Title: Quantum Entanglement-Based Probability Space Modeling (QE-PSM)

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, offers a unique perspective on probabilistic outcomes and the behavior of complex systems. This paper explores the application of quantum entanglement to probability space modeling, aiming to extend classical probability models to encompass the inherent uncertainty and emergent behaviors observed in systems exhibiting quantum phenomena. We propose a novel algorithm, Quantum-Inspired Probability Space Modeling (QE-PSM), that leverages entanglement as a fundamental probability field, allowing for a more accurate and dynamic representation of random processes. The core mechanism focuses on incorporating entanglement into a probabilistic framework, potentially surpassing the limitations of conventional methods in simulating complex systems. This research addresses the inherent challenges of modeling uncertainty and provides a promising avenue for advancing simulations in diverse fields, including physics, chemistry, and materials science.

DOI: 10.5281/zenodo.22278121

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