基于量子自旋场论的非对称矩阵运算算法

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper presents a novel algorithm for matrix computation based on quantum spin networks (QSNs). We propose a method that leverages the inherent properties of QSNs, specifically their non-associative nature and dynamic connectivity, to achieve significantly improved computational efficiency, particularly when dealing with matrices exhibiting significant non-symmetry. The core mechanism focuses on dynamically adjusting the connectivity of the QSN network during the matrix computation process, optimizing for performance based on the matrix's specific structure. We demonstrate the effectiveness of this approach through theoretical analysis and preliminary experimental results, showcasing substantial gains in computational speed and memory usage compared to traditional matrix multiplication methods, especially for matrices with complex non-symmetry.

DOI: 10.5281/zenodo.22463055

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