基于量子拓扑的机器学习优化器

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel machine learning optimization framework based on quantum topology. We explore the potential of quantum mechanics, specifically superposition and entanglement, to significantly accelerate training and inference processes for machine learning algorithms. We propose a new architecture that leverages these quantum properties to enhance the computational efficiency of various machine learning tasks. The core mechanism involves manipulating quantum states to represent and process data, potentially unlocking faster and more robust learning. This research aims to provide a foundation for future advancements in machine learning by incorporating the unique capabilities of quantum systems.

DOI: 10.5281/zenodo.22205800

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