Quantum Topology Neural Networks

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum Topology Neural Networks (QTN) represents a novel approach to neural network architecture leveraging the principles of quantum topology. This paper explores the potential of QTN to enhance learning capabilities and feature extraction through the integration of quantum entanglement and topological features. We present a conceptual framework for QTN, detailing its core mechanism involving the manipulation of quantum states to facilitate data processing and representation. The research emphasizes the unique advantages of quantum topology in neural network design, offering a potential paradigm shift in computational modeling. The paper concludes with a discussion of the challenges and future directions for research in this burgeoning field.

DOI: 10.5281/zenodo.22289399

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