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Updated: May 10, 2025

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通过优化算法和维度减小来探索量子控制景观和解决方案空间复杂性

Haftu W Fentaw1,2, Steve Campbell3,4, Simon Caton5,4

  • 1School of Computer Science, University College Dublin, Dublin, Ireland. haftu.fentaw@ucdconnect.ie.

Scientific reports
|April 26, 2025
PubMed
概括

了解量子控制环境 (QCL) 对于有效的量子策略至关重要. 主要组件分析 (PCA) 和特定的机器学习算法,如遗传算法 (GA),有助于优化量子比特控制.

关键词:
遗传算法 (GA) 是一种基因算法.主要组成部分分析 (PCA)量子控制的景观 (QL)强化学习 (RL) 是一种强化学习.随机梯度下降 (SGD) 是指随机梯度下降.

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