Core Claim: Develop a quantum spin-based non-symmetric matrix multiplication algorithm capable of efficiently handling matrices with non-symmetric properties, exhibiting adaptive computational efficiency.

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

The efficient computation of matrices, particularly those with non-symmetric properties, remains a significant challenge in various scientific and engineering fields. This paper presents a novel quantum spin-based matrix multiplication algorithm designed to address this challenge. We introduce a dynamic adjustment mechanism leveraging the intrinsic self-adaptivity of quantum spin systems to optimize the matrix multiplication process. The algorithm's core mechanism involves a carefully designed quantum circuit that adapts the matrix multiplication operation based on the specific characteristics of the input matrix. This adaptive approach significantly enhances computational efficiency, offering a potential breakthrough in matrix multiplication performance. We demonstrate the effectiveness of this algorithm through theoretical analysis and preliminary experimental validation, highlighting its ability to outperform traditional approaches in certain scenarios. The research explores the potential of quantum spin systems to provide a fundamentally new paradigm in matrix multiplication, offering a promising pathway toward more efficient and scalable computations.

DOI: 10.5281/zenodo.22463515

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