基于量子纠缠的自适应矩阵运算

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper presents a novel approach to matrix computation leveraging the principles of quantum entanglement. We propose a self-adaptive matrix multiplication algorithm that utilizes quantum entanglement to optimize the computational process, resulting in significant improvements in efficiency compared to traditional methods. The core mechanism centers around establishing entangled states between matrix elements, allowing for instantaneous correlations to guide the computation. We demonstrate the effectiveness of this framework through rigorous analysis and simulation, highlighting its potential to revolutionize matrix operations. The paper concludes with a discussion of future research directions and potential applications.

DOI: 10.5281/zenodo.22321126

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