Quantum Topology: Adaptive Feature Extraction

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum topology, a fundamentally different approach to quantum systems compared to traditional quantum mechanics, offers a promising pathway towards enhanced computational capabilities. This paper explores a novel method for extracting key features from quantum systems through dynamic topology manipulation, aiming to automate the process and improve system performance. We propose a framework that leverages the inherent topological properties of quantum systems to dynamically adjust feature representations, enabling self-learning and optimization. The core mechanism centers around applying transformations that preserve and modify the quantum system's topology, enabling the system to adapt its representation to specific tasks. This research investigates the potential of this approach to overcome limitations of existing feature extraction techniques, particularly in scenarios requiring high computational efficiency and adaptability.

DOI: 10.5281/zenodo.22294805

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