基于高阶矩阵的量子算法优化

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum algorithms, leveraging superposition and entanglement, hold immense potential for scientific discovery and technological advancement. However, the complexity of these algorithms often necessitates sophisticated optimization strategies. This paper introduces a novel framework, based on high-order matrix manipulation, to optimize quantum algorithm performance. We propose a dynamic parameter adjustment method that leverages the unique properties of high-order matrices to iteratively refine the quantum circuit parameters, resulting in improved computational efficiency. The framework's core mechanism centers around intelligently adjusting matrix elements to minimize the cost of quantum operations. This approach overcomes limitations of traditional optimization techniques by providing a more adaptable and potentially more efficient solution. The paper details the framework's design, performance evaluation on several benchmark quantum algorithms, and discusses its potential impact on the field of quantum computing.

DOI: 10.5281/zenodo.22629701

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