基于自适应高阶矩阵的量子计算优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel quantum computation optimization framework based on adaptive high-order matrix techniques. Traditional optimization methods often struggle with complex environments, necessitating pre-defined parameters. This framework leverages the unique properties of high-order matrices to dynamically adjust parameters, enabling a more flexible and efficient optimization process for quantum computation. We present a theoretical analysis and preliminary experimental results demonstrating the efficacy of this approach in optimizing quantum circuit parameters, ultimately leading to improved performance. The core mechanism focuses on intelligently tuning the matrix's structure to address specific challenges within quantum algorithms.

DOI: 10.5281/zenodo.22630297

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