High-Order Matrix Dynamics and Quantum Entanglement

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the potential of high-order matrix dynamics, augmented with quantum entanglement, to accelerate optimization processes, particularly within matrix decomposition and linear algebra problems. We explore a novel approach leveraging quantum entanglement to enable parallel computation during the optimization process, offering a potential paradigm shift from traditional algorithms. The core mechanism centers on utilizing entanglement to enhance the computational capabilities of the optimization process, aiming for significantly faster results in key areas of matrix analysis. The research focuses on demonstrating the efficacy of this approach through theoretical analysis and preliminary numerical simulations, highlighting its potential impact on the field of matrix optimization.

DOI: 10.5281/zenodo.22196976

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