Quantum Entanglement-Based Global Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of quantum entanglement to a novel global optimization algorithm. Traditional global optimization methods often struggle with complex problems, requiring extensive manual design and computational effort. We propose a quantum-enhanced approach leveraging entanglement to potentially achieve significant improvements in efficiency and scalability. The core mechanism centers around utilizing entanglement to facilitate a more structured and parallel exploration of the search space, ultimately leading to faster convergence and better solution quality. This research investigates the practical implications of this approach and analyzes its potential for broader applicability within complex optimization scenarios.

DOI: 10.5281/zenodo.22195591

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