Nonlinear Matrix Decomposition of Quantum Entanglement Analysis

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the application of Nonlinear Matrix Decomposition (NMD) to quantum entanglement analysis, aiming to enhance the accuracy of characterizing entanglement properties and strength, particularly in the context of high-dimensional quantum states. The core claim is that NMD offers a novel approach to tackle the complexity inherent in entangled states, translating them into more computationally tractable models. We investigate the potential of this method to improve the precision of entanglement measurement and provide a robust framework for analyzing entangled systems. This research focuses on leveraging the mathematical foundations of quantum entanglement to develop a modified NMD algorithm that addresses specific challenges in data analysis. The paper details the design and implementation of the NMD technique, exploring its efficacy through simulations and preliminary experimental results. Finally, the paper presents a comprehensive analysis of the potential benefits and limitations of this approach, highlighting the contributions to the field of quantum entanglement analysis.

DOI: 10.5281/zenodo.22466996

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