Machine Learning Framework Based on Quantum Entanglement

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel machine learning framework predicated on the principles of quantum entanglement. We explore the potential of leveraging this phenomenon to enhance machine learning capabilities, specifically focusing on improved learning efficiency and the ability to tackle more complex problems. The framework's core mechanism centers around designing a quantum-enhanced learning algorithm that exploits the inherent fragility of entanglement. We detail the design of the framework, highlighting its key components and potential benefits. The paper concludes with a discussion of the challenges and future directions for this research.

DOI: 10.5281/zenodo.22624915

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