Quantum Entanglement Computing Optimization via Nonlinear Models

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents a unique opportunity for computation exceeding the capabilities of classical systems. However, harnessing this potential requires sophisticated optimization techniques, particularly when dealing with the inherent challenges of quantum systems. This paper explores the design and application of a novel optimization algorithm based on nonlinear models to leverage quantum entanglement for enhanced computational efficiency. We propose a method that transforms entanglement-based problems into a non-linear framework, allowing for the exploitation of quantum properties to achieve significantly faster computation times. This work addresses a critical challenge in quantum computing, focusing on the potential of non-linear models to unlock new optimization strategies.

DOI: 10.5281/zenodo.22513392

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