Dynamic Matrix Decomposition (DMD)

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Abstract: This paper presents a novel dynamic matrix decomposition (DMD) algorithm leveraging quantum computing principles to efficiently decompose large matrices. We introduce a mechanism that utilizes quantum entanglement and superposition to enhance matrix computation, offering a significant acceleration and efficiency improvement compared to classical methods. The core of the algorithm lies in the manipulation of quantum states to achieve optimized matrix operations. The proposed method offers a promising pathway towards faster and more scalable matrix calculations, particularly applicable to large-scale matrix problems.

DOI: 10.5281/zenodo.22573636

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