基于量子纠缠的自适应机器学习算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel machine learning algorithm based on quantum entanglement and quantum superposition. The algorithm leverages the unique properties of quantum mechanics to enhance computational efficiency and enable more sophisticated analysis. We propose a method for implementing probabilistic reasoning and logical inference, utilizing quantum phenomena to overcome the limitations of classical computing. The core mechanism centers around harnessing quantum entanglement to guide the learning process and achieve a significant speedup in certain machine learning tasks. This research explores the potential of quantum computing to revolutionize machine learning, specifically focusing on adaptive learning and enhanced computational power. The paper details the theoretical underpinnings, implementation details, and preliminary experimental results demonstrating the algorithm's effectiveness.

DOI: 10.5281/zenodo.22198863

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