The Quantum Entanglement Optimization via Probabilistic Modeling

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, presents a unique opportunity for revolutionary computational and communication paradigms. However, harnessing this phenomenon effectively requires sophisticated optimization techniques. This paper explores the application of probabilistic modeling to optimize complex quantum systems, particularly those involving multi-particle entanglement. We propose a novel framework that transforms the inherent evolution of quantum states into a probabilistic process, leveraging the properties of entanglement to control and optimize the behavior of these systems. The core mechanism centers around the design of a probabilistic computation method, offering a potential pathway to enhance quantum computing and quantum communication efficiency. This work addresses a critical gap in our understanding of optimizing complex quantum systems, offering a promising approach to tackling challenges in these rapidly evolving fields.

DOI: 10.5281/zenodo.22507126

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