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Quantum Entanglement-Based Non-Linear Geometric Optimization Algorithm

Jincheng Zhang

Published Sep 4, 2026• 0 citations
Publisher

Abstract

Quantum entanglement, a fundamental phenomenon in quantum mechanics, offers a potentially transformative approach to optimization problems. This paper investigates the design and implementation of a novel geometric optimization algorithm leveraging quantum entanglement to achieve global optimality beyond the capabilities of classical methods. We propose a framework that utilizes entangled states to represent the problem space, enabling a novel form of interaction and computation that surpasses conventional optimization techniques. The core mechanism centers around constructing a quantum entanglement system to transform the optimization problem into a correlated quantum state, facilitating a robust and efficient solution. This approach seeks to address the limitations of classical optimization algorithms in tackling complex geometric shapes, ultimately offering a significant advancement in this field.

DOI
10.5281/zenodo.22293756

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