基于自适应拓扑的量子特征提取

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper presents a novel quantum feature extraction algorithm, termed "Adaptive Topological Feature Extraction" (ATFE), designed to efficiently extract complex system features leveraging the unique properties of quantum computation. The algorithm utilizes a dynamically constructed topological structure to represent and analyze data, offering a significant advantage over traditional methods in terms of computational efficiency and sensitivity to data variations. The core mechanism centers around the creation of a topologically-constrained representation, which is then analyzed using quantum algorithms to reveal underlying patterns and relationships within the input data. This paper explores the potential of ATFE to enhance data analysis and model building, specifically focusing on its application to complex systems. We demonstrate the algorithm's effectiveness through a series of illustrative examples and discuss its future directions.

DOI: 10.5281/zenodo.22295655

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