Quantum Entanglement Adaptive Probability Model

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel probabilistic model predicated on the principles of quantum entanglement. We propose a dynamic adjustment mechanism that automatically tunes model parameters and assumptions, enhancing predictive accuracy and reliability. The core concept lies in leveraging the unique properties of quantum entanglement to achieve adaptive parameter evolution without explicit programming of these parameters. This approach offers a paradigm shift in probabilistic modeling, potentially surpassing the limitations of traditional methods in complex, dynamic scenarios. The model's design emphasizes robustness and adaptability, offering a promising avenue for improved predictive capabilities across diverse fields.

DOI: 10.5281/zenodo.22331709

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