Quantum Entanglement-Based Probability Distributions

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement, a fundamental phenomenon in quantum mechanics, offers a unique approach to probability distribution modeling. This paper explores the potential of harnessing this principle to create novel statistical frameworks, specifically designed to capture probabilistic systems with strong correlations. We introduce a novel algorithm predicated on quantum entanglement, aiming to move beyond traditional deterministic models by enabling inherent, non-deterministic probabilistic behavior. The core claim is that this framework provides a pathway towards improved precision in modeling complex probabilistic systems. The paper details the algorithm's mechanism, highlighting its potential advantages over existing probabilistic models. This work contributes to a growing body of research exploring the application of quantum mechanics to statistical analysis and modeling.

DOI: 10.5281/zenodo.22192298

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