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基于量子纠缠的概率论框架

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

This paper introduces a novel probabilistic framework predicated on the principles of quantum entanglement. Traditional probability theory often relies on classical models, while our proposed framework leverages quantum entanglement to enhance the accuracy of probability distributions and unlock potential advantages within quantum computation. We establish a conceptual foundation for "quantum entanglements" and their influence on the generation of probabilistic outcomes. This work explores the potential of this approach to address limitations of classical probability and provides a roadmap for future research in quantum probabilistic modeling. The core mechanism involves introducing a new concept, the "quantum entanglement variable," which subtly influences the probabilistic outcome through entanglement, enhancing the precision of the model.

DOI
10.5281/zenodo.22205683

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Quantum entanglement, a bizarre phenomenon where two or more particles become linked and share the same fate, has captivated physicists and philosophers alike. This paper explores the potential of leveraging quantum entanglement to revolutionize probability theory and, consequently, quantum computation. We propose a novel probabilistic model predicated on the inherent nature of quantum entanglement, aiming to provide a deeper understanding of probability and enhance quantum machine learning capabilities. The core of this work lies in establishing a probabilistic model intrinsically linked to the quantum entanglement mechanism, offering a fundamentally new approach to interpreting and optimizing quantum computations. The model will be designed to function as a computational foundation for quantum algorithms, addressing the limitations of traditional probabilistic methods. This paper will detail the theoretical framework, preliminary implementation, and potential applications of this new model.
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