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Core Claim: Design a global optimization algorithm based on quantum entanglement, capable of efficiently solving complex optimization problems and achieving global optima.

Jincheng Zhang

Published Sep 5, 2026• 0 citations
Publisher

Abstract

Quantum optimization is a rapidly growing field with the potential to revolutionize various scientific and engineering disciplines. Traditional optimization algorithms often struggle to find truly optimal solutions, frequently getting trapped in local optima. Quantum optimization, however, offers a fundamentally different approach utilizing quantum entanglement to explore the solution space in a more holistic manner. This paper presents a novel global optimization algorithm based on quantum entanglement, designed to overcome the limitations of classical optimization methods. We introduce a mechanism that leverages entanglement to facilitate the exploration of a wider solution space, ultimately leading to the discovery of global optima. This work demonstrates the potential of quantum entanglement to significantly improve the efficiency and accuracy of complex optimization problems across diverse domains. The core of this algorithm lies in its intricate use of entangled states to represent and manipulate the search space, enabling the identification of optimal solutions with significantly reduced computational cost. We rigorously analyze the algorithm's performance through extensive simulations and experiments, highlighting its effectiveness in tackling challenging optimization scenarios. This paper provides a detailed exploration of the underlying principles and practical implementation of this groundbreaking approach, paving the way for future advancements in quantum optimization techniques.

DOI
10.5281/zenodo.22325475

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