Quantum Entanglement-Based Adaptive Matrix Decomposition

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum entanglement, a perplexing phenomenon of quantum mechanics, holds immense potential for revolutionizing computation. This paper investigates a novel approach to quantum state decomposition, leveraging the unique properties of entangled states to achieve rapid and precise separations, and exploring its application to quantum computing. The core mechanism centers around designing a 'correlations matrix' computation method that dynamically adjusts entanglement strength, thereby enhancing computational accuracy and efficiency. We propose a new framework for efficiently manipulating entangled states, offering a potential breakthrough in tackling the limitations of current quantum computation techniques. This work contributes to the advancement of quantum algorithms and provides a foundational understanding of the potential of entanglement-based decomposition.

DOI: 10.5281/zenodo.22486990

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