High-Order Quantum State Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing holds tremendous potential, yet efficient quantum algorithms remain a significant challenge. This paper investigates a novel quantum algorithm designed to leverage the unique properties of high-order quantum states to enhance the performance of quantum algorithms, particularly within the domains of machine learning and optimization. The core mechanism centers around a quantum optimization strategy that exploits superposition, entanglement, and interference to achieve improved computational efficiency. We present a detailed theoretical analysis and preliminary experimental validation demonstrating the algorithm's efficacy in a specific optimization problem. The paper concludes with a discussion of future research directions and the potential impact of this approach on the field of quantum computing.

DOI: 10.5281/zenodo.22301028

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