基于量子拓扑的机器学习加速器

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum topology offers a fundamentally new approach to computation by leveraging the unique properties of quantum states. This paper introduces a novel machine learning accelerator based on quantum topology, aiming to significantly enhance the training and inference speed of various machine learning algorithms. We detail the core mechanism of utilizing quantum superposition and entanglement to accelerate these processes, demonstrating its potential to overcome the limitations of classical computation in specific scenarios. This work explores the fundamental principles of quantum topology and presents a practical implementation of the proposed accelerator, highlighting its advantages and potential impact on machine learning research and applications.

DOI: 10.5281/zenodo.22205773

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