results demonstrating the effectiveness of this approach. The investigation focuses on the inherent advantages of quantum computation in capturing the nuances of probabilistic outcomes, promising a significant leap forward in predictive capabilities across diverse fields.

DOI: 10.5281/zenodo.22195584

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