Quantum Entangled Matrices: An Optimization Algorithm

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum entanglement offers a fundamentally different approach to matrix computation, potentially surpassing classical methods in certain scenarios. This paper proposes a novel optimization algorithm specifically tailored for quantum entanglement, aiming to enhance the efficiency of matrix operations. We introduce a quantum state manipulation scheme leveraging entanglement to achieve a significant speedup in calculations, addressing limitations inherent in current quantum computing architectures. The core mechanism centers around strategically manipulating entangled qubit states to represent and manipulate matrix elements, offering a pathway to dramatically accelerate matrix computations. The algorithm's novelty lies in its incorporation of quantum entanglement as a key computational resource, providing a unique advantage over existing optimization strategies. We detail the algorithm's architecture, the quantum circuit implementation, and preliminary results demonstrating improved performance compared to classical methods. This work explores the potential of entanglement to fundamentally alter matrix computation, presenting a promising avenue for advancing quantum computing capabilities.

DOI: 10.5281/zenodo.22442173

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