基于量子自适应的超分辨率矩阵分解

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel method for matrix decomposition utilizing quantum-adaptive matrix decomposition. Traditional matrix decomposition methods often suffer from computational inefficiency, particularly when dealing with large matrices. This work proposes a quantum-adaptive approach that dramatically improves computational efficiency by leveraging the unique properties of quantum self-adaptation within the matrix decomposition process. The core mechanism involves a carefully designed quantum algorithm that accelerates the decomposition process significantly, offering substantial benefits for large-scale matrix applications. We present preliminary results demonstrating the effectiveness of this method, highlighting its potential to revolutionize the field of matrix analysis.

DOI: 10.5281/zenodo.22255161

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